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PODIUM ABSTRACT COMPENDIUM
Advances in Bioanalytics and Biomarkers Assay Development and Screening
Automation and High Throughput Technologies Biologics Discovery Cellular
Technologies Data Analysis and Informatics Drug Target Strategies Micro- and
Nano Technologies Molecular Libraries Precision Medicine Technologies
Podium presentations are organized into 10 educational tracks. Podium abstracts
and speaker information are organized first by track and then by session below.
To search for a specific speaker use the 'Find' functionality in your browser
(usually Ctrl + F).
To view a complete schedule of podium presentations and schedule of events for
SLAS2020 and to view speaker bios and photos, please visit the SLAS2020 Event
Scheduler.
ADVANCES IN BIOANALYTICS AND BIOMARKERS
Track Chair(s): Andreas Luippold, Ph.D., Boehringer Ingelheim (Germany) and
Martin Giera, Ph.D., Leiden University Medical Center (The Netherlands)
LABEL-FREE BIOANALYTICAL TECHNIQUES
Session Chair: Daniel Bischoff, Ph.D., Boehringer Ingelheim (Germany)
* Combining Arrays and Mass Spectrometry for High-Throughput Experiments in
Chemistry and Biology
Milan Mrksich, Northwestern University
This talk will describe an approach for using mass spectrometry and arrays of
self-assembled monolayers to perform quantitative experiments in
high-throughput. The arrays are prepared by immobilizing small molecules,
proteins, peptides and carbohydrates to self-assembled monolayers of
alkanethiols on gold. These arrays are then treated with reactants—either
chemical reagents or enzymes—and then analyzed using the SAMDI technique to
identify the masses of substituted alkanethiolates in the monolayer and
therefore a broad range of reactivities and post-translational
modifications—including kinase, protease, methyltransferase and
carbohydrate-directed modifications—and for discovering chemical reactions.
This talk will describe applications to high throughput experiments,
including the discovery of reactions, the use of carbohydrate arrays to
discover novel enzymes, the preparation of peptide arrays to profile the
enzyme activities in cell lysates and high-throughput screening to discover
novel reactions and small molecular modulators.
These examples illustrate the broad capability of the SAMDI method to profile
and discover molecular activities in the molecular sciences.
* Establishing Capabilities for (Ultra)High-Throughput Mass Spectrometry at
Merck: Reflections from “Year One”
David McLaren, MSD.
Long a prized analytical tool for low and medium-throughput applications,
recent innovations in mass spectrometry (MS) are changing the way
pharmaceutical scientists apply MS to challenges requiring truly
high-throughput. Such endeavors include HTS, parallel medicinal chemistry and
protein engineering with emerging needs in drug metabolism and
pharmacokinetics as well. At Merck, we have embarked on a journey to
incorporate these innovative uHT-MS capabilities in our own approach to drug
discovery. This presentation will highlight how we have deployed both a
fully-automated uHT-MALDI-MS instrument and the Echo-MS platform in a
cross-functional research setting.
As one example, we will demonstrate the application of the uHT-MALDI-MS to a
prototypical HTS assay for a kinase target. Here we will discuss how we have
enabled "on-demand" MALDI target plate preparation in both 384w and 1536w
formats and will further compare & contrast this data to those obtained using
a conventional Glo assay for both primary (single concentration) screening
and compound titrations.
We will also describe how we have leveraged the Echo-MS platform to triage
hits from an HTS designed to discover inhibitors of lipid metabolism which
employed a fluorescent, cell-free assay. Here, we will highlight a useful
“quench-and-read” sample preparation approach that allows for the selective
enrichment of hydrophobic analytes and which is also fully compatible with
direct acoustic transfer of the surface solution to the mass spectrometer for
analysis.
Throughout the presentation, we will highlight the relevant figures of merit
for each application and discuss our findings around the ‘critical
parameters’ whose optimization was important to enabling assay
success. Finally, we will conclude with a perspective of the future of our
journey in this space.
* CETSA® Beyond Soluble Targets: A Broad Application to Multi-Pass
Transmembrane Proteins
Aarti Kawatkar, AstraZeneca
Demonstration of target binding is a key requirement for understanding the
mode of action of new therapeutics. The cellular thermal shift assay (CETSA®)
has been introduced as a powerful label-free method to assess target
engagement in physiological environments. Here, we present the application of
live-cell CETSA® to different classes of integral multi-pass transmembrane
proteins using three case studies: the first showing a large and robust
stabilization of the outer mitochondrial five-pass transmembrane protein
TSPO, the second being a modest stabilization of SERCA2 and the last
describing an atypical compound-driven stabilization of the GPCR PAR2. Our
data demonstrated that using modified protocols with detergent extraction
after the heating step, CETSA® can reliably be applied to several membrane
proteins of different complexity. By showing examples with distinct CETSA®
behaviors, we aim to provide the scientific community with an overview of
different scenarios to expect during CETSA® experiments, especially for
challenging, membrane-bound targets.
* Novel Label-Free Interaction Technologies and Concepts and its Direct Impact
on Early Drug Discovery
Anders Gunnarsson, AstraZeneca
This presentation will disclose three new biophysical concepts and
technologies currently implemented in early drug discovery at AstraZeneca to
significantly enhance throughput, broaden chemical space or provide an
in-depth mechanistic understanding of drug targets and its oligomeric state
at the single-molecule level.
* Profiling >100 compounds at the speed and cost of 1.
Concentration-independent off-rate screening using optical biosensors
enable small scale (µmol) library synthesis followed by kinetic profiling
of the crude reaction products to rapidly inform structure-activity
relations (SAR) within a day of synthesis start.
* Overcoming limitations of profiling potent or covalent compounds with
surface-based biosensors. Using novel streptavidin-based concepts for
regeneratable surface chemistry significantly enhance throughput for potent
(long residence time) compounds and even enable assessment of covalent
compounds.
* Weighing single proteins by light. Label-free single-molecule scattering
measurements provide rapid information on the oligomeric state of proteins
under biochemical assay conditions and provide instant information on small
molecule-induced complex formation of unlabeled proteins.
TARGET ENGAGEMENT AND PATHWAYS
Session Chair: Gary Siuzdak, Ph.D., Scripps Research (USA)
* Activity Metabolomics
Gary Siuzdak, Scripps Research
The metabolome, the small molecule chemical entities involved in metabolism,
has traditionally been studied to identify biomarkers in the diagnosis and
prediction of disease. However, the value of metabolomics has been redefined
from a simple biomarker identification tool to a technology for the discovery
of active drivers of biological processes. In this presentation, I will
describe the molecular mechanisms by which the active cell metabolome affects
cellular physiology through modulation of other "omic" levels, including the
genome, epigenome, transcriptome and proteome. This concept of activity
screening guided by metabolomics to identify biologically active metabolites
or “activity metabolomics”, is having a broad impact on biology.
* Connecting High-Throughput Screening and Clinical Pharmacology Using Stable
Isotope Tracer Kinetics and Mass Spectrometry: Moving from Enzyme Activity to
in vivo Pathway Flux with the Same Assay.
Stephen Previs, MSD
Stable isotope-labeled substrates can be of broad use in cases where
target-based high-throughput screening aims to identify compounds that can
modulate enzyme activity. For example, depending on the source of a given
enzyme target, the presence of endogenous substrates or products can limit
one’s ability to follow substrate product conversions; utilization of a
labeled substrate(s) can help overcome background contamination. These same
isotope flux assays can then be used to follow the progression of hits in
later stages of development, including cell-based assays and in vivo studies.
Although stable isotope tracer kinetics, coupled with mass spectrometry-based
detection, can, therefore, connect all phases of drug discovery some caveats
should be recognized to ensure reliable data interpretations.
Our presentation will highlight key areas where the logic surrounding tracer
kinetics diverges as the application of flux analyses moves across different
stages of drug discovery. We will consider a case study that is focused on
lipid biology, i.e. modulating the level of glycosylated ceramides. We will
first outline how labeled substrates can be used to circumvent problems that
arise in early screening. We will then outline how tracers can be used to
progress molecules into later phases, including in vivo studies. Although one
can use virtually the same back-end mass spectrometry assay to measure the
formation of labeled products, several parameters change with regards to
dosing the labeled substrates. For example, when measuring enzyme activity in
early biochemical screening one needs to only measure the labeled product. In
contrast, in vivo studies must contend with the fact that substantial amounts
of “cold” (endogenous) substrate can exist, also, it may not be possible to
maintain a steady-state exposure to the labeled substrate. Consequently,
strategies need to account for temporal tracer dilution, most of which may
not be immediately obvious and/or difficult to correct.
In summary, the ability to measure stable isotope flux from precursors to
products can provide a bridge that spans the entire spectrum of drug
discovery and development. However, changes in the generation of a labeled
product do not immediately reflect changes in the metabolic activity of a
given target enzyme or pathway, it is possible to observe differences in the
abundance of a labeled product which reflect an unexpected modulation of
precursor metabolism. Although the example described here is focused on a
targeted screen, the logic has immediate implications with regards to
phenotypic screening; attention to a few details can influence essential
decision points.
* Novel Approaches to Quantitative Metabolomics
Loren Olson, Sciex
The major challenge in the field of metabolomics is to accurately identify
and quantify hundreds of metabolites in a single run. Recently variable
window SWATH acquisition has shown to identify a higher number of metabolites
compared to the traditional Data Dependent Acquisition (DDA) approach, thus
enabling broader metabolome coverage. Here we have implemented a variable
window SWATH acquisition method for enhanced quantitation of selected
metabolites using MS/MS, with reduced matrix interferences and improved
signal-to-noise. Using MS/MS fragments for metabolite quantitation provides
better selectivity, and ultimately increased sensitivity. Variable window
SWATH Acquisition provided quality quantitative data for metabolites in
complex matrix. Due to many coeluting metabolites in complex matrix, using
only the MS spectrum and retention time is often not sufficient for
metabolite identification. MS/MS information is necessary to obtain further
structural knowledge about the metabolite. Complete full scan MS and MS/MS
data is available in every SWATH file for improved ID. In addition, MS/MS
quantitation of metabolites often leads to lower detection limits due to
significantly improved signal to noise ratios vs MS data. Measuring the whole
MS/MS spectrum allows selection of the best fragments for metabolite
quantitation. SCIEX OS software combines comprehensive qualitative and
quantitative data analysis, making data processing easier and more efficient.
SWATH Acquisition on all detectable metabolites is successfully utilized for
identification, and accurate MS/MS level quantification of metabolites in
urine.
* NMR-Based Metabolomics in Drug Research: Cancer Metabolism
Martin Giera, Leiden University Medical Center
Metabolism and in particular central energy metabolism have evolved as
promising drug targets. A cutting edge technology that has become widely used
for studying oxygen consumption and extracellular acidification is the
Seahorse™ analyzer. While this technology allows for rapid label-free
screening it does not provide further details on the involved metabolites and
pathways. The quantitative analysis of these pathways, mainly involving
glycolysis, the tricarboxylic acid cycle (TCA) and adjacent pathways is
intrinsically very challenging. Several commercial solutions have evolved
over the years predominantly using mass spectrometry and a series of labeled
internal standards. However, many of these approaches suffer from long
analytical procedures and the need for special internal standards or kits. As
an alternative, we will discuss our NMR based workflow allowing the
quantitative analysis of several important pathways for example glycolysis,
TCA cycle, OxPhos, one-carbon metabolism and others. Our NMR based workflow
allows for the rapid and quantitative analysis of >80 metabolites without the
need for specialized kits or internal standards. The workflow can partially
be operated in an automated fashion using a KNIME workflow such as KIMBLE.
Moreover, flux analysis using 13C labeled materials can easily be adapted
resulting in kinetic information.
As an example for the usefulness of this workflow, we will discuss the
discovery of choline kinase α (CHKA) as a possible target for the prevention
of epithelial to mesenchymal transition (EMT) an important metastatic
process. Using NMR based analysis of metabolic changes during TGFα induced
EMT we could observe significant alterations in choline phosphorylation.
Following up on these results by using experimental inhibitors we could
identify CHKA as a crucial enzyme for the EMT phenotype.
TARGET AND MECHANISM IDENTIFICATION AFTER PHENOTYPIC SCREENS
Session Chair: Paul Tesar, Ph.D., Case Western Reserve University (USA)
* Identifying Compounds that Improve Neuromuscular Function
Lee Rubin, Dept of Stem Cell and Regenerative Biology, Harvard University;
Harvard Stem Cell Institute
Motor neuron diseases, as a class, are becoming increasingly well-known and
understood. However, effective therapeutics that preserve motor neurons are
still lacking. Motor neuron dysfunction is reflected, ultimately, in skeletal
muscle weakness and deterioration. Surprisingly, the involvement of muscle
cells themselves in diseases ranging from Spinal Muscular Atrophy, a
childhood developmental disorder, to sarcopenia – muscle weakness with aging
– is much less understood. I will describe two different projects – one
directed at promoting the survival of healthy motor neurons, the other at
improving muscle health. Both projects started with disease-relevant
cell-based screens and culminated in the discovery of new therapeutic
targets.
* Can Lattice Theory Help Find a Cure for Paralysis?
Nicola Richmond, GlaxoSmithKline
With the advent of the Human Genome Project came the industrialization of the
drug discovery process and a belief that combinatorial chemistry and high
throughput screening would deliver molecules with increased potency against a
single target of interest. Yet the attrition rate is still at the 10% mark
and there remain many human diseases for which no effective treatment exists.
As Swinney et. al. showed [1], there is compelling evidence that
first-in-class drugs are more likely to be found by assays that measure a
clinically meaningful phenotype in a physiologically relevant system rather
than a single target-based screening approach in an artificial setting. One
perceived issue with phenotypic screening is the lack of mechanistic
knowledge. Whilst understanding mechanism of action (MOA) is not a
prerequisite for FDA approval, it can guide a medicinal chemistry effort,
predict potential toxicities and help define patient populations for clinical
trials and ultimately the market place. There are several in vitro approaches
to target deconvolution. However, these tend to be of lower throughput and
better placed later in a screening cascade. So there is a real need for in
silico-based approaches that can be deployed early on in a drug discovery
program to identify potential MOAs. Using publicly available data on the
Published Kinase Inhibitor Set (PKIS) [2,3], we describe the application of
Formal Concept Analysis (FCA), an association mining technique with roots in
set theory, to the problem of deconvoluting a phenotypic screen. We describe
each compound in the PKIS by the set of kinases it inhibits. We then
construct a Galois Lattice, whose nodes correspond to a set of compounds
inhibiting a common set of kinases and where two nodes are connected if the
compound set of the child node is a subset of the compound set of the parent
node. Lattice nodes enriched with compounds that promote neurite outgrowth in
rat inform which kinases should be targeted when seeking small molecules that
encourage CNS axon repair following injury. The targets we identify using
this push-button approach, that can be placed in the hands of the bench
scientist, are in line with those identified in [3] and confirmed in siRNA
studies.
1. Swinney DC, Anthony J: How were new medicines discovered? Nat Rev Drug
Discov 2011, 10(7):507-19.
2. Drewry DH, Willson TM, Zuercher WJ: Seeding collaborations to advance
kinase science with the GSK Published Kinase Inhibitor Set (PKIS). Curr Top
Med Chem 2014, 14(3):340-2.
3. Al-Ali H, Lee DH, Danzi MC, Nassif H, Gautam P, Wennerberg K, Zuercher WJ,
Drewry DH, Lee JK, Lemmon VP, Bixby JL: Rational Polypharmacology:
Systematically Identifying and Engaging Multiple Drug Targets To Promote Axon
Growth. ACS Chem Biol 2015, 10(8): 1939-51.
* Cytosolic Proteome & Affinity-Based Target Identification (CPATI)
Xianshu Yang, MSD
Disease-relevant phenotypic screening directly identifies ligands that
modulate useful biology and constitutes a promising approach to the discovery
of novel pharmaceutical treatments. Beyond identifying chemicals with
desirable effects, it is important to identify the target(s) and mechanisms
that drive the desirable phenotype in complex cellular systems. However,
determining the relevant target(s) of phenotypically active ligands has often
proven slow or impossible, hampering drug discovery and development.
Recently, a few methodologies have emerged that enable detection of target
engagement in cells, but most of them require prior chemical modification of
either biologically active compounds or proteins. Here, we reported a novel
cytosolic proteome & affinity-based target identification platform (CPATI),
which is an unbiased, label-free and modification-free approach.
We applied CPATI to identify the candidate target protein(s) of three
compounds with Jurkat cells. First, native size-exclusion chromatography
(SEC) was used to separate cellular cytosol isolated from Jurkat cell lysis.
Second, using affinity-selection technology with our two-dimensional LC-MS
system, three compounds were screened with 170 SEC fractions. Cytosolic
fractions identified to have specific ligand binding were analyzed via
quantitative proteomics. A combination of the protein-bound ligand recovery
and target protein SEC elution profile revealed potential targets of test
compounds. Third, the thermal shift experiment was conducted to identify
proteins with elevated Tm in the presence of ligands, yielding a shortlist of
target proteins. Fourth, the target proteins were selected for recombinant
protein production and were validated in a binding assay with ligands.
Finally, top target proteins were recommended for further validation.
Three control ligands, compound A, compound B, and compound C were identified
to bind specifically with Jurkat cytosolic fractions. Their associated target
proteins NUDT1 (compound A), HSP90 (compound B), and PAK4 (compound C) were
identified from the Jurkat cytosol as their top candidate targets,
respectively. Compound A and compound B had a similar binding affinity (Kds)
with specific cytosolic fractions and recombinant proteins NUDT1 and
HSP90AA1/AB1, respectively. PPP3A-HSP90-CCT complexes were also identified.
Compound C is an ATP competitive kinase inhibitor and was identified to
associate with seventeen target proteins. Three recombinant proteins PRKACB,
PRKCQ and STK38 were confirmed as compound C-bound target proteins.
We also compared thermal shift experiments using compound C with compound
C-bound cytosolic fractions and Jurkat crude cytosol. Former samples
demonstrated advantage over later samples with short potential target
proteins and less false positive. This technology potentially provides a
broad application in target and biomarker identification from cells and
tissues.
* Combining Large-Scale in vitro Pharmacological Profiling and Human Cell-Based
Phenotypic Profiling Identifies Novel Mechanisms of Cardiovascular Toxicity
Ellen Berg, Eurofins Discovery
We have previously described a phenotypic signature associated with
cardiovascular toxicity relevant to vascular calcification and
atherosclerosis from a human primary cell-based coronary artery smooth muscle
cell model of vascular inflammation (BioMAP® CASM3C system). The key
biomarker activity in this signature is increased cell surface levels of
serum amyloid A (SAA) protein. Analysis of a large reference database (BioMAP
Phenotypic Profile Reference Database) of >3400 drugs and chemicals tested in
this assay identified 147 compounds exhibiting the signature at one or more
concentrations. For some of these compounds, specific mechanisms could be
implicated and include MEK inhibition, HDAC inhibition, glucocorticoid
(GR)/mineralocorticoid (MR) receptor agonism, IL-6 pathway agonism, as well
as modulation of mitochondrial NAD+/NADH ratios.
To further characterize the mechanisms underlying this toxicity-associated
signature, we took advantage of a second large reference database (BioPrint®
Pharmacology Profile Database) comprised of in vitropharmacological profiles
of drugs and chemicals screened against a broad range of targets (~148
receptors, ion channels, enzymes and transporters). We evaluated the in
vitropharmacology profiles for compounds exhibiting the phenotypic signature
associated with cardiovascular toxicity(data was available for 85 of 147
compounds). Target activities (in binding assays) enriched among the
phenotypic actives include glucocorticoid receptor (GR), androgen receptor
(AR), chloride channel (Cl-channel), ML2 (MT3), (5-Hydroxytryptamine receptor
2B (5-HT2B), peripheral benzodiazepine receptor (BZD), MT1 and ML1. The
identification of ML2 (MT3), also known as NAD(P)H quinone dehydrogenase 2 or
NQO2, and MT1 receptors is interesting as these are receptors for melatonin.
Melatonin has been reported to reduce blood pressure and also to reduce NAD+
levels through effects on NAMPT (nicotinamide phosphoribosyltransferase).
Recent studies have suggested that NAMPT may play a role in the pathogenesis
of atherosclerosis in experimental mouse models. In humans, serum
concentrations of NAMPT are an independent predictor of symptomatic carotid
stenosis in patients undergoing carotid endarterectomy.
These results show how the combined analysis of phenotypic and pharmacology
profiling data can confirm and extend our understanding of potential
mechanisms associated with the risk of cardiovascular toxicity. The pairing
of target-based and phenotypic assays is an efficient and effective means to
improve confidence in non-animal based screening of new drug leads for
potential liabilities.
Back to Top
ASSAY DEVELOPMENT AND SCREENING
Track Chair(s): Joe McGivern, Ph.D., Amgen (USA) and Melissa Crisp, Ph.D., Eli
Lilly (USA)
ADVANCED IMAGING & HIGH-CONTENT ASSAYS
Session Chair: James Evans, Ph.D., Phenovista Biosciences (USA)
* Applications of high content imaging in drug discovery using physiologically
relevant models of disease
Monica Chu, Phenovista
Cell-based imaging assays are used extensively for drug discovery; however,
challenges remain in the translation of in vitro data to in vivo outcome. We
are focused on generating relevant and translatable high content imaging data
from physiologically relevant cell models, including 3D structures. Case
studies will be presented on the application of high content imaging assays
to several complex, physiologically relevant cell-based models, including
ex-vivo patient-derived xenografts for assessment of tumor/immune cell
interactions in the tumor microenvironment; iPSC derived mini-brains for
assessment of neuronal health, and cell painting in 3D organoids.
* Deep, Single-Cell Analysis by Microscopy: Beyond Human Vision
Anne Carpenter, Broad Institute of Harvard and MIT
Microscopy images contain tremendous information about the state of cells,
tissues, and organisms. We aim to go beyond measuring individual phenotypes
that biologists already know are relevant to a particular disease. Instead,
in a strategy called image-based profiling, we stain many cellular components
and extract thousands of morphological features from each cell’s image, often
using an assay called Cell Painting. We then harvest similarities in these
“profiles” to identify, at a single-cell level, how diseases, drugs, and
genes affect cells, which can uncover small molecules’ mechanism of action,
discovering disease-associated phenotypes, identify the functional impact of
disease-associated alleles and identify novel therapeutics.
* Cell-Based Screening to Identify a Lead Humanised Antibody Drug Conjugate
Siobhan Leonard, LifeArc
Antibody-drug conjugates (ADCs) are being designed and used as highly
targeted cancer therapies, with five approved by the FDA and over sixty in
clinical trials. Building on the success of antibody therapies, ADCs enable
highly specific delivery of a toxic payload to a target tumor cell. LifeArc
has previous experience in the successful humanization of antibodies for
clinical use, Keytruda, Entyvio, Actemra and Tysabri. In order to build upon
this expertise and extend the therapeutic approaches, LifeArc has several ADC
programmes in the oncology and non-oncology space. As part of this portfolio,
the in-house capability has been established and several cell-based assays
have been developed to identify candidate ADCs. A case study will be
presented that outlines the screening process used to characterize the
capacity of candidate antibodies to bind, internalize and induce cell death
in HEK293 cells overexpressing the receptor of interest.
Critical to the success of an ADC program is the development of effective
methodologies to screen for candidate internalization to the lysosome, where
the linker will be cleaved to release the attached cytotoxin. To facilitate
high-throughput analysis of hybridoma supernatant and humanized variant
internalization, LifeArc has developed robust cell-based assays with the
IncuCyte S3 Live-Cell Analysis System and pH-sensitive dyes which fluoresce
in acidic lysosomes and endosomes. Following rapid evaluation with the
IncuCyte, deeper insight into the intracellular trafficking of promising
candidates was gained with the IN Cell Analyzer 6500 HS high content analysis
system. When coupled with intuitive analysis workflows to evaluate antibody
co-localisation with the lysosome, the sophisticated sensitivity of this
high-content imager has allowed further insight into the profile of promising
drug candidates and has facilitated the validation of this receptor as an ADC
target.
* Cell Painting in Hit Discovery
Charles-Hugues Lardeau, AstraZeneca
Having historically looked at characterizing our compound collection for
cytotoxicity and cytostaticity or performed the routine annotation of the
AstraZeneca compound collection with frequent hitters, we are looking into
alternative compound annotation solutions (e.g. imaging or transcriptomics
output) and the added benefits they may provide. The Cell Painting imaging
assay multiplexes six fluorescent stains to enable the visualization of up to
eight cellular compartments in U2OS cells. We will present how we have
established the Cell Painting imaging assay in 384-well plates and made it
compatible with our CoLab automation platform. The use of a centrifugal plate
washer afforded the reduction of staining solution needed and combined with a
microvalve-based microplate dispenser allowed the miniaturization of the
assay to 1536-well plates. Driven by sustainability, we have also explored
the use of a microplate cleaning system to wash and reuse plates for this
assay. Specific collections we have applied the Cell Painting imaging assay
include a set of compounds also tested with a metabolomics output, compounds
that are part of a phenotypic set or compounds from a nuisance compound set.
On the analysis side, we will share our experiences using a traditional
analysis pipeline (segmentation, working with ca. 1500 features) and the work
we are planning to do using deep learning models to best exploit images and
data generated. The latter part will touch on the work we have been doing to
segment compartments from images.
BIOCHEMICAL AND BIOPHYSICAL ASSAYS
Session Chair: Amy Quinn, Ph.D., GlaxoSmithKline (USA)
* Enzymology Framework and Assay Platform for Targeted Protein Degradation
Optimization
Stewart Fisher, C4 Therapeutics, Inc.
Targeted protein degradation, through the use of heterobifunctional degraders
that act as catalytic activators for an E3 ligase and target protein, has the
potential to transform drug discovery. This talk will discuss the key
structure: activity relationships that underpin degrader optimization,
including the interpretation and interplay of both thermodynamic and kinetic
elements that drive the catalytic turnover of targeted proteins. These data
will be placed in context with an enzymology framework to characterize
cellular degradation data the extension of these insights to pharmacodynamic
modeling and predictions.
* Mass Spectrometric Assay of METTL3/METTL14 Methyltransferase Activity
Shane Buker, Accent Therapeutics
A variety of covalent modifications of RNA have been identified and
demonstrated to affect RNA processing, stability and translation. Methylation
of adenosine at the N6 position (m6A) in mRNA is currently the most
well-studied RNA modification and is catalyzed by the RNA methyltransferase
complex METTL3/METTL14. Once generated, m6A can modulate mRNA splicing,
export, localization, degradation and translation. Although potent and
selective inhibitors exist for several members of the Type I
S-adenosylmethionine (SAM)-dependent methyltransferase family, no inhibitors
have been reported for METTL3/METTL14 to date. To facilitate drug discovery
efforts, a sensitive and robust mass spectrometry-based assay for
METTL3/METTL14 using self-assembled monolayer desorption/ionization (SAMDI)
technology has been developed. The assay uses an 11-nucleotide
single-stranded RNA compared to a previously reported 27-nucleotide
substrate. IC50 values of mechanism-based inhibitors S-adenosylhomocysteine
(SAH) and sinefungin (SFG) are comparable between the SAMDI and radiometric
assays that use the same substrate. This work demonstrates the SAMDI
technology is amenable to RNA substrates and can be used for high-throughput
screening and compound characterization for RNA modifying enzymes.
* Fragment-Based Target Screening - An Empirical Approach to Prioritising
Targets; A Case Study on Antibacterials
Peter Coombs, LifeArc
In the post-genomic era, abundant functional genomic data is being generated
and lists of potential new druggable targets are being analyzed across
industry and academia. Bioinformatics and literature diligence can take us so
far, but there are two key aspects to target selection that are best examined
empirically: tractability and ligandability. We have developed a
high-throughput fragment screening approach we call Fragment-Based Target
Screening (FBTS) to examine this.
The FBTS approach has been exemplified at LifeArc in its application to
antibacterials. New antibacterial drugs are urgently needed to tackle the
emerging crisis of multidrug-resistant infections. 50 potential targets were
selected by bioinformatic analysis from a TraDIS dataset of essential genes.
Our high-throughput expression and purification platform were used to test
the targets for expression. Biophysical techniques were used to QC 38
proteins and match them with a control ligand. Proteins were screened against
a library of 1280 fragments on a Biacore 8K, then hits confirmed in
dose-response experiments. Automated data processing and machine learning
were applied to assign a ligandability score to each target & prioritize hit
fragments for progression. This was combined with additional essentiality
data & a progression assessment to compile a priority list of targets to
advance into drug discovery projects.
FBTS is accessible; fragment libraries and the equipment needed for protein
production and fragment screening are not only in the domain of big pharma,
and the cost and effort associated less daunting than that typically
associated with other screening options such as HTS or DNA-encoded libraries.
In addition, the approach lends itself to take advantage of the wealth of
structural data from public databases and structural genomics consortia.
Combined with novel functional genomic data, our empirical tractability and
ligandability assessment allows high-quality targets to be prioritized for
prosecution and improved chances of success.
* Identification and Biophysical Characterization of STING Modulators
Charles Lesburg, MSD
The second messenger cyclic dinucleotide (CDN) cGAMP is produced by the cGAS
protein in response to activation by cytoplasmic dsDNA. Upon recognition of
cGAMP by the stimulator of interferon genes (STING) protein, STING undergoes
a substantial conformational change which leads to downstream upregulation of
proinflammatory cytokines. Modulation of the cGAS/STING pathway is therefore
considered a promising route for the treatment of inflammatory diseases as
well as a potential partner for immune-oncology therapies. This presentation
will describe the identification and optimization of compounds that were
found to antagonize STING signaling as well as the identification and
conformational characterization of non-CDN STING agonists. Techniques
employed include surface plasmon resonance and X-ray crystallography.
ADVANCED IN VITRO CELL CULTURE SYSTEMS
Session Chair: Virneliz Fernandez-Vega, B.S., Scripps Research (USA)
* Pancreatic Cancer Patient-Derived Organoids as a Tool for Personalized
Medicine
Herve Tiriac, University of California, San Diego
Pancreatic cancer is the most lethal common solid malignancy. Systemic
therapies are often ineffective and predictive biomarkers to guide treatment
are urgently needed. We generated a pancreatic cancer patient-derived
organoid (PDO) library that recapitulates the mutational spectrum and
transcriptional subtypes of primary pancreatic cancer. New driver oncogenes
were nominated and transcriptomic analyses revealed unique clusters. PDOs
exhibited heterogeneous responses to standard-of-care chemotherapeutics and
investigational agents. In a case study manner, we find that PDO therapeutic
profiles paralleled patient outcomes and that PDOs enable longitudinal
assessment of chemo-sensitivity and evaluation of synchronous metastases. We
derived organoid-based gene expression signatures of chemo-sensitivity that
predicted improved responses for many patients to chemotherapy in both the
adjuvant and advanced disease settings. Finally, we nominated alternative
treatment strategies for chemo-refractory PDOs using targeted agent
therapeutic profiling. We propose that combined molecular and therapeutic
profiling of PDOs may predict clinical response and enable prospective
therapeutic selection.
* Drug Combination and Gene Network Analysis in 3D models of Brain and Pancreas
Cancer towards Precision Medicine
Tim Spicer, Scripps Research
Molecular pathology approaches for clinical oncological care is routinely
performed on cancer patients with recurrent or metastatic disease. While
these “omic” diagnostics seemingly improved prognostication and prediction,
some molecular 'signatures' are not useful in clinical practice because of
their inability to independently validate treatment options. By nature,
associations between genomic profiles and clinical response are correlative
rather than mechanistic resulting in poor prediction for needed care.
Advances in our lab, in combination with our academic and industry partners,
has made possible in-vitro/ex-vivo 3 dimensional (3D) models of cancer
biology for use in a rapid, highly miniaturized, and cost-effective fashion
that permits direct drug response profiling to be generated in a phenotypic
manner that is patient specific. By integrating genomic diagnostics with drug
response testing a significant breakthrough toward advancing precision
medicine, using tumor biopsies, is now technologically possible and is
referred to as Precision Medicine Therapeutic Profiling. Glioblastomas and
cancer of the pancreas represent two of the most lethal malignancies with
survival typically less than two years from diagnosis. These models of
malignancy combined with genetic profiling have been tested in 3D cultures to
validate the best drug, or combination of drugs, for individualized care in a
time frame that is meaningful to clinical application. It is hypothesized
that the comprehensive data generated will afford physicians with a powerful
new insight that is actionable for patient care.
* New Innovation to Solve Unmet Needs: Implementing Human Induced Pluripotent
Stem Cell-Derived Neural Spheroids as a Robust Screening Platform for
Phenotypic-Based Central Nervous System Drug Discovery
Oivin Guicherit, StemoniX
The central nervous system (CNS)-based drug discovery has been hampered by a
lack of relevant, high-throughput experimental platforms. Complex,
three-dimensional (3D), experimental preparations with multiple cell types
better represent the native, in vivo biology, thus providing relevant
material for CNS investigations. Unfortunately, these preparations
traditionally have not been able to support the throughput necessary for
early-stage discovery programs. The ideal preparation would provide
consistent native tissue function in high throughput plates. To meet this
need, we have developed 96- and 384-well assay-ready, 3D neural spheroid
platforms; each spheroid is composed of cortical glutamatergic and GABA-ergic
neurons co-cultured with astrocytes to provide a more complex, biologically
relevant, and predictive preparation in a high throughput platform for
compound screening, safety evaluation, and toxicity studies.
Whole-genome RNAseq profiling demonstrated neural tissue expression patterns,
and high content imaging validated neuronal and astrocytic cell populations
while showing highly reproducible spheroid size across both 96 and 384-well
platforms. Functional neuronal activity was confirmed with MEA recordings and
visualized under high-throughput conditions as robust spontaneous,
synchronized calcium oscillations with consistent and reproducible baseline
activity patterns across wells and plates. Functional circuitry was confirmed
by challenging the system with specific ion channel and neurotransmitter
receptor agonists and antagonists.
To validate the capabilities of the platform for compound profiling and
discovery, a library of 1622 FDA approved compounds were screened in single
point at 10 µM final concentration examining Ca2+ oscillations as a
functional phenotypic readout. The library included drugs covering a wide
spectrum of targets such as CNS biology, oncology, cardiology,
anti-inflammatory, immunology, neuropsychiatry and analgesia with DMSO as a
vehicle control. Hits were identified as responses that were at least 3
standard deviations from DMSO control responses. As expected, the highest
number of hits were from targets associated with neuronal signaling
(serotonin, dopamine, GABA, and adrenergic receptors), neural biology, and
second messengers such as cAMP. Of note was the identification of several
compounds that led to increases in peak count similar to that of 4-AP, a
known pro-convulsant. The results validated a robust screening platform with
a vehicle control standard deviation of ~9% across all plates and a Z’ score
of 0.73 across the entire screen.
In conclusion, performing a high-throughput functional screening assay on our
human iPSC-derived 3D neural spheroid platform demonstrated the ability to
identify a wide range of hits spanning multiple target areas. This model may
serve as a phenotypic and target-based platform for overcoming traditional
hurdles of CNS-based drug discovery and improving outcomes for novel
CNS-targeted drug discovery and development efforts. Moreover, the model can
be created from both wild type and diseased individuals, providing relevant
human platforms for disease-specific drug discovery.
* Maximizing the Value of Cancer Drug Screening in Multicellular Tumor Spheroid
Cultures – Are You Analyzing Your 3D Tumor Models Appropriately?
Paul Johnston, University of Pittsburgh Dept. Pharmaceutical Sci.
Historically, cancer drug leads are identified in high-throughput screening
(HTS) growth inhibition assays performed in tumor cell line panels maintained
and assayed in 2-dimensional cultures. However, the overall probability for
success in oncology clinical trials is a dismal 3.4%. To improve clinical
development success rates for solid tumors, more physiologically relevant in
vitro 3-dimensional models are being deployed in lead generation to identify
better cancer drug candidates. Multicellular tumor spheroids (MCTSs) resemble
avascular tumor nodules, micro-metastases or the intervascular regions of
large solid tumors concerning morphology, volume growth kinetics, and form
diverse microenvironments due to gradients of nutrient distribution and
oxygen concentration. Head and neck cancers (HNC) are the 8th leading cause
of cancer worldwide and in 2019 it’s projected that 53,000 people in the USA
will develop oral cavity or pharynx cancer and 10,860 will die of these
cancers. Seven drugs are approved for HNC therapy, but only 10-25% of
patients respond to single-agent therapy, and 5-year survival and/or cure
rates have not improved. Although pembrolizumab (Keytruda®) was well
tolerated in patients with recurrent or metastatic HNC and produced
clinically relevant antitumor activity, only 16% of patients responded to
treatment. The low response rates and limited efficacy of HNC drugs
underscore the need to discover new and effective therapies. We have
developed methods to characterize HNC MCTS morphologies, viability and growth
phenotypes and to conduct cancer drug HTS. In a total of 95 pairwise cancer
drug x HNC cell line experiments, only 35.8% of MCTS cultures exhibited a
concentration-dependent growth inhibitory response using metabolic viability
reagents, and only 24.4% produced ≥50% reduction in Calcein AM live cell
staining. In contrast, 67.8% increased ethidium homodimer dead cell staining
by ≥50% and 89.5% altered ≥1 morphological feature; size, shape/perimeter or
density/compactness. These data demonstrate that multiple analysis methods
are required to accurately assess the impact of cancer drugs on HNC MCTS
cultures and to maximize the value of these physiologically relevant tumor
cultures.
DEVELOPMENT OF CELLULAR ASSAYS TO UNDERSTAND PROTEIN HOMEOSTASIS
Session Chair: Dane Mohl, Ph.D., Amgen (USA)
* Novel Strategies for Oncoprotein Degradation
Willem Den Besten, Amgen
Targeted protein degradation has the potential to open the door to
therapeutic targets previously deemed undruggable. In this talk, I will
present the characterization of two ligase ligands and show how target
degradation coupled with modulation of ligase biology leads to increased
cellular efficacy. I will also share results on a new method for inducing the
degradation of an ubiquitin ligase.
* Quantitative Live Cellular Assays for Screening Degradation Compounds and
their Mechanism of Action
Kristin Riching, Promega Corporation
A new generation of heterobifunctional small molecules, termed PROTACs, holds
significant therapeutic potential by inducing degradation of target proteins.
These compounds consist of two binding regions separated via a linker: one
that specifically binds to the target protein, and the other that directly
recruits E3 ligase machinery, resulting in ubiquitination and degradation of
the target. Characterizing PROTAC degradation efficacy represents a
significant challenge, both in terms of understanding the individual
mechanistic processes that control whether degradation will result, as well
as the ability to screen for target protein loss in high throughput fashion.
Here, we present a live-cell, luminescence-based technology platform that
enables characterization and screening of PROTAC compounds and their
mechanism of action using either ectopic or endogenous target expression
formats. We employ CRISPR/Cas9 endogenous tagging of target proteins with the
small peptide, HiBiT, which has a high affinity for and can complement the
LgBiT protein to produce NanoBiT luminescence. This allows for sensitive
detection of endogenous protein levels in living cells, and can also serve as
a BRET energy donor to study protein: protein or protein: small molecule
interactions. Using this combinatorial approach, we demonstrate the ability
to measure permeability effects and binding affinities of PROTAC compounds to
both target and E3 ligase, as well as monitor the kinetics of the subsequent
ternary complex (target:PROTAC: E3 ligase) formation, target ubiquitination
and recruitment to the proteasome in live cells. We further show the power of
this technology in extended kinetic monitoring of endogenous target protein
levels, quantification of key degradation parameters for rank-ordering,
correlation of these parameters to the precise MOA and the application of
these approaches for HTS. This comprehensive technology platform enables
rapid, simple and robust screening of functional degrader compounds,
ultimately aiding chemical design strategies for the optimization of new
therapeutic PROTACs.
* Cellular Assays Targeting Two Mutation Classes Causing Cystic Fibrosis:
Through (1) Protein Misfolding or (2) Premature Translational Termination
Feng Liang, Cystic Fibrosis Foundation
Cystic fibrosis (CF) is a disease caused by mutations in the gene coding for
the cystic fibrosis transmembrane conductance regulator (CFTR), a chloride
channel. Mutations are classified into six classes with phenotypes from no
CFTR protein synthesis to misfolding and/or functional defects.
Over the past seven years, the FDA approved several novel small molecules
that partially correct defects of different mutation classes of CFTR. This
has triggered broad efforts to find better and/or different small molecule
modulators that address even more CF disease-causing mutations. Here we
present screening assays for two classes of CFTR variants: (1) F508del
(causing protein misfolding and severely impaired cellular trafficking) and
(2) premature termination codon (PTC) mutations, resulting in stop codons in
the open reading frame of CFTR and no functional expression. Assays need to
address the primary defects of these specific mutation types. A differential
screening approach allows the discovery of class-specific hit molecules.
CFTR F508del leads to (1) misfolding of the nucleotide-binding domain 1
(NBD1) of CFTR and (2) perturbs normal interdomain interaction in the CFTR
protein. An efficient therapy needs to address both protein folding defects
for CFTR for the rescue of CFTR functional expression. Suppressing one defect
may allow identification of modulators of the 2nd defect. Thus, using
specific suppressor mutations (R555K to restore NBD1 folding or R1070W to
rescue domain-domain interactions, allelic screens were developed to enrich
for small molecules that preferentially modulate interdomain interactions or
NBD1 folding, respectively. The phenotypic screen relies on mammalian cells
expressing CFTR F508del with the suppressor mutations and a reporter gene
fused into an extracellular loop of CFTR. Hits from the two assays were
further tested for complementary effects on the trafficking rescue of CFTR
F508del.
A different class of CFTR mutations are PTC variants (about 170 reported)
that cannot be treated with available medicines. During CFTR protein
synthesis, the interaction of the ribosome with the PTC (UAA, UAG, or UGA)
terminates protein translation. Furthermore, when the ribosome stalls at a
PTC, translation-coupled RNA surveillance triggers the nonsense-mediated mRNA
decay (NMD) pathway, resulting in a reduction of CFTR mRNA levels. Therefore,
an effective therapy for CFTR PTC variants needs to address both premature
translation termination and reduced CFTR mRNA. Cell-based assays to assess
translational readthrough of PTCs have been developed based on either a
reporter or the native CFTR gene. RT-qPCR of CFTR mRNA is utilized to monitor
anti-NMD effects. Our data support the concept that combining readthrough
modulators and NMD inhibitors may lead to more effective therapy.
The CF phenotypes for the above two classes of CFTR mutations derive from
defects in different stages of CFTR biogenesis. Specific types of mutations
require different screens for the identification of mutation class-specific
disease modulators.
* Cellular Thermal Shift Assays in High-Throughput: A 1536-Well Cellular Target
Engagement Assay for Drug Discovery
Lorena Kallal, GlaxoSmithKline
Thermal shift assays (TSA) reveal changes in protein structure upon binding
to small molecules due to a resultant change in the thermal melting
temperature of the protein. Experimentally, this change in melt temperature
can be measured by exposure of the protein to a temperature gradient,
followed by quantification of the protein level or activity at each
temperature. Originally, protein thermal shift experiments were performed
with purified protein samples, but recently the TSA was reported in a
cellular context and the cellular thermal shift assay (CETSA) was born. We
have combined CETSA with a high-throughput protein detection method to
increase the throughput of the assay since traditional protein detection
methods such as western blots are low throughput. To develop high-throughput
1536-well CETSA, we used a protein reporter system in a homogeneous
(additions only, no wash) assay format. We have successfully utilized this
assay to characterize compounds in dose-response curves for drug discovery
programs at GSK. This method can also be applied to identify hits in high
throughput screening. Assay parameters optimized included target expression
level, the number of detection reagents added after thermal melting, plate
type and thermal melt methodologies. Uses and applications in drug discovery
will be presented.
APPLICATIONS OF CRISPR TECHNOLOGY IN DRUG DISCOVERY
Session Chair: Melissa Crisp, Ph.D., Eli Lilly (USA)
* Quantitating Endogenous Protein Dynamics with a Bioluminescent Peptide Tag
Marie Schwinn, Promega Corporation
There are an estimated 3,000 human genes that constitute the “druggable
genome.” However, only a small percentage of proteins coded by these genes
are the focus of drug discovery programs. One barrier in investigating these
understudied targets is the lack of easily implemented and scalable methods
for assaying proteins. The two principal techniques for analyzing proteins
are immuno-detection and mass spectrometry. They offer the advantage of
generating data from endogenously expressed proteins. However, these methods
are limited by the lack of protein-specific reagents, sensitivity, and HTS
compatibility. This prompted us to develop a workflow for studying endogenous
proteins that were both easy to use and scalable. In recent years, CRISPR
technology has been utilized to integrate reporters into host genomes, such
that cellular proteins can be monitored in real-time through detection of the
reporter fusion. CRISPR-mediated knockin of the HiBiT luminescent peptide
reporter has been demonstrated on a small-scale using a cloning-free
workflow. The high sensitivity and dynamic range associated with HiBiT make
it suitable to study most cellular proteins across a range of expression
levels. Thus, we wanted to determine if CRISPR-mediated HiBiT tagging would
provide an approach to rapidly tag any protein in the human proteome. To
explore this strategy, a diverse set of proteins representing a broad range
of functions and biophysical properties were targeted for tagging with the
HiBiT luminescent peptide tag. The majority of the selected targets showed
successful integration and expression of functional fusion protein. Given the
high success rate in this initial experiment, we investigated if this
strategy could be used for developing an HTS-compatible assay for an entire
protein family. For this purpose, the cyclin-dependent kinase (CDK) family
was targeted for HiBiT tagging and then used to quantitate CDK-specific
target engagement. Although the majority of edited CDK-HiBiT cell lines
displayed compound pharmacology similar to what was observed in
over-expression-based models, several differences were found which suggests
that endogenous models may provide more accurate information on compound
activity. In summary, CRISPR-mediated tagging of endogenous proteins with
HiBiT represents an easy and scalable strategy for studying endogenous
proteins which enables the analysis of proteins in their appropriate
physiological context.
* A 384-Well Workflow to Execute an Arrayed CRISPR-Cas9 Gene Editing Screen in
T-Cells
Sapna Desai, GlaxoSmithKline
Functional genomics approaches to identify novel therapeutic targets are
rapidly gaining traction. Arrayed screening for the phenotypes resulting from
gene-knockouts using CRISPR-Cas9 technology can yield results rapidly, with
very little need for target deconvolution. Data can be further enhanced by
the selection of disease-relevant primary cells.
We have developed a high-efficiency, arrayed genome-editing screen in primary
CD4+ T cells using CRISPR–Cas9 for the identification of genes associated
with cytokine release. T-cells are isolated, purified and expanded before
genome editing occurs via nucleofection. A 384-well nucleofector is used to
deliver RNP complexes consisting of guide RNA (gRNA), transactivating CRISPR
RNA (tracrRNA) and Cas9 enzyme. Edited cells are rested and activated before
being utilized in downstream assays capturing multi-cytokine release and cell
viability.
The development of miniaturized, robust nucleofection protocols and assays
for T-cell screening allows integration of this challenging cell-type onto
well-established liquid handling platforms and demonstrates the potential of
genome-wide arrayed CRISPR-Cas9 screening of primary cells in a screening
environment.
* Development and Implementation of High-Throughput Cellular Protein Stability
Assays for Evaluation of Target Engagement at Early Stages of Screening
Projects
John Holleran, Sanford Burnham Prebys Medical Discovery Institute
Cellular protein thermal stability provides a powerful method for assessing
compound target engagement. Recently, there have been several high-throughput
384 well assay compatible detection formats published for cellular protein
thermal stability using commercial luminescence complementation systems as
well as homogenous antibody sandwich AlphaLISA assays. Similarly, we have
utilized these detection formats and successfully developed and employed
high-throughput format assays for a large number of diverse drug discovery
projects ongoing at the SBP Prebys Center. In addition to serving the primary
goal of assessing the target engagement, these efforts have provided in-depth
knowledge of diverse detection systems, such as Promega HiBiT, DiscoveRx ePL,
AlphaLISA and the classical approach relying on SDS-PAGE-Western Blot
detection. In addition to monitoring the thermal stability of intracellular
proteins, we successfully employed these same detection approaches to assess
small-molecule effects on steady-state protein level or localization in the
cell. Not only do these approaches enable reporting on direct target binding,
but they also monitor the effects of small molecules on the protein target
interactome governing homeostasis. This enables the identification of
druggable partners from the entire target interaction network. Along with
small molecule screening, all these methods provide unique and powerful tools
to study targets of interest in their native state which exposes valuable
information about the effects of cellular background and extracellular
environment. From these studies, we have gleaned insight into the cellular
and context-specific target regulation and potential biological relevance of
identified hits. We have successfully utilized both exogenous expression and
CRISPR knock-in of detection tracers or AlphaLISA detection to assess protein
stability of endogenous proteins learning advantages and disadvantages of
each approach. Side-by-side assessment of these approaches helped to develop
a decision tree for selecting the most appropriate approach for each new
project and target.
* The Development and Application of a Whole Genome Arrayed CRISPR Screening
Platform for Target Discovery and Mechanism of Action Investigation
Douglas Ross-Thriepland, AstraZeneca
The identification of novel therapeutic targets that translate into clinical
successes is needed now more than ever to deliver life-changing medicines to
patients across disease areas; from drug resistance in oncology to
cardiovascular and respiratory disease. In this effort, the unbiased
identification of targets through perturbation at the gene level is not new.
However, the CRISPR/Cas9 revolution has enabled us to achieve this with
higher efficiency, reduced off-target effects and has enabled new modes of
perturbation such as gene activation (CRISPRa) and SNP mutation (base
editing). We have used this technology to build a Target Discovery platform
encompassing both pooled and arrayed screening techniques that, taken
together, allow us to probe a wide range of biology, from the slow onset of
drug resistance seen in oncology (pooled), through to understanding what role
genes play in signaling and cell response (arrayed). Here we present the
development and application of our Arrayed CRISPR Screening component of this
platform. Using CRISPR libraries comprised of synthetic gRNAs arrayed into a
“one-gene-per-well” format we demonstrate the high-efficiency of both genes
knock out (CRISPRn) and gene activation (CRISPRa) at whole genome-scale in
cell-based assays. Coupled with the generation of high-quality Cas9
expressing cells through the ObLiGaRe insertion of an inducible Cas9
expression cassettes (ODin), we show that CRISPR/Cas9 is a powerful and
robust technology for arrayed screening. By combining this platform with
high-content imaging and multivariate analysis technology we have been able
to interrogate the phenotype resulting from gene perturbation to a much
greater depth. This has significantly improved how we are able to rank,
triage and progress hits into target validation and into the clinic. Here we
demonstrate the application of this platform for the unbiased discovery of
new therapeutic targets with two case studies that exemplify the capability
and how it has impacted our new target pipeline in both oncology and advanced
drug delivery.
OPTIMIZATION OF ASSAYS FOR CHALLENGING TARGETS FOR LEAD DISCOVERY AND SCREENING
Session Chair: Julie Conkright-Fincham, Ph.D., Stowers Institute for Medical
Research (USA)
* Functional Proteome Array Screening Strategies for Biomarker Discovery
Joshua LaBaer, The Biodesign Institute, ASU
Self-assembling protein microarrays can be used to study protein-protein
interactions, protein-drug interactions, search for enzyme substrates and as
tools to search for disease biomarkers. In particular, recent experiments
have focused on using these protein microarrays to search for antibody
responses in patients with cancer, autoimmune and infectious diseases. This
approach has led to the first CLIA-certified blood test for the early
detection of breast cancer, Videssa™. Recent work has focused on using the
arrays to explore the post-translational modification of proteins and their
role in producing neoantigens in disease.
* NanoClick Assay: A High-Throughput, Target-Agnostic Cell Permeability Assay
that Combines NanoBRET Technology with Intracellular Click Chemistry
Andrea Peier, MSD
Macrocyclic peptides open new opportunities to target intracellular
protein-protein interactions (PPIs) that are often considered non-druggable
by traditional small molecules. Specifically, peptides have the potential to
bind to highly expansive binding surfaces (orthosteric blocking) of such PPIs
and/or other unique allosteric binding sites. However, their clinical
development may be limited by their ability to efficiently penetrate cells to
modulate their cognate PPI targets. The ability to have a predictive,
high-throughput assay to assess cell permeability is a critical tool to
support peptide drug discovery programs.
We developed a high throughput, quantitative, target-agnostic cell
permeability assay that essentially measures the cumulative cytosolic
exposure of a peptide in a concentration-dependent manner. The assay has been
named NanoClick as it combines in-cell Click chemistry and monitoring of a
NanoBRET signal in cells. The assay is based on cellular expression of the
NanoLuc-HaloTag system and relies on the Click reaction of azide-containing
peptides with DiBac-chloroalkane (CA) anchored to the HaloTag. The subsequent
introduction of an azido-dye followed by the NanoLuc substrate allows the
detection of a BRET signal that is reduced by the presence of Click-reactive
peptides in the cytosol. The readout can be expressed as a permeability ratio
of EC50s when compared to the response of a low permeability control.
We validated the assay using known cell-penetrating peptides and were further
able to demonstrate correlations to cellular activity using a p53/MDM2 model
system. The assay has been applied across multiple programs and has been used
to guide and establish structure-permeability relationships in the
optimization of macrocyclic peptides for cellular potency across
intracellular PPI target programs.
* Building Toolkits for the Orphan Kinome
Laurie Parker, University of Minnesota
Protein phosphorylation by kinases is a major mechanism of cell signaling and
is involved in almost all aspects of cell biology. Kinase dysregulation is a
key factor in diseases like cancer, and kinases are one of the major drug
targets in oncology. However, despite decades of research and billions of
dollars in drug discovery efforts on kinases, relatively few are well
characterized. The majority of the ~90 tyrosine kinases are considered
“orphans,” for which few to no substrates, and thus few details about
biological pathways and roles, are known. Without substrates to use as
activity probes, inhibitors for use as tool compounds or potential
therapeutics cannot be discovered. We have developed a strategy to
incorporate empirically-determined substrate profiling data into our
KINATEST-ID bioinformatics pipeline to efficiently tackle the orphan kinase
problem, determine substrate preferences and design novel substrate tools.
Protease-digested peptides from cell lysates are stripped of pre-existing
phosphates, then re-phosphorylated with a kinase of interest. The resulting
phosphopeptides are enriched and analyzed using mass spectrometry.
Phosphopeptide sequences are extracted from the peptide ID list and funneled
through the KINATEST-ID pipeline using a set of scripts implemented in the
open-source user interface GalaxyP, to define substrate sequence preferences
and propose candidate optimal substrate peptides. Those are then synthesized
and tested for phosphorylation efficiency by the target kinase. Using this
approach, we have characterized substrate preferences for several
understudied kinases for which few validated substrates were known, including
FLT3 and two clinically relevant mutants, and BTK. Current and future efforts
are to broaden the scope of kinases characterized using this streamlined
phosphoproteomics/bioinformatics pipeline and proceed with systematically
defining substrate information and developing novel tools for other orphaned
kinases in the kinome.
* Hybridization Chain Reaction for Single-Cell Visualization of RNA in
High-Content Imaging Assays
Gianluca Pegoraro, National Cancer Institute
The precise regulation of gene expression programs is responsible for the
establishment and maintenance of cell, tissue and organ identity, for
cellular responses to signaling cues and injuries, and, when disrupted or
rewired, for diseases such as cancer and inflammation. Measuring gene
expression in high-throughput assays often requires reporter cell line
engineering, or using antibodies against endogenous protein markers, which
involves a lengthy development process, and can also suffer from
batch-to-batch variation. On the other hand, single-molecule RNA Fluorescence
In Situ Hybridization (smRNA-FISH) detects endogenous transcripts, and is
based on DNA oligonucleotide probes that can be rapidly designed in silico,
chemically synthesized, tested, and scaled up. For these reasons, smRNA-FISH
has the potential to be a useful additional tool for High-Content Imaging
(HCI) in chemical or functional genetics screens for the identification of
gene expression regulatory pathways. However, visualization of RNA at the
single-cell level via smRNA-FISH has not been optimized for HCI assays. To
address these limitations, we adapted the single-step, enzyme-free RNA
Hybridization Chain Reaction (RNA HCR) to a 384-well format using an HCI
platform. First, we used RNA HCR probes against IFIT3, an
interferon-stimulated gene (ISG), to demonstrate that high-throughput RNA HCR
can quantitatively measure gene expression changes at the single-cell level
in a 384-well format. As a proof of principle, we performed a focused RNAi
screen against 521 human genes involved in epigenetics regulation to identify
novel factors mediating the transcriptional response to interferon-γ. The
results of this primary screen suggest that multiple components of the MOF
acetylase complex are involved in the upregulation of IFIT3 upon interferon
stimulation. Finally, we applied high-throughput RNA HCR in other HCI assays
to measure expression levels of specific mRNA splicing isoforms of the FGFR2
gene, to monitor the effect of steroid treatment on the expression of
inflammation regulators in primary human monocytes, and to determine the
effect of steroid treatment on a variety of GR-responsive genes in mouse
cells. Altogether, these results indicate that RNA HCR can be miniaturized in
384-well assays to semi-quantitatively detect several endogenous RNA species
via HCI in physiologically relevant systems, at the single-cell level, and in
a medium- to high-throughput format. In the future, we expect that
high-throughput RNA HCR will be useful for the discovery and validation of
diverse targets regulating gene expression.
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AUTOMATION AND HIGH-THROUGHPUT TECHNOLOGIES
TRACK CHAIR(S): SAM MICHAEL, NIH (USA) AND HELEN PLANT, B.SC., ASTRAZENECA (UK)
ADVANCED IMAGING TECHNOLOGIES TO BRIDGE THE GAP BETWEEN HIGH-CONTENT AND
HIGH-THROUGHPUT
Session Chair: James Pilling, M.Sc., AstraZeneca (UK)
* Revolutionizing Cellular Screening with Artificial Intelligence-Driven
Label-Free Imaging
Adam Corrigan, AstraZeneca
The primary reasons for drug failure in the clinic are a lack of efficacy and
safety. Therefore, to drive a better understanding of disease biology and
improve the translation, cellular imaging assays in early discovery need to
be increasingly complex, utilizing multiple biomarkers to label several
proteins in a pathway and to quantify multiple sub-populations.
The field of image analysis has been transformed by the explosion of machine
learning and AI methods, and we are now leveraging recent developments to
maximize the information we get from imaging data and enable new experimental
approaches. A key limitation of machine learning, and particularly deep
learning models is the requirement for large amounts of annotated training
data. We have developed an active learning framework for efficient training
data generation, alongside unsupervised phenotype discovery approaches, to
build models that can quantify the full complexity of cellular screening
data.
We are also integrating label-free phase-contrast imaging into our cellular
screens. A large amount of information on cellular morphology is contained in
the phase-contrast images, which do not take up a fluorescent color channel,
but the human interpretation is very difficult. By training a deep neural
network to find and segment nuclei and cells from phase-contrast images
alone, nuclear and cell markers are no longer required. This allows multiple
biomarkers to be combined into a single screen, enabling more complex biology
for less cost.
In addition to segmentation, we have shown that standard readouts such as
cell division and cell death can be predicted from the label-free images,
opening the possibility for digital multiplexing of a wide range of
biomarkers, in living cells, and without expensive cell engineering.
Combining this method with the high-content Cell Painting assay, we are
learning how to extract meaningful biological features from label-free
images, which can then be used to re-interrogate existing screening data for
new insights. This approach is straightforwardly integrated with existing
workflows and is revolutionizing the questions being asked through cellular
screening.
* Applications of Image-Based Artificial Intelligence in Drug Discovery and
Safety Testing
Mahnaz Maddah, Dana Solutions LLC
Discovering effective drugs and demonstrating their safety are significant
challenges facing the pharmaceutical industry, due to the high costs of
development, long lead times, and low success rates of late-stage clinical
trials. There is a need for new tools and technologies to help identify safe
and effective drugs during the early stages of development.
Over the last decade, there has been significant progress in using human
induced pluripotent stem cells (hiPSCs) for modeling of human disease, drug
screening, and toxicity testing. Numerous studies have demonstrated that
these cells have physiologically relevant characteristics and can be used for
preclinical testing of new drugs using high-throughput assays. In such
assays, image and signal analysis algorithms are used to generate
quantitative measurements that relate to cell degradation, death, or changes
in function. Such approaches may be missing subtle changes that are not
easily visualized, are too complex to measure with traditional data analysis
methods, and/or suffer from lack of consistent quality control metrics on the
input data.
Artificial intelligence (AI) techniques and specifically deep convolutional
neural networks are perfectly suited to address the challenges of these
high-throughput assays by analyzing large amounts of imaging data robustly
and with a level of sensitivity that has not been previously possible. We
present case studies for using AI for high-throughput image-based phenotypic
screening, toxicity testing, and quality control. First, we present data from
a drug discovery program for dilated cardiomyopathy using high-throughput
imaging of sarcomere structure in stem cell-derived cardiomyocytes. We were
able to build disease models with high accuracy, which were then deployed to
identify small molecules that showed to reverse the disease phenotype. The
identified small molecules were further validated with functional assays and
preclinical mouse studies. Second, we present data from a pilot toxicity
testing study using stem cell-derived cardiomyocytes. Our novel image-based
AI method was successful in capturing dose-dependent structural changes on a
panel of drugs with known cardiotoxicity profiles, while no change was
detected for the negative control. The detected structural changes correlated
strongly with contractility. Finally, we present data from a pilot quality
control study using current-trace signals from a patch-clamp instrument. We
successfully built an AI model that can accurately classify signals as good
versus poor quality, which enables automated and consistent filtering of data
during high-throughput experiments.
* Optical Pooled Screens in Human Cells
Avtar Singh, The Broad Institute
Pooled genetic screens have been critical for the systematic identification
of genes underlying cellular processes, but have thus far been limited to
phenotypes defined by cellular enrichment or comparatively low-throughput
single-cell molecular profiling. We have developed a method to make pooled
libraries compatible with the rich set of spatially and temporally resolved
phenotypes accessible to high-content microscopy by using targeted in situ
sequencing to demultiplex genetic perturbations. We applied this technology
to screen 952 genes for involvement in NF-κB signaling by imaging p65 nuclear
translocation and relaxation, recovering most canonical pathway members and
identifying novel candidate regulators of IL-1Β/TNFα-stimulated immune
responses. We are currently piloting applications with a range of optical
assays and cell models and expect that pooled optical screens will have broad
utility in identifying genetic components, analyzing genetic circuits, and
interrogating disease variants.
* High-Throughput Single-Cell Imaging and Advanced MachineLlearning Supported
Image Analysis of Primary Tumors Enables Anti-Cancer Therapy Development
Gregory Vladimer, Allcyte
The ability to perform high-content screening in a high-throughput fashion is
routinely limited to cell lines and other explant model systems, however,
there is a risk that these may not be fully representative of the in vivo
environment due to culture adaptation or the lack of multi-lineage cell
types. The ability to gather high-content data directly from primary samples,
however, both direct from blood and bone marrow, metastasized cancers and
dissociated solid tumor, without cell outgrowth or selection in a method
amenable to laboratory automation can be a more direct system. Further, by
combining imaging of these primary sample with an adaptable analysis
pipelines robust to micro-aggregates, especially formed in solid tumor biopsy
homogenates, vastly different cell shapes and sizes, and that can ultimately
harness the features from each cell can become a powerful means to study drug
response in a variety of indications using model systems directly derived
from the patient. This methodology has been used to prioritize therapy for
late-stage patients with hematological cancers in a basket trial (Snijder &
Vladimer et al 2017, Lancet Hematology), has been integrated with genetic
data to further uncover biological understanding and clinical synergy options
(Schmidl & Vladimer et al 2019, Nat Chem Bio). Here, this talk will
specifically focus on the details of the computational framework, including
supervised and unsupervised machine learning approaches for cell
identification and feature extraction, and other aspects of necessary
infrastructure including cloud-deployment that is used to, in very
high-throughput, quantify single-cell phenotypes form primary material from
cancer patients for drug discovery. Further, the use case of understanding
single-cell phenotypes after drug screening, both in single-cell suspensions
and in micro-aggregate multi-cell / 3D environments, will be highlighted.
SCREENING & PROFILING AT HIGHER THROUGHPUT USING PHYSIOLOGICALLY RELEVANT CELL
MODELS
Session Chair: Roger Clark, B.Sc., Charles River Laboratories (UK)
* A Systematic Medium-Scale Comparative Study of 2D Vs. 3D Models Using
High-Content Imaging Approaches
Thierry Dorval, Institut De Recherches Servier
The development of new pharmaceutical drugs is an expensive and high-risk
endeavor for the pharmaceutical industry. Major advances in physiologically
relevant in vitro cellular assays such as three-dimensional models, induced
pluripotent stem cells, organ-on-chip are expected to provide a better
ability to predict therapeutic response, hence, reducing clinical attrition.
Unlike high-throughput screening, high-content screening combines automated
fluorescence microscopy with quantitative image analysis allowing phenotypic
multiparametric readouts such as cell viability, DNA damage or mitochondria
structure among many others. This approach is particularly well suited for
complex or partially characterized targets. Moreover, in the oncology field,
it has been shown that compound efficacy could be dramatically modulated in
3D models.
In this context, we are aiming to perform a medium scale screening campaign
using a chemically diverse compounds collection on a cell line derived from
non-small cell lung cancer with a specific mutation both in 2D and 3D models.
Using high-content imaging approaches, a large set of parameters will be
extracted, leading to a better characterization of various toxicity
mechanisms of actions.
To provide robust comparable results between cellular models, a specific
subset of compounds was selected and screened in dose responses during the
assay development workflow. The analysis of this rich set of complex data
provided an opportunity to improve the rest of the screening campaign.
Hits obtained from both screens will be classified, compared and validated in
dose responses for a better understanding of the difference induced by the
use of a 3D model combined with high-content imaging. Ultimately this could
help assess the relevance of the 3D model in drug discovery in oncology.
* A Novel Multiplexed uHTS and uHCS (MuHTCS) Platform in a 1536-Well Format for
Chemical Biology Screening Using 3D Patient-Derived Cancer Organoids
Yuhong Du, Emory Chemical Biology Discovery Center
The current effort to grow human tissues as 3D “organoids” for cancer
research aims to recapitulate 3D architecture of tumors in an in vitro
environment for cancer biology studies and therapeutic development. However,
due to various technical challenges, primary 3D organoid culture has not been
widely used in a high-throughput screening (HTS) format for chemical
screening. Here, we report the miniaturization and development of a
multiplexed uHTS and uHCS (MuHTCS) organoid culturing platform for effective
compound screening in a 1536-well format. Using pancreatic patient
tumor-derived organoids as a model system, we optimized the 3D organoid
culturing conditions with extracellular matrix (ECM). The growth of organoids
was monitored by automated imaging. We further developed a multiplexed
screening platform to simultaneously monitor the effect of compounds on the
growth of organoids for ultraHTS (uHTS) and on the morphological change of
organoids for ultra-high-content screening (uHCS) in a 1536-well plate. The
MuHTCS assay has achieved Z’ > 0.5 and signal-to-background (S/B) > 6. A
pilot screening of ~2000 FDA approved and the bioactive compound libraries
have validated the assay for screening. Our data have demonstrated that it is
feasible to utilize miniaturized 3D cancer organoids for large scale compound
screening. The optimized MuHTC platform provides an efficient approach to
accelerate 3-D organoids-enabled screening for drug discovery.
* Acute Myeloid Leukemia Drug Sensitivity Testing Using Patient-Derived Cells
in 1536 Format
Lynn Rasmussen, Southern Research
In practice, the choice of which drug to prescribe for an individual patient
is often made without any information on how that individual will respond to
a specific drug. The field of precision medicine is attempting to provide
data to fill that information gap to match the patient with the most
effective treatment for that individual. To try to fill that gap for AML
patients we have developed a drug screening process using a panel of FDA
approved drugs with patient-derived leukemia cells. Because the
patient-derived cells are an extremely limited resource, a 1536-well assay
format was developed to maximize the amount of data that could be generated
for each patient. The process of developing this assay will be discussed,
including the technical challenges, their solutions and the equipment choices
used to achieve a reliable HTS format screening protocol.
* Automating a CRISPR based rescue screen for Alzheimer’s phenotypes in iPSC
derived neurons
Shushant Jain, Charles River
Alzheimer’s disease (AD) is a complex disorder with increasing prevalence and
socio-economic burden. However, the majority of strategies aimed at
identifying therapies for AD have been focused on targeting Abeta or TAU,
which make up the plaques and tangles respectively commonly found in people
with AD. The continued failure of the drug discovery process and the
accompanying trials against these targets have necessitated more and better
options for therapeutic intervention. Using multi-parametric high content
phenotypic readouts with neurons derived from human differentiated iPSCs with
familial AD mutations, we will perform CRISPR based rescue screen for the
various phenotypes associated with the mutations, such as endolysosomal
transport, synaptic dysfunction, neuronal toxicity. The multiple-phenotypic
rescue approach will enable the identification of novel key pathways and/or
targets that could serve as drug candidates for the treatment of AD.
AUTOMATING CHEMISTRY IN THE AGE OF AI
Session Chair: Alex Godfrey, Ph.D., National Center for Advancing Translational
Sciences (NCATS) (USA)
* Modern Automated Chemical Synthesis and Purification of Small Molecules
Gerard Rosse, Arrival Discovery LLC
Today, drug discovery remains a game of big numbers and many organizations
routinely investigate small molecules collection in the 200,000 to 2 million
compound range. Automation of chemical synthesis has gained a renewed
interest to produce novel compounds and to facilitate the challenging
multidimensional problem of compound optimization. This presentation will
describe the strategy and obstacles to implement a technology platform for
the production of 90,000 compounds per year in 13 mg quantity and >90%
purity. Custom designed robotic instruments, specialized laboratory
infrastructure, workflows, logistics and data management to enable high
throughput synthesis and purification will be discussed. The implementation
of core supercritical fluid chromatography (SFC) technologies provided a
unique opportunity to increase productivity and significantly reduce
operational costs. The presentation will conclude with an overview of the
integration of chemistry automation with advanced compounds management
systems.
* A Beginner’s Guide to the Practicalities of Automating Chemical Synthesis
Paul Harper, AstraZeneca
In late 2017 AstraZeneca undertook an internal “hack-a-thon”, bringing
together a diverse skill set to investigate our ambition of fully automated
chemical synthesis for drug-like compounds. Over the past 2 years, we have
evolved 4 prototypes to better understand the challenges associated with all
stages of a multi-step synthesis process. In this presentation, we will
review our most recent evolution, realizing fully automated batch and flow
chemistries to fuel automated synthesis. We will describe in detail the
integration and optimization of the Zinsser SOPHAS platform for batch
chemical synthesis; along with the varied Waters devices for product
purification and analysis.
To achieve seamless integration, we have selected a third-party process
scheduling software. Here we will cover the development of new drivers,
protocols and interfaces for chemistry system control, along with the unusual
demand of tracking and scheduling both single vial and associated plate-based
activities (and the interplay between the 2 formats).
Looking forward to our 5th iteration, we’ll discuss our plan for pre-cursor
storage, along with our concepts for how reactions could be constructed using
the Zinsser REDI platform.
* SynFini: An Automated Chemical Synthesis Platform
Nathan Collins, SRI Biosciences, SRI International
Exploration in organic chemistry is still inherently a manual process both in
conducting reactions in the lab and reporting results in the written
literature. Both are subject to the skill of the practitioner and the next
chemist who attempts to reproduce their reported results. In an effort to
improve the transferability and reproducibility of chemistry we have
developed an automation platform named SynFini that automates the design,
reaction screening and optimization (RSO), and production of target
molecules. SynFini includes three core components. A computational tool,
SynRoute, develops synthetic strategies for molecules of interest. Routes to
target molecules are built by combining knowledge of known chemistry from
reaction databases and new reactions predicted by machine learning. A high
throughput RSO platform, SynJet, (max. throughput reaction / s) enabled by
inkjet printing experimentally validates these strategies. Automated analysis
of the RSO outputs in the predicted route allows for the preparation of a
digital synthesis protocol that drives a benchtop multistep synthesizer,
AutoSyn. AutoSyn is capable of performing solution-based synthesis routes at
the milligram to gram scale. To assist medicinal chemists in drug discovery
programs, artificial intelligence (AI) can be included to aid in the design,
selection, and prioritization of compounds with desired properties, such as
biological activity and ADMET properties, and can be interfaced with SynFini
automated synthesis and testing for rapid turnaround. Examples of how each
tool works independently and then how they fit together into a seamless
automated solution for design, synthesis and testing of a variety of
molecules are presented. How such automated processes are digitally captured
and electronically transferrable for ultimate reproducibility are discussed.
* A Decade and Journey of Lilly’s Discovery Automated Synthesis
James Beck, Eli Lilly
Lilly actively engages Automated Synthesis in it's Medicinal Chemistry
portfolio of projects. This brief talk introduces the journey Lilly has been
on with the Automated Synthesis Lab (ASL - Indianapolis) and now with the
closed-loop and integrated automation capabilities residing within the Lilly
Life Sciences Studio (L2S2 - San Diego). Along the way, Automated Synthesis
has provided a foundation for other Lilly initiatives including the Proximal
Lilly Collection (PLC, published), Idea-to-Data (ItoD, published) and
ChemoPrint (in press).
SCREENING AUTOMATION: MODULAR VS. HIGHLY INTEGRATED SYSTEMS
Session Chair: Helen Plant, B.Sc., AstraZeneca (UK)
* Enabling Nontraditional Screeners from a Centralized uHTS Core
Mitchell Hull, Calibr at Scripps Research
Large, ultra-high-throughput screening systems can lead to an overreliance on
simple assays and deny screening access to those with lower throughput needs.
There is a temptation to forego slower, complex assays in favor of ones more
amenable to HTS and to pursue familiar target families that “plug-in” to know
platforms. HTS facilities, sometimes siloed within a department, are often
unavailable even to those working in an HTS capable organization. As a
result, some organizations have turned to multiple smaller systems designed
for small-scale screening. However, data and compound management issues arise
in this decentralized approach. Compound spotted assay plates, created by
acoustic compound transfer platforms, can mitigate these issues. However,
even combined, these cannot match the capabilities of a larger system when a
larger campaign is needed. We have set up a hybrid uHTS/modular acoustic
transfer platform that can act as one integrated system or three modular
systems. Combining this with a high-value chemical library and an active
pursuit of partners with high-value bioassays, we have pursued an approach to
enable high-value, low-throughput assays, while maintaining uHTS capability
and centralized compound and data management.
* A B Cell Antibody Discovery Platform Using an ‘Islands of Automation’
Approach
Paul Anderson, Eli Lilly and Company
In recent years Lilly has implemented a Next-Generation Research (NGR)
initiative to improve the value output of the R&D portfolio. One of the NGR
pillars focuses on decreasing the timeline to bring medicines to patients. As
part of this initiative, Lilly has invested in an ‘Islands of Automation’
approach to advance the B cell antibody discovery platform at the Lilly
Biotechnology Center in San Diego to significantly increase throughput and
reduce project timelines. This talk will focus on the automated systems that
have been developed as part of this platform beginning with B cells sorted
into microtiter plates through binding and functional assays run in
dose-response plates from recombinantly expressed material. Examples of
alternative instruments to traditional methods and software solutions to
eliminate inefficiencies will be shared. This highly automated approach to
antibody discovery has allowed us to meet aggressive timelines and
dramatically increase throughput while allowing flexibility for future
changes to our process.
* Innovative Tube and Dispensing Technologies Enable Fully Acoustic Workflows
for Drug Discovery Assays
Silvio Di Castro, Sample Management / Discovery Sciences / AstraZeneca
Innovative design and deployment of novel labware, instrumentation and
software technologies have delivered an automated, fully acoustic platform
and a step-change in small molecule Sample Management (SM) processes.
For many years, conventional SM workflows have included multiple sample
transfers between vessels, using a hybrid of contact and non-contact
dispensing, which are cumulatively wasteful. These combine to affect
excessive sample consumption, necessitating chemists to synthesize
superfluous quantities of the compound.
Here we show high-quality concordant datasets from the first fully acoustic
workflow for physicochemical, enzymatic, cellular and in vitro ADME assays.
We also show a reduction in (i) sample usage in these assays, (ii) DMSO usage
throughout the process, and (iii) future synthesis requirements.
An acoustically compatible storage tube (FluidX™ AcoustiX™ Sample Tubes,
Brooks Life Sciences, UK) was designed with optimum geometry for dispensing
accuracy and speed, whilst maintaining a working sample volume able to
sustain a 10-year screening lifetime. Co-molded capping technology for these
tubes has resulted in increased durability for multiple dispense access and
sample longevity, whilst a novel split barcode at the base affords a central
opening for transmission of the acoustic pulse.
A tube-compatible acoustic liquid handler (Echo® 655T Liquid Handler, Beckman
Coulter Life Sciences, USA) has been designed to utilize acoustically
compatible storage tubes including a faster drop-transfer rate via a new
transducer-focussing mechanism. A new dryer system removes moisture on the
exterior of the tube, alongside local humidity control in the drop-transfer
zone to maintain sample integrity.
The development of a new, fully acoustic workflow has minimized sample
handling and waste, enabling miniaturization of assays and hence reducing the
amounts of sample required for synthesis to support drug discovery projects.
We have implemented and validated novel labware and instruments for a
transformative and sustainable solution to many drug discovery issues
applicable across the industry.
* Highly Integrated Modular Systems – Mobile Robots Unlock the Best of Both
Architectures
David Dambman, Biosero, Inc
Choosing the right system architecture for your automation can be
challenging. Large, highly integrated systems provide advantages in terms of
throughput and operation simplicity, but the system itself becomes a single
point of failure and it can be difficult to maintain up-time as well as
evolve the system as applications and technologies change. Modular systems
provide greater flexibility, are easier to scale and adapt to changing needs,
but require more human effort to operate. It can also be challenging to
integrate the data from disparate modules and manage efficient utilization
across the full workflow.
Fortunately, advances in mobile robot AGV (Autonomous Ground Vehicle)
technology, coupled with new scheduling and data management architectures can
bridge the gap. These provide the means to fully integrate modular, manual or
robotic workcells by scheduling and executing operations with the additional
capability to transport consumables, samples, and reagents between modules.
This enables a truly connected and fully automated lab while still
maintaining the advantages of standalone walk-up operations that has the
flexibility to evolve as your needs change.
1536 AND BEYOND: HT MINIATURIZATION WHILE MAINTAINING PHYSIOLOGICAL RELEVANCE
Session Chair: Mindy Davis, Ph.D., National Institute of Allergy and Infectious
Diseases (NIAID) (USA)
* Continued Development of High-Throughput MS and Applications for Cell
Analysis
Jonathan Wingfield, AstraZeneca
Over recent years, AstraZeneca has worked to develop a high-throughput mass
spectrometry platform that utilizes the speed and contactless nature of
acoustics as a sample introduction technology. Fully automated acoustic mist
ionization mass spectrometry platforms are now routinely used to support
biochemical HTS campaigns, to date over 10 million samples have been
successfully screened against more than 10 different enzyme targets using
this technology.
Having established a primary role for AMI-MS we are now looking to expand the
application space where the technology could add value to early drug
discovery. We have recently started to evaluate the impact of AMI-MS for
metabolomic analysis of cell lysates, primarily within the early toxicology
screening area.
In December 2018, AstraZeneca and collaborators at several Swedish academic
institutions and SME’s were awarded a phase 2 grant from Sweden’s Innovation
Agency, Vinnova. The collaboration aims to develop technologies and workflows
to enable primary patient-derived disease cells to be utilized in the early
phase of drug discovery.
This presentation will focus on the continued development of AMI-MS within AZ
and how we are applying high-throughput mass spectrometry to enable clinical
samples to be assessed in the early phases of drug discovery.
* Array and Microfluidic-Based Cellular Assays Miniaturized Beyond the 1536
Well Plate
Jeffrey Gross
Small molecule high throughput screening (HTS) in drug discovery
traditionally involves microtiter plate screening in 384- and 1536- well
formats. While these methods are miniaturized compared to Petri dishes or
flasks, reagent and labor costs are still significant factors in high
throughput screening campaigns. Here we present the development of cellular
assays utilizing ultra miniaturized array-based and microfluidic devices. The
experiments were aimed at reducing cellular assay volumes from uL to nL
volumes. Challenges included maintaining environmental controls for cell
health and handling small volumes for cells and compounds. Novel approaches
in equipment, device design, and automation were required. Data suggest that
cell health, cell morphology, and pharmacological responses to drugs were
similar in nL volumes compared to those observed in 50 uL volumes in 384 well
plates. The development of processes and automation to industrialize new
devices will ultimately enable these technologies to be applied broadly in
drug discovery. Cost savings in cell and reagent usage and the ability to use
disease-relevant cell systems are paths toward reduced attrition in drug
discovery.
* Approaches that Enable Large-Scale Chemical Biology Interrogations
Fred King, GNF Systems
During SLAS (Lab Automation) 2009 we presented a low cost,
automation-friendly, screening platform that used reporter gene assays
(RGA’s) to delineate the interaction of small molecules with canonical
mammalian signal transduction pathways. Our experience with this approach
over the last decade has demonstrated its broad utility in the support of
phenotypic screening, ranging from generating mechanism of action hypotheses
for individual compounds to characterizing compound libraries. Furthermore,
this RGA panel inspired and guided the development of additional platforms
that are more comprehensive and flexible in terms of both cell types under
investigation and the scope of biological activity detected. This
presentation will focus on several of these new technologies, which all
leverage Next Generation Sequencing technologies to measure RNA expression
levels in a multiplexed fashion. The suite of approaches provides users with
the ability to balance sequencing depth, transcriptome coverage and cost per
well in their assay design. Coupled with internally designed automation
platforms these systems allow expression levels of thousands of genes to be
monitored in every well of an HTS-sized screen.
* Identification of Chemical Compounds Inhibiting Zika Virus Replication
Through a Large-Scale High-Content Screening Approach
Laura Riva, Sanford Burnham Prebys Medical Discovery
Zika virus (ZIKV) is a human mosquito-borne positive-sense RNA virus,
belonging to the Flaviviridae family. World Health Organization (WHO)
classified this virus as an Emergency in 2016 and currently identifies Zika
as a priority disease. Although symptoms are generally mild, a risk of
neurologic complications including Guillain Barré Syndrome is associated with
the infection in adults, while infection during pregnancy is responsible for
microcephaly and other congenital malformations. Since no vaccine or
commercialized antiviral targeting this virus are available, scientific
efforts are currently focusing on the development of treatments allowing to
efficiently limit ZIKV spread. Prompted by this unmet medical need, we
conducted a screen of 51,520 small chemical compounds using a high-content
imaging cell-based assay, monitoring Zika virus replication within Huh-7.5
cells by combining DAPI staining of cellular nuclei together with
immunostaining of the Zika virus envelope protein. 99 candidates were
identified and validated as inhibiting ZIKV replication of at least 50% at a
concentration of 10 µM. Subsequent dose-response studies were performed to
evaluate the effects of each compound on both virus replication and
cytotoxicity and compounds showing a strong dose-response inhibitory effect
on replication with weak cell toxicity were then selected for follow-up
studies. Two compounds sharing a common structure presented a particularly
promising antiviral activity with a selectivity index, calculated as the
ratio of 50 % inhibitory (IC50) and 50 % viability (CC50) concentrations,
greater than 30. This common chemical scaffold showed to specifically inhibit
ZIKV, displaying an antiviral activity against several strains of both
African and Asian lineages but no effect on other Flaviviruses tested. Its
antiviral activity was confirmed with similar efficacy in more relevant
models for ZIKV infection, including human monocyte-derived dendritic cells
(hMDDCs), human neural progenitor cells (hNPC) and the placenta-derived
choriocarcinoma cell line JEG-3. Time of addition kinetics as well as
specific entry and replication assays excluded an inhibitory role during ZIKV
entry, highlighting an antiviral role during the RNA replication step. This
observation, in addition to the appearance of resistant mutant viruses upon
selection in the presence of the drug, strongly suggested a non-structural
protein of the virus as a target of the compound. Current efforts are ongoing
to identify the specific viral target of the compound and to get more
insights about its mechanism of action. In addition, Pharmacokinetics (PK)
and in vivo efficacy studies will be performed in the near future to evaluate
the therapeutic potential of this compound. In summary, taking advantage of a
cell-based large-scale high-content screening approach to identify small
chemical compounds showing antiviral activity against ZIKV, we identified a
chemical scaffold specifically targeting this Flavivirus, inhibiting its RNA
replication step.
OPEN SOURCE AUTOMATION
Session Chair: Sam Michael, National Center for Advancing Translational Sciences
(NCATS) (USA)
* Improving Daily Operation of a Fully-Automated uHTS System
Steven van Helden, Pivot Park Screening Centre
Pivot Park Screening Centre (PPSC) is a small company that specializes in
ultra-high-throughput screening (uHTS) for drug discovery. We perform about
25 full deck screening campaigns a year on our own library of 300.000
compounds, the European Lead Factory library of 550.000 compounds and client
libraries up to 1.000.000 compounds. In order to support this huge
production, we have implemented efficient processes on a fully automated
screening system consisting of 3 robot pods integrated with a wide variety of
instruments.
Even in a highly automated environment like our uHTS lab, there is a
continuous need for tools and little tricks to support our daily work. These
include software tools to run active picking from the online store, re-use of
(washed) verification plates, a simple tool for drying compound plates,
implementation of a weighing station in the robot for checking dispensing
performance, etc. Also, we have implemented cleaning stations for our heavily
used certus dispensers. Finally, we make extensive use of a 3D-printer to
create all sorts of tools in the lab and to save costs by printing parts of
instruments that need repair. This presentation will provide insight into the
daily operations in a uHTS lab.
* Leveraging Open Source Electronics for Rapid Development of Custom Laboratory
Devices
Pierre Baillargeon, Scripps Research
The Lead Identification team at Scripps Florida routinely leverages open
source technologies to meet operational challenges and to provide custom
engineering tools for lab use. Most recently, these tools include the
development of a micro solenoid dispensing QC platform built around the Lee
Company VHS series valve. This system was developed to address the unmet need
of dispensing of 3D models such as spheroids and to assist with general QC of
valves used in ongoing HTS efforts. This QC platform allows users to
characterize & optimize the performance of VHS valves under a variety of
conditions.
This reconfigurable QC platform is built on an optical breadboard and is
comprised of three main subsystems: electronics, optical train and motion
control. The electronics subsystem allows users to easily control VHS series
valve behavior using an Arduino microcontroller through a custom in-house
designed Arduino shield. The optical train consists of an off the shelf USB
camera combined with an in-house designed open-source illumination panel that
allows imaging of individual droplets via the stroboscopic effect. An
open-source X/Y motion control system further increases the utility of the
platform by allowing automated dispensing into microplates. User control of
the QC platform is provided via a custom web-based interface that
communicates directly with the microcontroller and allows users to easily
specify microplate dispense patterns by interacting with graphic
representations of microplate wells.
Also presented is the development of a custom Arduino-based syringe pump
system intended for use alongside the Lee valve QC platform. This syringe
pump system utilizes a Tecan Cavro pump and allows for real-time adjustment
of pump parameters during mixing and dispensing operations which are critical
for mixing and homogeneous distribution of the spheroids. The development of
these platforms, lessons learned and results of initial testing are
presented.
* Intelligent Microscopes Using Open-Source Hardware for High-Throughput
Laboratory Automation
Pavan Chandra Konda, Duke University
Traditional microscopes used for automated imaging and analysis sets one
aback with tens of thousands if not hundreds of thousands of dollars. This
limits the number of microscopes a lab can afford, hence limiting the number
of parallel experiments that can be performed. We present a novel approach by
combining low-cost, low-resolution microscopes with advanced computational
imaging methods that can extract high-resolution image information in the
post-processing. In addition, we implement novel machine learning methods to
jointly optimize the automation task, e.g. cell segmentation, and the data
acquisition process, e.g. illumination pattern, to capture fewer data without
losing the performance of the automated task.
Our initial prototype costing ~$150 employed a Raspberry Pi as the computer
and a modified Raspberry Pi V2 camera as the low-resolution microscope. A
low-cost 16x16 LED array developed for display is used to illuminate the
sample and 3D printed parts are used for assembly. LEDs in the array are
sequentially illuminated to capture 256 low-resolution images, where the
high-resolution information is encoded within these low-resolution images
using the aperture synthesis concepts. The captured 256 low-resolution images
were combined to achieve 0.8µm resolution, for the first time in a low-cost
setting, across 4 mm2 field-of-view. The phase of the object is also
recovered in the process, making this suitable for imaging cell cultures
without any need of staining. In the latest developments, we implemented a
new machine learning model to multiplex the illumination to reduce the number
of images captured to two, without any loss in performance for tasks such as
cell segmentation or detecting malaria infection. This also reduces the image
processing time and, exploiting the increasing computing performance on
opensource hardware such as Raspberry Pi and Google’s Coral Edge TPU, we are
currently working towards achieving real-time machine learning-based
automation on our portable low-cost setup.
The 3D printed design of our microscope can be easily modified to the
specific requirements of a lab, e.g. imaging stress fiber reorientation in
cells under mechanical stimuli requires a different setup compared to imaging
cell confluency in a petri-dish. Our optics and algorithms still stay valid
for all these different configurations and the required modifications in the
3D printed designs are usually minor. This is not possible with commercial
systems that are designed for a limited number of imaging applications.
Combining the latest developments in machine learning makes our approach a
powerful tool for laboratory automation and diagnostics in low-resource
settings.
* Beyond High-Content Screening: An Open Next Generation Image Analysis
Platform
Peter Bajcsy, NIST National Institute of Standards and Technology
There is an increasing interest in discoveries from images acquired by
high-throughput and high content microscopy imaging of multi-well plates with
biological specimens under a variety of conditions. As multi-dimensional
automated imaging increases its throughput to thousands of images per hour,
the computational infrastructure for handling the images has become a major
bottleneck. The bottleneck associated challenges arise due to big image data,
complex phenomena to model, non-trivial computational scalability that
leverages the advanced hardware and cutting-edge algorithms, and incompatible
software tools that vary in the language they were written in, the platform
they were written for and capabilities they were designed to execute.
To address the above challenges, groups have developed software solutions
based on client-server systems with modern web technologies on the
client-side and a spectrum of databases, computational workflow engines, and
communication protocols on the server-side to hide the infrastructure
complexity. However, these solutions have not focused on the interoperability
of imaging specific computational plugins and visual exploratory capabilities
of such plugins over very large image collections.
To address these inter-operability and visual exploration challenges, the
National Institute of Standards and Technology (NIST) and the National
Institutes of Health (NIH) - National Center for Advancing Translational
Science (NCATS) have formed a close collaboration to develop an open-source
platform for executing web-based image processing pipelines over very large
image collections with interoperable plugins. The plugins developed by both
institutes are based on software containers as standardized units for
server-side deployment, as well as on dynamically created web user interfaces
(UI) to enter parameters needed for the software execution and for advanced
visual data explorations on the client-side. Each container packages code,
with all its dependencies, and has an entry point for running the computation
in any computing environment. Each UI description file contains metadata
about the plugin-container and the computation parameters.
We will demonstrate the utility of the platform with algorithmic plugins by
analyzing 1536 well plates with three spectral channels and multiple fields
of views (FOVs) per well for drug dose-response across an array of features.
Typical visual data exploration is assisted by algorithmic tools for quality
control, stitching of FOVs per well, segmentation, characterization of
regions of interest, and scalable visualization using Deep Zoom, a toolkit
for browser viewing of gigapixel 2D images. The data explorations are
interactive either in a Deep Zoom viewer or in a Jupyter notebook while
prototyping pipelines. More demanding computations are supported via batch
processing and deep learning-based pipelines are designed for GPU execution.
With the NIST and NIH NCATS combined efforts, researchers are enabled to
discover quantitative insights from their imaging data and reuse
computational tools developed by anyone following the web computational
plugin conventions.
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BIOLOGICS DISCOVERY
Track Chairs: Rob Howes, Ph.D., AstraZeneca (UK) and Janice Reichert, Ph.D., The
Antibody Society (USA)
ANTIBODY THERAPEUTICS DISCOVERY: FOCUS ON BISPECIFICS AND IMMUNE CHECKPOINT
MODULATORS
Session Chair: Janice Reichert, Ph.D., The Antibody Society/mAbs (USA)
* Creating a Novel T-cell Engaging Bispecific Antibody Platform: Fine-Tuning
Anti-Tumor Activity with Sequence-Based Discovery and Machine Learning
Katherine Harris, Teneobio
Using a unique sequence-based discovery approach along with proprietary
transgenic rats, we have created a large collection of fully human anti-CD3
antibodies with diverse T-cell agonist activities. Our novel discovery
platform combines antibody repertoire deep sequencing, high-throughput gene
assembly, and recombinant expression. Our approach generates a large
diversity of sequence-defined antibodies that we characterized in
high-throughput T-cell agonist assays. Using machine learning tools, we were
able to rapidly establish sequence-activity relationships and identify key
residues and variable region positions in the antibody repertoire that had
desired agonist behavior. The CD3 antibodies identified by our platform show
diverse in vitro T-cell activation profiles measured by CD69 upregulation,
IL2, and IFNg production. We also generated human domain antibodies targeting
a variety of tumor antigens that we combined with our unique CD3 antibodies
to create bispecific molecules that mediate redirected T-cell killing of
tumor cells. In one particular example, we have created a panel of aCD3:aBCMA
bispecific antibodies for the treatment of multiple myeloma that stimulate
different levels of T-cell activity. Using a multiple myeloma tumor cell line
along with primary human PBMCs, we demonstrate a spectrum of in vitro tumor
cell killing activity with varying levels of cytokine release using our
bispecific molecules with diverse CD3 binding activities. In summary, we have
created a T-cell engaging bispecific antibody platform with tuned T-cell
agonism that can be used to optimize the therapeutic index for a variety of
tumor antigens.
* Benefits of Chicken-Derived Antibodies for Combination Immunotherapy
Torben Gjetting, Symphogen
The development of novel antibodies and more powerful therapeutic
combinations for immunotherapy is an intense area of focus. However, for
difficult and/or conserved targets, finding antibodies with unique
functionality, and generating early proof of concept pose challenges to the
development of novel antibody therapeutics. Symphogen’s approach to discovery
and development of potent antibody combinations for cancer immunotherapy
using different species, including chicken, will be presented. Examples from
our clinical pipeline will be shown.
* Quantitative High-Throughput Screening Assays for the Discovery and
Development of SIRPα-CD47 Interaction Inhibitors
Thomas Miller, Institut Paoli Calmettes
CD47 is an immune checkpoint molecule that downregulates key aspects of both
the innate and adaptive anti-tumor immune response via its counter receptor
SIRPα, and it is expressed at high levels in a wide variety of tumor types.
This has led to the development of biologics that inhibit SIRPα engagement
including humanized CD47 antibodies and a soluble SIRPα decoy receptor that
are currently undergoing clinical trials. Unfortunately, toxicological
issues, including anemia related to on-target mechanisms, are barriers to
their clinical advancement. Another potential issue with large biologics that
bind CD47 is the perturbation of CD47 signaling through its high-affinity
interaction with the matricellular protein thrombospondin-1 (TSP-1). One
approach to avoid these shortcomings is to identify and develop small
molecule molecular probes and pretherapeutic agents that would (1)
selectively target SIRPα or TSP-1 interactions with CD47, (2) provide a route
to optimize pharmacokinetics, reduce on-target toxicity and maximize tissue
penetration, and (3) provide for more flexible routes of administration. As
the first step toward this goal, we report the development of an automated
quantitative high throughput screening (qHTS) assay platform capable of
screening large diverse drug-like chemical libraries to discover novel small
molecules that inhibit CD47-SIRPα interaction. Using time-resolved
fluorescent resonance energy transfer (TR-FRET) and bead-based luminescent
oxygen channeling assay formats (AlphaScreen), we developed biochemical
assays, optimized their performance, and individually tested them in
small-molecule library screening. Based on performance and low false-positive
rate, the LANCE TR-FRET assay was employed in a ~90,000 compound library
qHTS, while the AlphaScreen oxygen channeling assay served as a
cross-validation orthogonal assay for follow-up characterization. With this
multi-assay strategy, we successfully eliminated compounds that interfered
with the assays and identified five compounds that inhibit the CD47-SIRPα
interaction; these compounds will be further characterized and later
disclosed. Importantly, our results validate the large library qHTS for
antagonists of CD47-SIRPα interaction and suggest broad applicability of this
approach to screen chemical libraries for other protein-protein interaction
modulators.
* Discovery of High-Affinity, Pan-Allelic, and Pan-Mammalian Reactive
Antibodies Against the Myeloid Checkpoint Receptor SIRPα
Janet Sim, ALX Oncology
Targeting the CD47-signal-regulatory protein α (SIRPα) pathway represents a
novel therapeutic approach to enhance anti-cancer immunity by promoting both
innate and adaptive immune responses. Ongoing clinical trials to inhibit this
pathway by targeting CD47 has shown promising results in reducing tumor
burden (Chow et al., ASCO 2019). Unlike CD47 which is expressed ubiquitously,
SIRPα expression is mainly restricted to myeloid cells and neurons.
Therefore, compared to CD47-targeted therapies, targeting SIRPα may result in
differential safety and efficacy profiles, potentially enabling lower
effective doses and improved pharmacokinetics and pharmacodynamics. In this
talk, we will present our strategies of using wildtype/human antibody
transgenic chickens for immunization and describe our screening approaches to
identify SIRPα antibodies suitable for clinical translation. A total of 200
antibodies were isolated and approximately 70 antibodies with diverse SIRPα
binding profiles, sequence families, and epitopes were characterized. A
subset of antibodies was shown to bind both human SIRPα v1 and v2 alleles
with high affinity (nM-pM), potently antagonize the CD47/SIRPα interaction
and potentiate antibody-dependent cellular phagocytosis in vitro. The
anti-SIRPα antibodies also enhanced anti-tumor activity in both xenograft and
syngeneic tumor models and were well tolerated in cynomolgus monkeys with
favorable PK and extended receptor occupancy. These properties provide an
attractive rationale to advance the development of these anti-SIRPα
antibodies as a novel therapy for advanced malignancies.
CELL THERAPIES FOR CANCER: CAR-TS IN DEVELOPMENT
Session Chair: David Gilham, Ph.D., Celyad (BEL)
* Generation of a Controllable CAR T Cell Therapy
Travis Young, Calibr, a Division of Scripps Research
T cell-based therapies, including T cell engaging bispecific antibodies, and
genetically engineered chimeric antigen receptor engineered T cells (CAR-T
cells) have produced remarkable results in clinical trials – achieving
complete remissions in patients with hematological malignancies who failed
multiple lines of prior therapy. Towards increasing the potency and safety of
these therapeutics, as well as expanding them to cancers outside of the
hematological space, we have defined how the biophysical characteristics of
the antibody-based components of these therapies modulate the physiological
response of the T cells that carry out the anti-tumor activity. For example,
we have designed a “switchable” CAR-T cell system using antibody-based
molecular switches. This platform enables fully tunable control of CAR-T cell
activity in a universal format that can be redirected to nearly any
therapeutic antigen target. The platform is expected to reduce the risk of
severe adverse events that have plagued the development of CAR-T cell
therapies clinically. We have demonstrated such a platform can reduce risks
related to cytokine release syndrome and double as a safety switch to turn
the therapy off in the case of an adverse event. We have further demonstrated
the temporal control over CAR-T cell activation enables the development of
robust central memory T cells. In preclinical mouse models, we’ve
demonstrated these central memory cells can be recalled affording on-demand,
in vivo T cell expansion. These concepts are expected to be central to
clinical efficacy with T cell-based therapeutics and important to ultimately
achieving efficacy in solid tumors. A proof of concept clinical trial will be
initiated in late 2019 for patients with lymphoma.
* Pluripotent Cell-Derived Engineered T and NK Cells as a Cornerstone Approach
for Off-the-Shelf Cancer Immunotherapy
Bob Valamehr, Fate Therapeutics
Several obstacles currently hamper the broad use of adoptive cell therapies,
including the inherent variability and cost of manufacturing of cellular
populations, the absolute requirement for precise genetic editing of multiple
elements and the elimination of undesired stochastic events associated with
cellular engineering. Here we present a unique approach to create master
pluripotent stem cell lines, clonally derived to contain precisely edited
events at the single-cell level and the conversion of that master cell line
into uniform populations of highly efficacious off-the-shelf engineered T and
NK cells.
* Exploiting Natural Killer Receptors for Autologous and Allogeneic CAR T Cell
Therapy of Cancer
David Gilham, Celyad
Chimeric Antigen Receptor (CAR) T-cell therapy has hit the headlines with
impressive clinical responses in hematologic B-cell malignancies that have
led to the successful licensing of two products that both target CD19.
Anti-BCMA CAR T-cell therapies for myeloma might come next but there is a
dearth of targets outside of the B-cell malignancy space.
Celyad has been exploring the potential of Natural Killer cell receptors to
target cancer. Specifically, the company is conducting a series of clinical
trials testing the safety and efficacy of CAR-T cells bearing the Natural
Killer Group 2D (NKG2D) receptor that can specifically bind eight stressed
induced ligands found on a broad range of cancers, yet largely absent from
the surface of non-malignant, healthy cells.
The first trial involved giving multiple infusions of autologous NKG2D-based
CAR-T cells without pre-conditioning chemotherapy and provided some initial
evidence of clinical activity with a good safety profile. Further clinical
activity has tested this CAR-T approach with pre-conditioning and standard of
care chemotherapy in hematological and solid tumors. Results of these trials
and the company’s trial of allogeneic NKG2D-based CAR T cell therapy will be
reviewed; the latter being thought to be the first allogeneic CAR-T approach
to be tested in the solid cancers.
Aside from NKG2D focused studies, the company is also embarking on a broader
allogeneic CAR T cell platform technology exploiting interfering RNA to
control graft versus host disease, the primary limitation of using allogeneic
cells for therapy.
Taken together, these early clinical studies suggest that the NKG2D receptor
in both autologous and allogeneic approaches could provide the potential to
target a broad range of tumor-targeting that could follow the success of CD19
and BCMA CAR T cell therapy. The challenges ahead relate to how to exploit
the targeting ability of NKG2D. Some of the next steps including manipulating
the memory phenotype of the CAR T cell product will be discussed.
* An Innovative Method for the Efficient, High-Throughput Transfection of
Primary Human T-Cells
Gregory Alberts, Lonza
Cancer with 18.1 million new cases and 9.6 million cancer-related deaths
observed in 2018 is still one of the most prevalent threats to human health
and well-being. Therefore, there is a strong need for better cancer
treatment. Cancer immunotherapy makes use of components of the immune system
like antibodies that bind to, and inhibit the function of, proteins expressed
by cancer cells. More promising novel immunotherapies rely on
patient-derived, genetically modified cells like T-Cells or Natural Killer
Cells that express chimeric antigen receptors (CAR).
Primary Human T-Cells are difficult to modify genetically using chemical
transfection reagents, just as virtually all non-dividing primary cell. Viral
transduction methods depend on the cumbersome production of the viral
vectors. Classical electroporation methods are often limited in throughput
and can result in impaired cell viability and functionality. Therefore, we
optimized the transfection and culture procedure for primary human T-Cells
using the 4D-Nucleofector™ System and 96-well Shuttle™ Device allowing the
high-throughput transfection of up to 96 independent transfection samples in
parallel.
Human T-Cells enriched from buffy coats were transfected with pmaxGFP™ Vector
through a high viability or high efficiency Nucleofector™ program in 20 ?l
volume. Donor-dependent transfection efficiencies of up to 70% with high cell
viability were achieved 48 hours after transfection. Transfection of eGFP
mRNA resulted in up to 60% transfection efficiency with more than 90% cell
viability 24 hours after transfection.
In a second step, we stimulated isolated human T-Cells for 2–3 days prior to
transfection via CD3 and CD28. 1.0 x 106 cells were transfected with the high
viability program using pmaxGFP™ Vector in 20 µl volume. Cells were analyzed
24 hours post transfection revealing transfection efficiency and cell
viability comparable to the results of unstimulated T-Cells.
In a last evaluation step, using unstimulated human T-Cells, we could show
very low intra- and interplate variability of the 96-well Shuttle™ System.
Transfection efficiencies varied between 62% and 77%, while a cell viability
of more than 80% compared to non-program control was observed.
In summary, we present an efficient and reliable transfection system for
primary human T-Cells that allows the parallel processing of up to 96
independent samples. The showcased method will support cell-engineering
approaches including screening of siRNA libraries, CRISPR-based genome
editing and rapid evaluation of different CAR constructs to advance novel
biomedical treatments including immunotherapy approaches.
FUTURE TECHNOLOGIES FOR BIOLOGICS DRUG DISCOVERY
Session Chair: Rob Howes, Ph.D., AstraZeneca (UK)
* Target and Drug Discovery in ‘Undruggable Space’ Using Functional Proteomics
Markus Muellner, PhoreMost
Despite an increasing spend on drug development, many diseases remain
unaddressed with little hope of finding new treatment options by conventional
means. One reason for this is the lack of knowledge regarding which proteins
are druggable, and which pockets on the protein surface might be most
beneficially targeted by small molecules. Current methods for discovering new
drug targets rely on genetic knock-out (CRISPR) or knock-down (RNAi) methods.
While these techniques can be useful in providing candidate therapeutic
target genes, the next step of developing protein-targeting therapies often
stalls due to insufficient information on druggability. To address this
problem, PhoreMost has developed a functional proteomics / phenotypic
screening technology called “Protein Interference” (PROTEINi®) that yields
both the target’s identity as well as information on available druggable
sites within the target. PROTEINi utilizes proprietary large ( >1 Million),
diverse, lenti-encoded libraries of small, self-folding, three-dimensional
peptide "shapes", which are expressed in live cells and, much like small
molecules, interfere and engage with available pockets on target proteins on
a proteome-wide scale. In contrast to shRNA or CRISPR screens, PROTEINi works
on the same level as most small molecules (the proteome) and is not
influenced by gene copy number, SNPs or genetic buffering. The process
discovers novel targets for a given assay system as well as peptides engaging
this target functionally as a starting point for drug discovery. PhoreMost
currently has internal small molecule programs in Oncology, Immuno-Onc and
Neurodegenerative disorders. We have recently also expanded the method into
Targeted Protein Degradation space to systematically discover novel and
functional E3 linkage sites across a set of 600 ligases.
* New Modalities for Drug Discovery
Rob Howes, AstraZeneca
Successfully drugging a target of interest is one of the key issues in drug
discovery. Small molecules and antibodies have a long and successful history
in drug development as our primary drug modalities. However, there are an
increasing number of targets that are not amenable to these drug modalities –
the ‘Undruggable Genome’. At AstraZeneca we are investigating new modalities
to be able to drug this previously undruggable set of targets. In this talk I
will describe our work with a range of new modalities including
oligonucleoties, therapeutic proteins, cyclic peptides, antibody mimetics and
PROTACS and how these are allowing us to tackle the ‘Undruggable Genome’.
* µ-Hydroporator: A Next-Generation Intracellular Delivery Platform
Aram Chung, Korea University
The introduction of biomolecules and functional nanomaterials into cells is a
crucial task in diverse biological situations, including immunotherapy,
genome editing, regenerative medicine, and fundamental biological studies.
Traditionally, intracellular delivery is achieved by carrier-based or
membrane-disruption-based techniques. Carrier-based approaches utilize
reconstituted viruses (e.g., lentivirus or AAV), or liposome (e.g.,
Lipofectamine), and when optimized they offer effective delivery (e.g., DNA
delivery for cell transfection). However, carrier-based approaches critically
suffer from toxicity, low-throughput, and require time-consuming and/or
labor-intensive preparation steps. Alternatively, membrane-disruption-based
methods such as electroporation and microinjection create transient
discontinuities on the cell membrane for target material diffusion. The
physical cell membrane disruption is relatively independent of target and
cell type, but they cause excessive damage to cells and suffer from limited
throughput. To address these drawbacks, recent advancements in microfluidics
and nanotechnologies have provided new solutions; however, identifying an
ideal method that offers easy, low-cost, highly efficient, high-throughput,
noninvasive and cell type/target independent delivery, remains challenging.
Here, we present a next-generation intracellular delivery platform termed
“µ-Hydroporator,” which introduces macromolecules into any cell type, at
high-throughput, in a single-step, without a vector or external apparatus.
µ-Hydroporator is purely based on the hydrodynamic cell
deformation-restoration process, which opens the cell membrane and enables
efficient transport of external target biomolecules or functional
nanomaterials into the cell. In brief, the cell suspension mixed with target
materials is injected into a T-junction microchannel with a micro-cavity
where inertial vortices instantaneously deform cell. This rapid hydrodynamic
cell deformation creates transient nanopores on the cell membrane, allowing
the convective transport of foreign target molecules during the cell
restoration process. Using µ-Hydroporator, we have successfully delivered
diverse macromolecules (e.g., RNAs, Plasmids, DNAs, DNA origami,
CRISPR-Cas9s, proteins, Q-dots, AuNPs, etc.) into various cell lines
including difficult-to-transfect primary cell lines such as stem and immune
cells, achieving highly efficient intracellular delivery (< 98%) in a
high-throughput manner (~1,600,000 cells/min) while maintaining high cell
viability (< 95%). Unlike traditional methods that rely on external
apparatus, and/or chemical modification of target molecules, µ-Hydroporator
only requires a syringe pump (not even a microscope!). This permits easy,
robust and simple operation and cost-reduction from not requiring a skilled
technician and instrument. We firmly believe that the reported µ-Hydroporator
will establish a new paradigm in intracellular delivery, which will immensely
benefit cellular engineering research and industry.
* High-Throughput Encapsulation and Selection of Cells Based on Antibody
Secretion Using Lab-on-a-Particle Technology
Joseph de Rutte, University of California, Los Angeles
We introduce a new approach to collect and quantify single-cell secretions
without crosstalk in monodisperse droplets formed by precisely structured
microparticles, enabling high-throughput screening based on this critical
cell function. The ability to analyze and sort cells based on secretions
(antibodies, cytokines, proteases, or other enzymes) has implications in
understanding cellular heterogeneity fundamental to biology and creating new
biotechnology products, such as biologics and cell therapies. Recently,
droplet microfluidics has emerged as a powerful approach to perform
single-cell secretion screening in high-throughput, using
compartmentalization in a small volume to accumulate secreted factors to high
levels for accurate detection. Despite this utility, the necessity of
specialized equipment and expertise on the end-user hinders its widespread
adoption. A platform that is fully compatible with standard lab equipment
(e.g. pipettes, flow cytometers) has the potential to dramatically extend the
reach of single-cell screening technology. Our particle-templated droplet,
i.e. “Dropicle”, approach is unique in that pre-fabricated particles are used
to form monodisperse emulsions that encapsulate single cells, requiring only
standard lab equipment for the end-user. Cavity-containing microparticles are
loaded into well plates and due to their morphology settle upright with their
cavities exposed. Cells are loaded into the microparticle cavities and adhere
via integrin binding sites. Biocompatible oil and surfactant are added and
the suspension is agitated by pipetting to create incrementally smaller
water-in-oil droplets. These resulting dropicles are monodisperse,
maintaining a size defined by the particle geometry (CV < 6%), while the
excess fluid is partitioned into surrounding smaller satellite droplets.
Secretions from encapsulated cells are captured on the associated particles
via protein A binding sites. Particles and associated cells and secretions
are transferred back to the aqueous phase enabling downstream labeling and
screening with standard flow cytometers. It was observed that seeded cells
filled the cavities of the particles according to single-poisson statistics
(in contrast to typical double-poisson statistics for single-cell,
single-particle pairs in drops). After dropicle formation cells maintained
high viability over 24 hours ( >80%). Initial tests with anti-IL-8 producing
CHO cells demonstrate the ability to capture and label secretions on
particles containing cells without crosstalk to neighboring particles.
Further, we demonstrate the ability to isolate cells associated with high
anti-IL-8 signals in high-throughput using commercial flow cytometry systems
( >100 sorts/s). Using this dropicle platform, researchers can perform
droplet-based assays using standard lab equipment without sacrificing the
precision of droplet microfluidics. Since dropicles are formed
simultaneously, compartmentalization is rapid ( >400k in 30s) and can be
easily scaled to accommodate large population screens. Further, the
associated particle enables additional functionality such as physicochemical
cues or cell-specific capture antibodies to select out specific cell types.
Our results demonstrate new capabilities for lab-on-a-particle technologies
that can accelerate the automation of single-cell assays.
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CELLULAR TECHNOLOGIES
Track Chairs: Jason Ekert, Ph.D., MBA, GlaxoSmithKline (USA) and Nancy
Allbritton, M.D., Ph.D., University of North Carolina Chapel Hill (USA)
DEMONSTRATING TRANSLATIONAL RELEVANCE OF ORGANOID AND MULTICELLULAR TISSUES FOR
PRECLINICAL MODELS OF HUMAN DISEASE
Session Chair: Nancy Allbritton, M.D., Ph.D., University of North Carolina
Chapel Hill (USA)
* Advanced Bioprinting Strategies for Tissue and Tissue Model Fabrication
Y. Shrike Zhang, Harvard Medical School
Bioprinting has recently emerged as an enabling technology in tissue
biofabrication at high fidelity. This talk will discuss our recent efforts on
developing a series of advanced bioprinting strategies, including sacrificial
bioprinting that allows generation of perfusable microchannels embedded in
hydrogel microchannels, microfluidic and hollow fiber bioprinting that
achieves production of standalone cannular tissues, and multi-material
bioprinting based on both extrusion and stereolithographic modalities that
enables creation of complex hierarchical tissue microstructures. Innovations
in various cytocompatible and bioactive bioink formulations will also be
presented. These platform bioprinting methods have been demonstrated to
facilitate faithful fabrication of biomimetic tissues and their models
spanning from the heart, liver, and musculoskeletal system to blood vessels
and beyond, as well as their diseased forms, for applications in regenerative
medicine and inaccurate screening of therapeutic agents.
* Wound-Conformal Delivery of Dermal Tissue Constructs for Full-Thickness Burn
Treatment Using a Handheld Bioprinter
Richard Cheng, University of Toronto
Full-thickness burns where both the dermal and epidermal layers of the skin
are destroyed result in high patient mortality due to infection, dehydration,
and shock. The current standard of care involves the direct application of an
acellular crosslinked protein scaffold which forms a temporary physical
barrier and promotes host cell migration into the wound area; however, this
is problematic in severe burns where little healthy skin is available for
repair. Delivery of patient-derived autologous or immunoprivileged allogeneic
cells are emerging as potential treatment options due to continuous
extracellular matrix remodeling and persistent cell signaling, but challenges
include homogenous delivery of cells onto a large, non-flat wound topography.
Although approaches such as cell spraying and microparticle injecting have
been explored in the field, the continuous formation of three-dimensional,
hydrogel-based tissue constructs uniformly on a physiological wound surface
remains unsolved. Here, we report the development of a handheld bioprinter
that delivers wound-conformal dermal tissue constructs to improve wound
healing in full-thickness burns. Mesenchymal stromal cell (MSC)-containing
fibrinogen bioink and thrombin crosslinker solutions were delivered through
on-board syringe pumps to a microfluidic printhead with internal bifurcated
channels. Dermal tissue constructs of consistent thickness covered with the
crosslinker were obtained at the exit. Wound-conformal delivery of these
MSC-laden dermal tissue constructs was achieved by translating the printhead
along the wound surface by a soft silicone wheel, while a two-axis gimbal
design allowed it to adapt to the wound topology. We observed that the
addition of 1% hyaluronic acid (HA) provided desirable shear-thinning
behavior of the bioink (1.2 Pa•s at shear rate 1/s; 0.35 Pa•s at shear rate
100/s), resulting in 83% of the starting thickness to be maintained for
deposition surfaces with inclination angles of 45 degrees. Furthermore, these
fibrin-HA hydrogels maintained high biocompatibility with the co-delivered
MSCs ( >94%), in addition to the long-term preservation of 3D morphology and
cell proliferation as shown with Hoechst/Phalloidin+ immunostaining over one
week. To demonstrate the clinical utility of this approach, we uniformly
distributed 1x10^6 MSCs/ml of the fibrin-HA hydrogel on a porcine 5cm x 5cm
full-thickness burn wound model and quantified a 1.4-fold improvement of
macroscopic re-epithelialization speed, a 1.3-fold increase in collagen
density in the dermal layer, and a 2.5-fold reduction in CD11b+ inflammatory
cell activity after 28 days compared to burn controls, as observed via
microscopic analysis of H&E histological stains. Taken together, we have
shown that the handheld bioprinter can conformally deliver MSC-containing
dermal tissue constructs directly on wound substrates with physiological
topographies, leading to full-thickness burn wound repair as shown in porcine
pre-clinical case studies.
* Generation, Validation and Application of Induced Pluripotent Stem Cell
Models for Functional Genomics
Lisa Mohamet, GSK
Myeloid cells play critical roles in adaptive and innate immunity and
dysregulation can result in disease pathology, such as neurodegeneration.
However, a detailed mechanistic understanding of human myeloid biology has
been hampered by the lack of robust and scalable models for cellular and
genetic studies. Conventional approaches rely upon immortalized cells that
lack biological relevance or primary cells which are limited in number,
reproducibility, and genetic perturbation. To overcome these challenges, we
developed and industrialized a human induced pluripotent stem cell
(iPSC)-derived myeloid platform that permits a robust and continuous supply
of progenitors that are subsequently differentiated into macrophage or
microglia. Since each iPSC line retains the genetic information of the donor
this provides an opportunity to harness human genetics to investigate in
vitro disease mechanisms.
We performed extensive transcriptomic, epigenetic, proteomic and metabolomic
analyses with concomitant phenotypic (e.g. flow cytometry, image analysis)
and functional assays (e.g. phagocytosis, cytokine secretion) to support
their use as a model to primary counterparts. Here, we demonstrate a
combination of conventional and innovative technologies to generate and
validate iPSC-derived target cell types as an unlimited source of patient
genotype-specific cells to study. We describe the implementation of such
disease-relevant models to enable large scale (epi)genomic functional
modeling for improved novel target ID.
The human biological samples were sourced ethically and their research use
was in accord with the terms of the informed consents under an IRB/EC
approved protocol.
* High-Throughput Organoid and Monolayer Platforms to Study Intestinal
Physiology
Scott Magness, University of North Carolina, Chapel Hill
Intestinal organoid technologies have revolutionized culture models to study
physiology, disease, and injury in vitro. While primary stem cell-driven
organoid cultures offer many improvements over conventional cancer cell line
models, individual organoids are highly heterogeneous in lineage ratios,
morphologies, growth properties, and other physiological parameters.
Additionally, the enclosed lumen prohibits easy access to the apical cell
surface to study nutrient absorption, the microbiome, and drug interactions
with the epithelium. We have developed platforms that address these
challenges. Specifically, our group focuses on engineering high-throughput
systems to study single-cell stem cell biology, stem cell niche co-cultures,
organoid dynamics, luminal physiology, and the microbiome. These platforms
can be applied to organoids across any tissue type, are scalable, portable,
and represent a high-resolution and statistically robust solution for
preclinical models of human disease.
APPLICATION OF ORGAN-ON-CHIPS AND MICRO-PHYSIOLOGICAL SYSTEMS
Session Chair: Deok-Ho Kim, Ph.D., Johns Hopkins University School of
Medicine (USA)
* Modeling Dystrophic Cardiomyopathy on a Chip for Phenotypic Drug Screening
Deok-Ho Kim, Johns Hopkins University School of Medicine
Directed differentiation of human pluripotent stem cells (hPSCs) into
cardiomyocytes typically produces cells with structural, functional and
biochemical properties that most closely resemble those present in the fetal
heart. Here we establish an in vitroengineered developmental cardiac niche to
produce matured hPSC-derived cardiomyocytes (hPSC-CMs) with enhanced
sarcomere development, electrophysiology, contractile function, mitochondrial
capacity and a more mature transcriptome. When this developmental cardiac
niche was applied to dystrophin mutant hPSC-CMs, a robust disease phenotype
emerged, which was not observed in non-matured diseased hPSC-CMs. Matured
dystrophin mutant hPSC-CMs exhibited a greater propensity for arrhythmia as
measured via beat rate variability, most likely due to higher resting
cytosolic calcium content. Using a custom nanopatterned microelectrode array
platform to screen functional output in hPSC-CMs exposed to our engineered
developmental cardiac niche, we identified calcium channel blocker,
nitrendipine, mitigated hPSC-CM arrhythmogenic behavior and correctly
identified sildenafil as a false positive. Taken together, we demonstrate our
developmental cardiac niche platform enables robust hPSC-CM maturation
allowing for more accurate disease modeling and predictive drug screening.
* Engineering the Cell Niche to Enhance iPSC-derived Cardiomyocyte Maturity and
Predictivity in a High-Throughput, Assay-Agnostic Manner
Nicholas Geisse, NanoSurface Biomedical
Stem cell technology holds great promise for mitigating the cost of drug
development by properly modeling human biology in vitro. Assays based on
these technologies have the potential to be more predictive of toxicity and
efficacy when compared to simpler single-molecule assays. Building these
representative organ-on-chip models relies on generating hierarchically
organized cells and tissues. In vivo, this organization is driven by a
complex interplay of cells and their environment, including the extracellular
matrix (ECM). Traditional cell culture environments—typically composed of
hard and unstructured glass or plastic— fail to fulfill the role of the ECM
in development. Consequently, many in vitro stem cell models often fall short
incorrectly reproducing critical in vivo phenotypes because cultured cells
oftentimes lose type-specific characteristics or express phenotypes
indicative of an immature developmental stage. Considerable effort is
directed at fabricating biomimetic culture environments that maintain or
promote mature phenotypes. However, making biomimetic substrates typically
involves costly or hard-to-reproduce techniques that are often incompatible
with many standard assays; these challenges are compounded when using
high-throughput techniques. Our objective is to develop novel surfaces that
mimic the mechanical and structural cues of the ECM without compromising
compatibility with state-of-the-art assays and instruments. The fabrication
scheme is based on high-precision photolithography techniques and is thus
highly reproducible, scalable and amenable to integration with most
industry-standard endpoint assays, including high-NA microscopy. Further, the
approach is centered on SLAS/ANSI/SBS-compliant formats that are compatible
with high-throughput automated platforms. Our data demonstrate that various
cell types are amenable to this approach. hiPSC-derived cardiomyocytes (CMs)
showed in vivo-like myofibril alignment, sarcomere spacing and width, and
expression of CM-specific proteins that are present in mature myocytes.
Higher-ordered 2D anisotropic myocyte tissues also showed adult-like
structure and electrophysiological responses to drugs in vitro when compared
to traditional unordered 2D isotropic constructs. Examples of phenotype
enhancement of other adherent mammalian cell types will be presented, further
demonstrating the utility of the approach for generating more representative
cells and tissues. Finally, we extend this technique to pattern the surface
of microelectrode arrays and demonstrate that these ECM-based cues enhance
the electrophysiological response of cardiomyocytes to various drugs of known
action. We conclude that our approach is a viable method for re-creating
specific aspects of the ECM that are critical for driving the development and
maturation of stem cells in culture.
* Automation of Multi-Organ Chip Assays and Microscopic Analysis
Ann-Kristin Muhsmann, Technische Universität Berlin
Microphysiological systems (MPS) are designed to mimic human organs and
physiology with the aim of improving the drug development process. They have
proven to be a powerful tool at the research level and a solid basis for the
establishment of qualified preclinical assays with improved predictive power.
However, one remaining drawback is the lack of comprehensive standardization.
This hinders their use for regulatory purposes as well as it impedes the
extraction of the full extent of information from acquired data. Moreover,
one main advantage of MPS in contrast to animal testing – the insight in “the
body” throughout the test assays – cannot be deployed fully as long as assay
execution, observation and analysis are highly time-consuming and resource
binding. This is why there is an immediate demand to automate MPS cultivation
and analysis. Concluding, we developed a dedicated system for the cultivation
of our TissUse Multi-Organ-Chips.
The Humimic AutoLab cultivates up to 24 Multi-Organ-Chips (MOCs)
simultaneously, providing customized incubation and systemic pulsatile media
circulation. Regular media exchanges, substance application and sample
extraction are executed automatically according to assay specifications.
Routine microscopic analyses such as bright field imaging and fluorescence
measurements are conducted in scheduled cycles and at any chosen time. To
hinder contamination and for operator protection, all liquid handling steps
are conducted under sterile conditions. Media, substances and samples are
stored in a refrigerator at 4°C, which are delivered on-demand via an
automatic provisioning system. Cell culture material such as well plates and
single-use pipet tips last for a minimum of four days until a restock is
necessary. The refrigerator also holds media samples and stores them until
further analysis. Dedicated software allows for a coherent and time-efficient
input of all assay parameters as well as it provides a variety of tools for
data analyzation. The Humimic LabOS also allows for assay feasibility checks
and provides the operator with instructions for equipping the system. The
fully automated image acquisition and ensuing analyzation will finally allow
for higher comparability of results and new findings through pattern
recognition and machine learning algorithms. Transferring our
well-established co-culture assays with organ models such as liver, skin,
intestine and bone marrow organoids proofed successful and showed high
comparability to the manually conducted assays.
* Novel Oxygen-Gradient Platform for the Co-Culture of Anaerobic Gut Microbiota
with Primary Human Colon Epithelium
Raehyun Kim, University of North Carolina at Chapel Hill and North Carolina
State University
Humans have co-evolved with their gut microbiota in a symbiotic relationship
essential for health, yet how these thousands of bacterial species influence
human biology remains little understood. A better understanding of the
interplay between human cells and gut microbiota is required to exploit the
complex relationships responsible for the local and distant effects of the
microbiome on the human body. Accordingly, significant interest exists in the
biotechnology community for improved in vitro models of the human
gastrointestinal system, in particular models that support human-microbial
co-culture. This feat is complicated by the fact that over 99% of gut
bacteria are obligate anaerobes that die in 30-60 min after exposure to room
air. Therefore, we have developed an easy-to-use and intuitive platform to
replicate the steep O2 gradient across the in vivo colonic epithelium, thus
create the appropriate environment required for anaerobes while maintaining
viable, healthy epithelial tissue. We have computationally modeled, designed
and prototyped the co-culture platform to fit within an SBS standard 12-well
plate. The co-culture platform consisted of a basal reservoir and luminal
reservoir with a porous polyester membrane and extracellular matrix (ECM)
support dividing the two reservoirs. Using our culture methods, colonic
epithelial stem cells were expanded on the ECM support and subsequently
differentiated into all cell types found in the intestines in a monolayer
ideal for compound screens and luminal stimulation/co-culture. Additionally,
the ECM could be micro molded to recreate the physical architecture of the
colon. Once the colonic epithelial layer was established, the luminal
reservoir was sealed with an O2-impermeable barrier which resulted in the
auto-generation of an anoxic environment (< 2% O2) in the luminal reservoir
within 8 hours by the O2 consumption of the epithelial cells. The basal
chamber remained normoxic to supply the epithelial cells with O2 through the
porous membrane and ECM support. The generation of a steep O2 gradient was
measured and experimentally confirmed. The resulting O2 gradient allowed for
anaerobes (lactobacillus rhamnosus GG) to be cultured in the luminal
reservoir in contact with an oxygenated colonic epithelial layer. Colonic
epithelium and anaerobic bacteria each maintained >90% viability when
co-cultured for ≥3 days. Our co-culture platform is simple, robust,
self-sustaining and easy-to-use. It does not require any fluidic and gas
control systems. It is based on a regular standard SBS microplate format that
industry and academia use daily. Thus, it can be adopted in any microbiology
laboratory without requiring new equipment.
DEVELOPMENT AND APPLICATIONS OF FUNCTIONAL GENOMICS TECHNOLOGIES
Session Chair: Alejandro Amador, Ph.D., GlaxoSmithKline (USA)
* Application of Genome-Wide Arrayed CRISPRn Screening for Target Discovery
Davide Gianni, AstraZeneca
Identification of novel and translatable therapeutic targets is urgently
required for diseases with unmet clinical needs. Application of CRISPR/Cas9
technology in an arrayed screening format holds great potential for rapidly
identifying new targets from physiologically relevant models. We have
developed an end-to-end arrayed CRISPRn library screening platform for target
discovery and integrated it with the capacity to interrogate advanced cell
models. We are using this platform to perform gene perturbation experiments
with the aim of identifying novel targets, understanding compound mode of
action, building patient stratification hypotheses and ideas for novel
combination therapies. A number of case studies will be presented
highlighting the progress we have made in making this platform amenable to
screening complex and advanced cell models. Taken together, these findings
underline how functional genomics approaches using CRISPR/Cas9 technology are
starting to revolutionize the drug discovery process.
Identification of novel and translatable therapeutic targets is urgently
required for diseases with unmet clinical needs. Application of CRISPR/Cas9
technology in an arrayed screening format holds great potential for rapidly
identifying new targets from physiologically relevant models. We have
developed an end-to-end arrayed CRISPRn library screening platform for target
discovery and integrated it with the capacity to interrogate advanced cell
models. We are using this platform to perform gene perturbation experiments
to identify novel targets, understanding compound mode of action, building
patient stratification hypotheses and ideas for novel combination therapies.
A number of case studies will be presented highlighting the progress we have
made in making this platform amenable to screening complex and advanced cell
models. Taken together, these findings underline how functional genomics
approaches using CRISPR/Cas9 technology are starting to revolutionize the
drug discovery process.
* Leveraging Functional Genomics in Oncology: A High Throughput Biology
Platform for Novel Drug Target Candidates
Alejandro Amador
New advances in gene editing, such as CRISPR-Cas9 technology, open new and
exciting avenues for genome-scale functional interrogation of the genome. The
newly formed Functional Genomics department (FxG) at GSK exists to provide
the deep scientific knowledge and technical capabilities required to reveal
genetic clues that underpin human disease, ultimately providing better
medicines for our patients. Our High Throughput Biology and Imaging (HTBI)
group in FxG has designed and built a high throughput automated robotic
platform to interrogate drug and genetic interactions (DrugxDrug, DrugxGene
and GenexGene) at scale by using cell-based high content imaging, flow
cytometry and plate reader screening assays. The group is formed by a
multidisciplinary team of scientists, including assay development and high
content imaging experts, computational scientists and automation engineers.
Our primary goal is to use functional genomics approaches for predicting and
identifying new oncology combination therapies, and immuno-oncology
mechanistic insights of GSK assets mode of action by interrogating gene
function using RNAi and CRISPR/Cas9 genome wide array screening. The
presentation will have examples on a couple of projects we are currently
working on highlighting the potential benefits to run a functional genomics
screening at scale.
* Using CRISPR-Cas9 Screening to Identify Genes Modulating the
Nigericin-Induced Pyroptosis
Christian Parker, Novartis
Inflammasomes are multiprotein complexes that sense danger or
damage-associated molecular patterns, DAMPS, as part of the innate immune
system. This recognition leads to the release of cytokines and other
signaling molecules that can then lead to cell death. Typically the term
inflammasome refers to the complex of proteins including PYCARD (ASC), NLRP3
(NLRC4 or AIM2) and pro-caspase-1. Upon activation by various DAMPS this
multi-protein complex promotes activation of caspase-1, which then leads to a
cascade of events that cause the release of intercellular signals such as
IL-β and IL-18. These danger signals, as well as released intracellular
components, can then further activate inflammasomes present in surrounding
cells. In addition, the activation of the inflammasome and caspase-1 can also
lead to cell death due to the activation of membrane pores such as gasdermin
D.
Mutations in components of the inflammasome have demonstrated this as a key
pathway regulating autoimmune diseases; e.g. cryopyrin-associated periodic
syndrome (CAPS), pyrin-associated autoinflammation with neutrophilic
dermatosis (PAAND) and Familia Mediterranean Fever (FMF). A detailed
understanding of the constituents of the inflammasome, and the pathway
leading to its activation will have utility in designing treatments for a
range of diseases associated with inflammation.
This report describes the development of an assay monitoring the induction of
inflammasome mediated cell death (pyroptosis). The development of this assay
allowed a genome-wide CRISPR-Cas9 screen to identify genes that regulate
assembly and activation of the inflammasome. The assay utilized nigericin
induction of the NLRP3 inflammasome mediated cell death in PMA differentiated
THP-1 cells.
The screen successfully identified known components of the inflammasome as
well as several genes that have not been previously implicated in
inflammasome induced cell death. The use of a genome-wide screen allowed a
comprehensive evaluation of the pathways controlling inflammasome assembly
and activation. The top 1000 genes were identified for the creation of a
focused mini-pool library of potential targets. Retesting of this mini-pool
of potential targets confirmed the activity of many of these genes as
modulating the inflammasome. So a further selection of genes was then made
and these genes were knocked out individually using CRISPR-Cas9.
This presentation will discuss a number of the challenges faced invalidation
of genes using this system as well as discussing potential means to address
these issues.
* Presentation Title TBD
TBD
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DATA ANALYSIS AND INFORMATICS
Track Chairs: Yohann Potier, Ph.D., Voyager Therapeutics (USA) and Nicola
Richmond, Ph.D. GlaxoSmithKline, (UK)
THE LAB OF THE FUTURE: AUTOMATION IN THE DIGITAL AGE
Session Chair: Umesh Katpally, Ph.D., Novartis Institutes for Biomedical
Research (USA)
* The Lab of the Future: Automation in the Digital Age
Michael Shanler, Gartner, Inc.
"Lab of the Future" (LoF) has recently become a popular topic for modernizing
laboratories. While performing upgrades to laboratory informatics systems
such as ELN or LIMS and adopting "hyped" technologies such as IoT, AI/ML,
AR/VR and blockchain may support modernization on the surface, many existing
LoF strategies run the risks of only delivering incremental value. Your LoF
strategies need to have a deeper impact to survive executive scrutiny and
must put an augmented data analytics strategy at the center. A LoF strategy
must also enable a digital twin for the lab at multiple levels- with impacts
on lab assets, personnel, and systems. As businesses transform, all aspects
of business, including the laboratory need to support digital optimization
and transformation. In this session, we review the meaning of digitalization,
the technologies important for achieving LoF and outline strategic steps for
ensuring your "LoF" strategy will be aligned to deliver true value in the
Digital Era.
* How Advances in Mobile, Voice and AI Technology are Impacting Scientists: The
Evolution of Technology in the Lab - University of California, San Francisco
Case Study
Ernesto Diaz Flores, University of California San Francisco
Scientists working today must navigate very large and complex datasets and
work within regulatory boundaries that are tighter than ever. To meet the
needs of modern scientists, lab documentation and management systems have had
to evolve from simple pen and paper to flexible, integrated digital tools.
We are at an era in which technology is at our fingertips, and having new lab
automation tools like a voice-powered AI digital lab assistant that allows
integration of multiple functionalities within a laboratory annotation system
greatly simplifies research workflows.
Ernesto Diaz-Flores is an Assistant Adjunct Professor at UCSF who works with
his team of scientists in the lab to study novel therapeutic targets for
high-risk subtypes of childhood leukemia. New technologies such as
voice-powered AI digital assistants enable scientists at the UCSF lab to take
voice notes, upload photos of experiments in real-time, set up several
reminders throughout the day and even dictate what reagents they need in
their shopping list, and have it all immediately added to their e-lab
notebooks. There’s also been less human error, scientists can capture and
access more information at the point of experimentation hands-free. When eyes
and hands are occupied on the experiment, their voice can make the
observations and capture the information in real-time with digital lab
assistants.
As mobile, voice and AI technology evolve, there are now new options for
scientists that seamlessly integrate with lab equipment and other data
sources. The developments in mobile, voice and AI/machine learning technology
are playing an important role in helping scientists bring their innovations
and discoveries to market, improve efficiencies in the lab and make their
work more reproducible.
* How Advances in Mobile, Voice and AI Technology are Impacting Scientists: The
Evolution of Technology in the Lab - University of California, San Francisco
Case Study
Gursatya "Guru" Singh, LabTwin
Scientists working today must navigate very large and complex datasets and
work within regulatory boundaries that are tighter than ever. In order to
meet the needs of modern scientists, lab documentation and management systems
have had to evolve from simple pen and paper to flexible, integrated digital
tools.
We are at an era in which technology is at our fingertips, and having new lab
automation tools like a voice-powered AI digital lab assistant that allows
integration of multiple functionalities within a laboratory annotation system
greatly simplifies research workflows.
Ernesto Diaz-Flores is an Assistant Adjunct Professor at UCSF who works with
his team of scientists in the lab to study novel therapeutic targets for
high-risk subtypes of childhood leukemia. New technologies such as
voice-powered AI digital assistants enable scientists at the UCSF lab to take
voice notes, upload photos of experiments in real-time, set up several
reminders throughout the day and even dictate what reagents they need in
their shopping list, and have it all immediately added to their e-lab
notebooks. There’s also been less human error, scientists can capture and
access more information at the point of experimentation hands-free. When eyes
and hands are occupied on the experiment, their voice can make the
observations and capture the information in real-time with digital lab
assistants.
As mobile, voice and AI technology evolve, there are now new options for
scientists that seamlessly integrate with lab equipment and other data
sources. The developments in mobile, voice and AI/machine learning technology
are playing an important role in helping scientists bring their innovations
and discoveries to market, improve efficiencies in the lab and make their
work more reproducible.
* The Hyperloop for the Lab: An Integrated Approach for Sample Delivery and
Treatment of Culture Dishes
Christoph Otto, TU Dresden
Digitalization, Automation and Miniaturization currently change the way we
live and work. It also affects the daily work in laboratories creating what
we perceive as the Lab 4.0 or the Lab of the Future. The disruptive
development of new technologies such as open-source automation technology,
the Internet of Things (IoT) and 3D-printing offer endless possibilities for
the rapid engineering of new laboratory devices, which are compact, adaptable
and smart. In conjunction with automated 3D-image analysis or deep learning
algorithms, powerful instruments emerge to create and resolve research data.
At the SmartLab systems department, the PetriJet31X hyperloop technology was
developed to automate all processes associated with culture dishes in
environments such as routine laboratories or culture development for the next
generation of antibiotics. The device technically is an x-y-robot consisting
of two linear axles enabled to transport all kinds of culture dishes from A
to B through a 3D-printed gripper-system which can also remove the lid of the
culture dish. The platform has been extended with a rail system and a small
robot with the ability to transport piles of culture dishes or other
laboratory material throughout the lab. The core part of the programming is a
self-learning control software that does not need any teaching – the most
time-consuming part of setting up a typical robot. With the presented
solution an experiment conducted on samples is planned only once and executed
for all culture dishes in the machine with the right processing station
installed – e. g. 3D sample imaging and analysis. It is no longer necessary
to specify locations for culture dish piles and treated dishes get allocated
dynamically and drawn e.g. from the incubating chamber while user
interactions are directed by LED-lighting. The system can process more than
1.200 culture dishes in an 8-hour shift and is equipped with a storage unit
for these culture dishes. One example of the benefit of the PetriJet
hyperloop can be found in routine labs for water and food inspection. Large
numbers of samples get incubated on specific medium in culture dishes and are
visually inspected regularly. Our system directly receives the tasks from the
laboratory information and management system (LIMS), creates job lists and
provides analytical data to the lab assistants through the LIMS. The data can
then easily be turned into result sheets right from the desk. The unique
feature of the system is that it can operate the night shift with no staff
present. The PetriJet31X hyperloop platform now operates at the Chair of
Microbiology at the TU Dresden for the screening of new antimicrobial
substances and the next generation of antibiotics. The system enables
biologists to screen agent combinations faster and use the gained image data
to feed new deep-learning algorithms.
* What, Where, How and Why? - Case Studies on Implementation of Lab of the
Future Technologies in Discovery Life Sciences
Umesh Katpally, Novartis
There have been a good number of articles written, presentations made and
webinars broadcasted on Lab of the Future (LoTF), including topics such as
digitalization and automation, for the past few years. We continue to read,
listen and discuss such topics even today and will continue to do so because
the Future is always about looking ahead. In this presentation, we will look
into the past few years to understand where we are currently in the context
of implementing LoTF ideas and how they have been implemented. We will also
look at what are some of the LoTF ideas that have not come to fruition and
why. Based on this can we anticipate what new LoTF ideas will become into
being in the years ahead?
DATA STRATEGY: SHARING AND REPURPOSING DATA
Session Chair: Marti Head, Ph.D., Oak Ridge National Laboratory (USA)
* Adventures in Data Sharing
Marti Head, ORNL
To democratize access to integrated data and transform our ability to make
data-driven decisions, organizations must break down barriers between siloed
data producers and foster a culture of open-hearted sharing of richly
contextualized data. This talk will unearth adventures in
cross-organizational data sharing, with storytelling and lessons learned over
my years at GlaxoSmithKline Pharmaceuticals and Oak Ridge National
Laboratory.
* To Blockchain or not to Blockchain? Practical Applications, Benefits and
Considerations of Blockchain Technology in Laboratory Workflows
Patrick Cullen, Yahara Software
In today’s world, no lab is an island. Samples, protocols, data, and ideas
need to be shared seamlessly within organizations and across scientific
communities to streamline the path to impactful progress. Also, the vast
amounts of data generated for each sample can be overwhelming to analyze and
maintain securely. Lastly, determining if data and results can be compared
apples-to-apples between different protocols, studies, or organizations can
be almost impossible.
In this talk, we will provide an overview of how blockchain can be a tool to
achieve immense improvements in sample accessioning, data transfer, and
workflow compliance using the ledgers inherent in the technology. Application
of blockchain to these workflows can provide advantages such as elimination
of ID duplication, reduction of missing or incorrect data, and decreased
workflow errors and omissions, among others. When different organizations are
part of the same blockchain, data integrity, protocol choice, and protocol
adherence are transparent to all organizations involved. This shared
technological ecosystem decreases barriers to communal data, study, and
protocol repositories and increases the likelihood of productive
collaboration.
Despite these benefits, the implementation of blockchain technologies is not
without challenges, requiring new tools, strategic thinking, and updated
approaches. To assist participants in evaluating opportunities for employing
blockchain technologies within their own laboratories, we will provide an
overview of some considerations organizations should take into account, offer
practical steps to evaluate potential blockchain use cases, and discuss
potential limitations of the technology.
* Enabling "Bench-to-Bedside" with FAIR data
Viral Vyas, Bristol Myers Squibb
Translational Medicine (“bench-to-bedside”) is a multidisciplinary field
focused on developing new therapies and procedures that extend and enhance
human life. Collaboration with internal and external labs is at the very core
of this effort which poses numerous challenges in fulfilling its promise.
Biomarker data from thousands of patients and multiple indications need to be
collected, collated with clinical data, analyzed and visualized. Data needed
to gain insights is often hard to find, incomplete, opaque, lacks conformance
and governance. Bristol-Myers Squibb has embarked on a set of bold strategic
initiatives dubbed “Digital Health - Sage” to tackle these challenges head on
by using FAIR (Findable, Accessible, Interoperable, Reusable) data principles
as a guide. Five key capabilities were delivered as part of the Digital
Health – Sage effort: data lake, data catalog, analytics environment, search
and visualization, data access and governance. The presentation will detail
business challenges, technology solutions, and lessons learned.
* Machine Learning is the Easy Part
Lauren DeMeuse, Roam Analytics
Data silos are prevalent across healthcare organizations, with challenges
from people, process and technical capabilities. Once that data is shared and
in a usable format, there's many new machine learning capabilities that can
unlock improved data-driven decision making and shared context. This
presentation will cover some of the typical challenges to data sharing,
strategies for overcoming, and opportunities for advanced analytics once
available.
FROM INSTRUMENT TO DECISION: IMPROVED DECISION-MAKING ON COMPLEX DATA AT SCALE
* Session Chair: Nicola Richmond, Ph.D., GlaxoSmithKline (UK)
* Deep characterization of drug libraries by image-based profiling and machine
learning
Michael Boutros, German Cancer Research Center
Images of drug-perturbed cells harbour a breadth of information about drug
effects that can be extracted and interpreted by machine learning
methodologies. When combined with genetic perturbations, such assays provide
a powerful approach to identify agonists and antagonists of potential targets
for therapeutic interventions. Chemical-genetic interactions thereby allow an
in-depth characterization of small molecules and their context-dependent
effects.
We have established a screening platform using high-throughput pipelines for
experimental and analysis workflows which allows us to screen libraries with
thousands small molecules. Using a simple staining procedure, termed
cellmorph, we extract multiparametric profiles describing overall changes in
cellular morphology and cell behavior using automated image analysis to
enable a deep phenotypic profiling of small molecules and other
perturbations.
Here, we phenotypically measured chemical-genetic interactions between
several mutant cell lines carrying single-gene knock outs and several
thousand small molecules. Unsupervised clustering and statistical modeling of
chemical-genetic interactions revealed promising interactions including
synthetic lethality and resistance. We could further show how the phenotypes
of mutant cell lines and small molecules can be quantified with machine
learning classifiers, allowing a direct scoring and interpretation of
drug-induced phenotypes. Importantly, the trained classifiers also
efficiently quantified dosage-dependent effects of drugs. Furthermore, we
will show how to apply image-based phenotyping to predict drug resistance and
sensitivity in patient derived organoids.
* Image-Based Cell Phenotyping Using Deep Learning
Samuel Berryman, University of British Columbia
The ability to phenotype cells is fundamentally important in biological
research and medicine. Current methods of phenotyping cells rely primarily on
flow cytometry to detect specific fluorescent markers. There are many
situations where this approach is undesirable, such as problems with
availability, specificity, cross-reactivity and cost of phenotyping markers.
Furthermore, the number of markers required can increase the complexity, may
exceed the detection limit, and even activate or decrease the viability of
some cells. Finally, cells that are non-spherical or are too few are
sometimes not compatible with flow cytometry. For these reasons, alternative
methods for phenotyping are sought after, with the focus on live-cell
imaging. Here, we investigate the potential to develop an “electronic eye” to
phenotype cells directly from brightfield and non-specific fluorescence
microscopy images.
Cells from ten cancer cell lines (MCF7, MDA-MB-231, LNCaP, PC3, U2OS, HCT,
THP-1, HL60, Jurkat and Raji) were non-specifically stained to identify their
nucleus (Hoechst), cytoplasm (Calcein green), and actin filaments (SiR
actin). Cells were dispensed into 96-well glass-bottomed imaging plates and
then imaged at 10X using brightfield and three fluorescence channels. The
microscopy images were segmented into four-channel 51x51 pixel images each
containing a single cell. The segmentation process used the DAPI channel for
locating individual nuclei and then used a combination of the other channels
to ensure other cells, or debris were not in close proximity.
To phenotype the cells, we developed a convolutional neural network (CNN)
consisting of a four-channel input, four convolutional layers, one
max-pooling layer, five fully connected layers, two dropout layers and seven
batch normalization layers. ReLU was used as the activation function
following each convolution or fully connected layer. Each node in the final
fully-connected layer represented the probability of the imaged cell
belonging to one of the known cell-lines. Softmax was utilized as a
cross-entropy classifying error function for back-propagation during
training.
Our CNN was trained over 20 epochs with Adam optimization and dropout to
avoid overfitting and rotational data augmentation to expand the dataset.
Using five-fold cross-validation, we show that the CNN was able to recognize
each cell line with a 94% average accuracy. Our results demonstrate the
ability to use deep-learning to phenotype cells directly from microscopy
images without specific markers. This capability will be valuable for
situations where phenotyping markers are unavailable or the cell sample
cannot be stained (such as before therapeutic use). We envision this approach
to be a general method for identifying cell types directly from image data to
identify the emergence of phenotypic shifts or new cell types.
* Assessing Biological Diversity of a Compound Collection Using High-Throughput
Cellular Imaging and No Ground Truth
Yusuf Roohani, GlaxoSmithKline
Image-based profiling of cellular phenotypes has emerged as a powerful source
of information for comparing chemical and genetic treatments. This has opened
the door to interrogating the biological impact of a chemical collection at a
scale that was not possible before. However, optimizing models to interpret
these images generally requires ground truth labels for the mechanism of
action that are difficult to generate at scale using conventional techniques.
Most often what is available for compounds in the discovery stage is the
nominal target but that does not capture primary and off-target effects.
Moreover, plate, batch and instrument variation can complicate the transfer
of methods and analyses across different datasets or instruments limiting the
utility of public data for this purpose. Thus, research groups are compelled
to build data analysis methods using the same instruments and protocols that
they would apply to their own data, even in the absence of corresponding
ground truth. In this talk, we describe a reliable system for discerning and
labeling distinct image-based cellular phenotypes in such a scenario. We
cover several methods for feature extraction (hand-engineered features, deep
learning) and analysis (clustering, similarity metrics, hit calling,
correcting batch effects). Most of our methods are based on the central
principle that biological replicates exhibit identical phenotypes. We run a
follow-up assays to validate our results.
* Interpreting AI Models Trained on High-Content Microscopy Data
Oren Kraus, Phenomic AI
The increasing popularity of high-content screening (HCS) and phenotypic
profiling in preclinical drug discovery is generating enormous amounts of
complex imaging data. The flexibility of these imaging-based assays allows
researchers to quantify many different biological processes using a single
technology. Examples include examining nuclear translocation of proteins,
internalization of receptors, and morphological changes in response to tens
of thousands to hundreds of thousands of treatments. Despite the experimental
throughput of HCS, analyzing and interpreting HCS imaging data remains a key
bottleneck in utilizing these systems. Scientists often need to collaborate
closely with computer vision experts and data scientists to extract
informative measurements (i.e. features) from imaging data and design
customized analysis pipelines for each new assay. Machine learning provides a
unique opportunity to automate and accelerate many of the steps involved in
analyzing HCS screens.
Recent results have shown that deep learning, specifically deep convolutional
networks (CNNs) trained directly on raw pixel data, outperform existing
approaches at classifying and clustering cellular phenotypes. The tradeoff
often associated with these methods is the lack of interpretability of
predictions made by deep learning models. We’ve designed several novel
machine learning process for HCS that prioritize interpretability, by
highlighting regions in the image that are responsible for the model’s
predictions. These models combine fully convolutional neural networks,
typically used for image segmentation, with convolutional multiple instance
learning (convMIL) to aggregate predictions spatially across fields of view.
Additionally, we’ve correlated predictions made by convMIL models with
features extracted from individual cells using traditional feature extraction
based analyses. Combining these two methods provides an additional layer of
model interability by automatically indicating which features are changing
most significantly between classes predicted by the CNN. Finally, we’ve
developed a novel approach for exploring single-cell phenotypes in HCS
screens using weakly-supervised learning models combined with an interactive
tool for exploring phenotypes. Weakly supervised models are CNNs trained to
predict every unique condition in an HCS screen based on image crops of
single cells. Once the model is trained, a feature vector is extracted for
every cell in the screen based on outputs from intermediate layers in the
CNN. These feature vectors are then converted to 2D using dimensionality
reduction techniques like t-SNE and UMAP. The interactive scatterplot we’ve
built allows scientists to explore this 2D space while being able to see what
individual cell phenotypes look like and which treatment conditions are
common in different clusters that appear. We’ve used this tool to discover
antibodies and compounds that are active in multiple assays that can include
multiple cell-types and 3D culture systems. Taken together, these approaches
significantly accelerate and improve phenotypic discovery programs.
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DRUG TARGET STRATEGIES
This track is generously sponsored by MSD.
Track Chairs: Margaret Scott, Ph.D., Genentech (USA) and Tim Wigle, Ph.D., Ribon
Therapeutics (USA)
PROTEIN HOMEOSTASIS: NEW DRUG DISCOVERY DIRECTIONS
Session Chair: Robert Blake, Ph.D., Genentech (USA)
* Leveraging Intrinsic Target Degradation
Delphine Collin, Cedilla Therapeutics
Protein degradation is a very effective way to inhibit target activity and
prevent its scaffolding function. At Cedilla, we are focusing on small
molecules that directly or indirectly regulate the homeostasis of a protein
of interest. This presentation will cover some of our strategic approaches to
direct and indirect degradation and the contribution of biomolecular sciences
(biophysics, biochemical, structural biology, molecular dynamics…) to this
novel path in drug discovery.
* A Homogeneous Cell-Based Membrane Potential Assay to Identify Compounds That
Promote Readthrough of Premature Termination Codons in the Cystic Fibrosis
Transmembrane Conductance Regulator Ion Channel
Emery Smith, Scripps Research Institute Florida
Cystic fibrosis (CF), an inherited genetic disease, is caused by mutation of
the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) gene, which
encodes an ion channel involved in hydration maintenance via anion
homeostasis. Nearly 5% of CF patients possess one or more copies of the
G542X, which results in a stop codon at residue 542, preventing full-length
CFTR protein synthesis. Identifying small molecule modulators of mutant CFTR
biosynthesis that affect “readthrough” of this stop codon, or premature
termination codon (PTC) to synthesize a fully functional CFTR protein
represents a novel target area of drug discovery. We describe the
implementation and integration for large scale screening of a homogeneous,
miniaturized 1536-well functional G542X-CFTR readthrough assay. The assay
utilizes HEK293 cells engineered to over-express the G542X-CFTR mutant, whose
functional activity is monitored with a membrane potential dye. Cells are
co-incubated with a CFTR amplifier and CFTR corrector to maximize mRNA levels
and trafficking of CFTR, such that compounds that allow translational
readthrough and synthesis of functional CFTR chloride channels will be
reflected by changes in membrane potential in response to cAMP stimulation
with forskolin, and CFTR channel potentiation with genistein. Assay
statistics were excellent with Z’ values of 0.69±0.06 despite a S:B of
1.19±0.04. As further evidence of HTS suitability, we completed an automated
screening of 666,120 compounds, identifying 7,761 initial hits. Following
secondary and tertiary assays, we have identified 188 confirmed hit compounds
with low and sub-micromolar potencies. Thus, the assay has integrated the
advantages of a phenotypic screen with high throughput scalability to
identify new small molecule G542X-CFTR readthrough modulators.
* Monovalent Versus Bivalent Degraders
Robert Blake, Genentech
The emerging drug design strategy based on inducing target protein
degradation offers the potential of drugging classes of proteins not
previously thought to be druggable. Furthermore, the magnitude of effect for
these agents is not limited by receptor occupancy and the duration of effects
can persist beyond drug exposure. The current design of protein degraders is
more commonly based on bivalent molecules, which consist of a ligand for the
target protein linked to a ligand for a ubiquitin ligase (such as VHL, CRBN
or XIAP). Due to their bivalent design, such drugs typically have a higher
molecular weight than classic small molecule drugs and may present some
non-ideal properties as drugs. An alternative monovalent degrader strategy is
exemplified by the group of drugs termed SERDs (selective estrogen receptor
degraders), for example, fulvestrant. The molecular structures of SERDs are
typically designed around a receptor-ligand and a “degradation tail”, whose
presence results in the degradation of the estrogen receptor. We have
recently reported that this monovalent strategy can also be applied to the
bromodomain and extra-terminal (BET) family, with the example of the
monovalent BRD4 degrader GNE-0011. We will use examples of monovalent and
bivalent degraders of BRD4 to compare these two complimentary degrader
strategies.
* Exploring protein homeostasis using DELPhe assays
Kandaswamy (Swamy) Vijayan, Plexium
Modulating protein homeostasis using small-molecules is an exciting new area
for therapeutics discovery. Inducing target degradation using bifunctional
molecules has been the predominant approach to this field. We will describe a
set of new tools that allows us to probe E3 ligase interactions without
requiring ligands to targets apriori. Phenotypic assays that use DNA-encoded
libraries (DELPhe) can scan chemical space for compounds that modulate E3
ligases in specific and interesting ways. Examples of both single-target and
multiple-target perturbations identified on DELPhe will be presented,
including a machine learning formalism to evolve pleiotropic perturbations
towards desirable goals.
DRUGGING RNA
Session Chair: Margaret Porter Scott, Ph.D., Genentech (USA)
* Opening New Frontiers of Biology with RNA-Targeted Small Molecules
Jessica Friedman, Arrakis Therapeutics
The identification of drug-like small-molecule medicines that directly bind
to RNA and modulate the biological function of RNA will vastly increase our
therapeutic target space. RNA folds into structures that have diverse pockets
into which small molecules can selectively bind. At Arrakis Therapeutics, our
main focus is to identify small molecules that selectively bind RNA
structures in critical regulatory regions of mRNA to modulate the expression
of otherwise undruggable proteins. Our platform enables the analysis of RNA
folding in vitro and in vivo as well as the identification of structures and
pockets within an RNA. Drug-like compounds that bind these pockets are
identified through high-throughput screening, followed by diverse biophysical
assays to confirm and characterize binding such as SEC-MS, SPR and NMR. The
biological impact of these compounds is evaluated in cell-based assays. The
discovery of compounds that act via RNA binding is a new approach that has
the potential to address previously intractable molecular targets and
diseases.
* Targeting Structurally and Functionally Diverse RNAs with Druglike Small
Molecules
Jay Schneekloth, NIH
Recent estimates indicate that greater than 85% of the human genome is
transcribed into RNA, yet just 3% of these transcripts code for protein
sequences. Coupled with an increased knowledge of the noncoding functions of
RNA and improved technologies for RNA structure determination, this
information has given rise to interest in RNA as a therapeutic target for
small molecules. In this presentation, I will discuss my group's recent
efforts to understand RNA-small molecule interactions. We have developed a
high throughput Small Molecule Microarray (SMM) screening platform, which we
use to rapidly screen and profile RNA-binding small molecules. Further, I
will discuss in detail several targets we have studied. I will also discuss
our efforts toward the structure-guided design of RNA-binding molecules and
the potential for future development.
* Translating RNA Sequence into Lead Small Molecule Medicines and Progress
Towards Small Molecule Antisense
Matthew Disney, Scripps Research
A major challenge in Medical Science has always been capturing targets for
drug development. The state-of-the-art in targeting of RNA is the use of
oligonucleotide-based modalities that target RNA sequence. Our focus over the
past 15 years has been on developing technologies to decipher which cellular
RNAs are “druggable” targets for small molecules and which small molecules
can target them, serving as lead medicines. I will describe advances in the
area of Small Molecules Interacting with RNA (SMIRNAs), including a
sequence-based small molecule rational design tool dubbed Inforna. This
approach allows sequence-based design principles for SMIRNAs of which only
oligonucleotides have been previously designed from the sequence. Inforna has
enabled the design of SMIRNAs against RNAs that cause hard to treat cancers
and incurable genetically defined diseases that have no known treatment. We
will describe these compounds and their implications for leveraging known
biology to advance lead medicines and also their implications as chemical
probes to understand previously unknown RNA biology.
I will also describe the development of approaches that allow for targeted
degradation of RNAs in cells and animals by using SMIRNAs. For example, we
have developed an approach that allows small molecules to recruit cellular
nucleases to an RNA target to cleave it selectively and
sub-stoichiometrically. Collectively, these studies show that small molecules
can be designed to target RNA by using sequence-based design to deliver
efficacious compounds targeting RNA including targeting the RNA for enzymatic
destruction in cells and animals.
* Development of a Novel High-Throughput Screening Approach to Target Specific
RNAs
John Joslin, GNF
There is a growing appreciation for the many roles that structured RNAs play
in disease progression. Accordingly, significant efforts are being devoted to
identify low molecular weight compounds that specifically target these RNA
molecules. These efforts may expand the number of therapeutic targets for
disease intervention. While several groups are developing antisense
oligonucleotides or siRNAs to target RNA, we sought to identify low molecular
weight compounds that have desired drug-like properties, oral
bioavailability, while retaining target specificity and potency. To
accomplish this goal we have devised novel biochemical assays that are
amenable to ultra-high-throughput screening. As a proof of concept, we have
used these assays to identify compounds that bind well-characterized
structured RNA, such as aptamers and ribozymes. For example, we developed
screens that target the theophylline aptamer, which binds theophylline with
high affinity and specificity. Through these screens, we identified
theophylline, as well as several related molecules that bind the theophylline
aptamer with an affinity that matches those reported in the literature. We
also identified several compounds that are distinct from the theophylline
scaffold, some of which have affinities exceeding that of the cognate ligand.
To date, we have screened over 3 million compounds in these assays and have
begun to understand the power and limitations of running HTS campaigns that
target RNA. This presentation will highlight the assay development, screening
results, and a view of what is required to carry out high-throughput
screening campaigns that purposively target RNA.
ADVANCES IN CELLULAR TARGET ENGAGEMENT
Session Chair: Tim Wigle, Ph.D., Ribon Therapeutics (USA)
* Re-Evaluating Kinase Inhibitor Selectivity and Residence Time in Living Cells
with Energy Transfer
Matthew Robers, Promega
I will describe the application of an energy transfer technique (NanoBRET)
that enables an approach to broadly profile compound fractional occupancy and
residence time against a variety of target classes inside intact, living
cells. Using this method, a broad-spectrum evaluation of compound engagement
can be measured against over 300 full-length human kinases in live cells.
Target engagement potencies correlate strongly with potencies using more
traditional pathway analysis readouts, thus providing a platform to establish
structure-activity relationships (SARs) for kinase chemical probes or lead
drug molecules.
In live cells, we have uncovered a surprising spectrum of intracellular
activity for certain cyclin-dependent kinase inhibitors (CDKi’s) and PROTACs,
offering opportunities for repurposing some chemotypes as selective chemical
probes for understudied kinases. We further evaluate opportunities for
achieving target selectivity under non-equilibrium cell culture conditions,
via protracted target residence time or PROTAC-mediated degradation. Here, we
describe a broadly applicable approach for evaluating existing and novel
chemical matter for selectively engaging CDKs in living cells.
* A Bespoke Screening Platform to Study Mono (ADP-ribosylation)
Tim Wigle, Ribon Therapeutics
Mono(ADP-ribosylation) (MARylation) and poly(ADP-ribosylation) (PARylation)
are post-translational modifications deposited on multiple amino acids, and
emerging evidence suggests they are also deposited onto nucleic acids. There
are 12 mono(ADP-ribose) polymerase (monoPARP) enzymes and 4 poly(ADP-ribose)
polymerase (polyPARP) enzymes that use nicotinamide adenine dinucleotide
(NAD+) as the ADP-ribose donating substrate to generate these modifications.
While there are approved drugs and clinical trials on-going for inhibitors of
the enzymes that deposit PARylation (specifically PARP1 and PARP2
inhibitors), MARylation is gaining recognition for its role in immune
function, inflammation and cancer, however there is a lack of chemical probes
to study the function of monoPARPs in cells and in vivo. An important first
step to generating chemical probes for monoPARPs is to develop screening
assays to enable determination of potency and selectivity of inhibitors
during the hit finding and lead optimization phases. Complicating the
development of enzyme assays is that the substrates for the majority of the
monoPARPs are unknown, and even for the ones with identified substrates, it
is uncertain how they engage their substrates. Here we describe the
development of multiple family-wide approaches to developing robust
high-throughput monoPARP assays that overcome this lack of knowledge around
their substrates.
* CETSA®-HT: Enabling a New Paradigm in Hit Discovery
Kirsten Tschapalda, AstraZeneca
High throughput screening (HTS) cascades have evolved to ensure that
high-quality hits can be identified from large screening collections.
Traditionally, most primary screens focus on the identification of modulators
of catalytically active sites, while target engagement assays are placed
further down the cascade. Well established technologies like
competition-based assays, affinity selection technologies or differential
scanning fluorimetry (DSF) depend on the availability of protein which is
tested in a non-native biochemical setting. Therefore, one of the main
concerns when initiating an HTS cascade remains the demonstration of target
interaction within a relevant cellular environment. The use of cellular
assays during primary screening and the HTS cascade presents an alternative.
However, cell-based screens can easily become very complex, risk off-target
effects and thus often require time-consuming target deconvolution of pathway
hitters. To date, there has been no single technology that can demonstrate
cellular target engagement in a suitable format for HTS primary screening.
The cellular thermal shift assay (CETSA®) can act as an interface between
this classic biochemical-cellular screening dichotomy. CETSA® facilitates
label-free screening in disease-relevant cells while approaching the ease of
biochemical assays. In an isothermal setup, full assay plates are heated to a
set point within the target protein melting curve. While most proteins unfold
and precipitate upon this heat-shock, a characteristic of protein-ligand
interaction is induced thermal stability. The remaining stabilized protein
can subsequently be detected with a pair of anti-species antibodies in an
AlphaScreen® system. This high throughput (HT) CETSA® format allows large
numbers of compounds to be tested in an HTS setting. Here, we report the
development of two CETSA®-HT assays along with the application of this
technology in HTS for the first time. This has been enabled following the
recent agreement between Pelago Bioscience and PerkinElmer to streamline
CETSA®-HT into validated kits and to offer support in the assay development.
In the Global High Throughput Screening Centre of AstraZeneca, we are
exploring the potential and the feasibility of CETSA®-HT for large scale HTS
campaigns ( >0.5M compounds). These datasets indicate the future impact
CETSA®-HT will have in hit identification. This is particularly timely given
the expanding interest across drug discovery groups in new target protein
classes. With new modalities like PROTACS (proteolysis targeting chimera)
non-catalytically active proteins can now therapeutically be targeted.
Utilizing CETSA®-HT to identify target engagement in cellular environments
early during primary screening could shift the paradigm of hit finding.
* Targeting Engagement by Utilising CETSA in Drug Target Studies
Laurence Arnold, Pelago Bioscience
Target engagement is a fundamental paradigm in drug discovery. A significant
portion of projects fail to reach the clinic due to lack of efficacy or
failure to show the lead candidate is interacting with the intended target in
a more complex environment. Using the proven CEllular Thermal Shift Assay
(CETSA) technology to measure target engagement in various matrixes, such as
tissues, intact cells or lysates is increasingly common for SAR studies and
lead optimization. It is also possible to inform early-stage programs with
CETSA technologies and investigate in-situ ligandability. This study looks to
investigate a well-established oncology target using CETSA high throughput
platform (HT). CETSA HT measures direct target engagement through the
interaction of the protein and molecule after a heat challenge, with
versatile readouts applicable to HTS and miniaturization for robotic
platforms. Assay development for CETSA HT includes the development of HTS
off-the-shelf kit formats and in this project, investigations into target
engagement of fragments within a cellular environment. These target
engagement studies are not reliant on in-vitro and often abstract functional
screens or methods, often limiting to certain protein classes.
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MICRO- AND NANO TECHNOLOGIES
Track Chairs: Amar Basu, Ph.D., Bioelectronica Corporation (USA) and Elodie
Sollier, Ph.D., Benkei (France)
MICRODEVICES FOR HIGH-THROUGHPUT CELLULAR AND BIOMOLECULAR PROFILING
Session Chair: Alex Shalek, Ph.D., MIT (USA)
* Enabling Precision Medicine: Pipetting at Single-Cell Resolution
Georges Muller, SEED Biosciences SA
Single-cell isolation is essential in stem cell biology, cancer research and
biotechnology among others. For example, to ensure quality, safety and
efficacy of the biotherapeutic product, companies shall demonstrate that each
new recombinant cell line has been cloned from a single progenitor cell (WHO,
2014). Because available methods for cell cloning do not provide fully
traceable cells yet, companies may waste up to 50 weeks in clonal validation.
To solve this issue, we have developed an automated impedance-based pipetting
robot for single-cell dispensing, allowing for traceable cloning of single
cells. This technology permits the efficient and gentle isolation of
industrial cell lines as well as rare and fragile stem cells and cancer
cells, at a single-cell resolution, so that cells can be individually
expanded in culture, transplanted downstream or analyzed by omics assays. We
will present the technology and illustrate its key features through various
case studies.
* An Adaptable Microfluidic Platform for Single-Cell Pathogen Identification
and Antimicrobial Susceptibility Testing
Pak Kin Wong, The Pennsylvania State University
Bacterial infections, such as bloodstream infections (BSI),
ventilator-associated infection (VAI), and urinary tract infections (UTI),
are a common cause of patient morbidity and mortality. Rapid identification
of the causative pathogens and their antimicrobial susceptibility profiles
will improve the clinical workflow for clinical management, accelerate
clinical decision-making, and improve patient outcomes. However, definitive
clinical microbiological analysis of samples obtained from patients requires
several days, hindering proper management of infection and driving the
overuse and misuse of broad-spectrum antibiotics. Novel precision
technologies for rapidly identifying the pathogens and their antibiotic
resistance are highly sought-after.
To address this clinical unmet need, we develop a nanotube assisted microwave
electroporation (NAME) technique for intracellular detection of
species-specific bacterial 16s rRNA in 30 minutes. NAME allows
amplification-free pathogen identification at the single-cell level. Unlike
typical sensing techniques that lyse the bacteria and dilute the
intracellular content, NAME directly detects species-specific regions of the
16S rRNA inside the cells. Due to the small volume of a bacterium, the target
molecule in the cell has a high effective concentration, which creates a
strong signal for single-cell detection without amplification. Intracellular
detection of bacterial 16S rRNA in viable cells also facilitates subsequent
antimicrobial susceptibility testing (AST). By incorporating an adaptable
microfluidic design, we demonstrate a phenotypic AST system that rapidly
determines the existence of bacteria, classifies major classes of bacteria,
detects polymicrobial samples, and identifies antimicrobial susceptibility
directly from clinical samples at the single-cell level. The adaptable
microfluidic system can dramatically accelerate the workflow of the
microbiological analysis. Pathogen classification, which is based on
microfluidic separation and microscopic inspection, eliminate the slow
culture step. This approach rules out negative samples classify bacteria
according to size and shape in as few as 5 minutes and identifies samples
with multiple pathogens for polymicrobial infection diagnosis. By monitoring
the bacterial growth directly, AST results can be reported in as few as 30
minutes or in a time scale similar to the doubling times of the bacteria.
In this study, we report the integrated microfluidic system for rapid
pathogen classification and AST. We demonstrate the NAME technique for
identifying bacteria that commonly cause BSI, VAI, and UTI. In collaboration
with our clinical and industrial partners, we are developing an integrated
ID-AST platform for the rapid diagnosis of bacterial infections. We pilot a
study of 25 clinical urine samples to demonstrate the clinical applicability
of the microfluidic system. The platform demonstrated a sensitivity of 100%
and specificity of 83.33% for pathogen classification and achieved 100%
concordance for AST. Our results demonstrate the analytical and clinical
feasibilities of the integrated ID-AST platform for rapid microbiological
analysis.
* Building Tissue to Understand How Tissues Build Themselves
Zev Gartner, UCSF
The capacity of cells to self-organize into tissues is critical to their
normal developmental and their ability to self-repair. Thus, a better
understanding of how tissues self-organize will improve our ability to
synthesize tissues and organs in the lab, and suggest new strategies to slow
the breakdown of tissue structure that contributes to the initiation and
progression of the disease. We are working to understand the mechanisms used
by cells to self-organize robustly in the breast and gut, and how these
programs are susceptible to the perturbations that underlie diseases such as
cancer. We are also developing new single cell analysis technologies to help
decode the logic of paracrine signaling networks that support the
self-organization of these tissues.
* Translating Single-Cell Genomics to the Clinic
Alex Shalek, Massachusetts Institute of Technology
While several methods exist for sampling tissues in clinical contexts,
without high-fidelity tools for comprehensively profiling them, we are both
limited in our capacity to understand how constituent cells and their
interactions impact prognosis, and to select and develop precision
therapeutics. Recent years have witnessed transformative and intersecting
advances in nanofabrication and molecular biology that now enable deep
profiling of low-input samples. Collectively, these afford new and exciting
opportunities to study cellular heterogeneity, starting from the level of the
single cell, and may unlock the diagnostic, prognostic, and discovery
potential of clinical isolates. Illustratively, I will introduce how we can
leverage single-cell genomic approaches – and, in particular, single-cell
RNA-Seq – to explore the extensive functional diversity between cells,
uncovering, from the “bottom-up,” distinct cell states and their molecular
drivers. Moreover, I will discuss high-throughput experimental strategies and
demonstrate how they can be leveraged to achieve the statistical power
necessary to reconstruct intracellular circuits, enumerate and redefine cell
states and types, and transform our understanding of cellular decision-making
in health and disease on a genomic scale.
NOVEL SAMPLING STRATEGIES AND HIGHLY MINIATURIZED SYSTEMS FOR MASS SPECTROMETRIC
ANALYSIS
Session Chair: Daniel Austin, Ph.D., Brigham Young (USA)
* Microscale Linear Ion Trap for Portable Mass Spectrometry
Daniel Austin, Brigham Young University
We present initial results from a high-aspect-ratio linear ion trap employing
20-micrometer-wide electrodes patterned onto ceramic substrates, with a
characteristic trapping dimension of 800 micrometers. In previous efforts, we
showed that a variety of ion trap geometries can be made using assemblies of
two ceramic plates, the facing surfaces of which are patterned with
appropriately shaped electrodes. The present report shows the significant
miniaturization of this approach. Mass spectra of organic compounds with this
device have a resolution of 2-3 amu. These highly miniaturized analyzers are
now being developed for portable GC-MS instrumentation. Aluminum electrodes
were deposited onto one side of each ceramic substrate. Electrodes are
wire-bonded to a printed circuit board, which connects with a capacitive
voltage divider. Two plate-PCB assemblies are mounted in a sandwich
configuration, with the trapping fields being established in the space
between the plates. Prior to patterning, a tapered ejection slit, 166
micrometers wide, was laser-cut into each substrate for ion ejection. The
taper is critical to prevent ions from striking the inner wall of the slit
and building up space-charge while allowing the thickness of the substrate to
remain sufficiently thick for strength. Dipole resonant ejection of ions, in
which the applied ejection waveform is phase-locked with the drive RF, was
demonstrated by the use of special phase-tracking circuit. The alignment of
the substrates was demonstrated using a set of 4 micropositioners (three
linear and three angular). Low-power performance—essential for portable and
hand-held mass spectrometers—was also demonstrated, with a maximum RF
amplitude of 400 V at the highest point in the scan. The typical mass
resolution of small organic compounds (toluene, xylenes) is 1.5 Da.
Experiments using high molecular weight compounds (octofluorotoluene and
perfluorotributylamine) showed typical mass resolution of 2-3 Da. The effects
of higher operating pressure on mass spectra were also examined. Resolution
decreased at pressures above 5 mTorr, but suitable spectra could still be
obtained at pressures of up to 42 mTorr. Resolving power is decreased
compared with the larger scale version of this device, possibly due to
increased space charge. However, the signal to noise ratio is largely due to
the high aspect ratio of these traps—the ratio of the length to the
characteristic trapping dimension is greater than 40, providing a large
trapping volume.
* A Benchtop Biochemical Analyzer: Microchip Capillary Electrophoresis Coupled
to High-Pressure Mass Spectrometry (HPMS)
J. Michael Ramsey, University of North Carolina, Chapel Hill
Biochemical analysis needs are frequently addressed using liquid
chromatography coupled to mass spectrometry (LCMS) in a centralized
laboratory setting. While these systems can be quite versatile to address a
broad range of biochemical measurement problems, they are correspondingly
complex and require a trained operator to produce results. LCMS
instrumentation also typically occupies a large footprint and requires
utilities beyond a simple power outlet. Our laboratory has been pursuing
miniaturized versions of liquid phase separation systems and mass
spectrometers for over two decades. We are combining these two technologies
to demonstrate a compact benchtop analyzer that can address measurement needs
in areas such as cellular biology, clinical diagnostics, and
biopharmaceutical research and development that would normally be
accomplished using LCMS.
We have developed microfabricated capillary electrophoresis (microchip CE)
devices with monolithically integrated nano-electrospray ionization (ESI)
emitters that exceed the performance of conventional CE-ESI implementations.
CE separations require ionic analytes, whereas LC can potentially separate
either charged or neutral compounds. Biochemical species of interest are
predominately ionic and CE systems outperform LC systems for separative
performance, while the former can also be implemented more compactly with
simpler components, e.g., voltage sources versus high-pressure pumps.
Microchip CE has been used to separate ions as small as elemental species to
intact monoclonal antibodies. One million theoretical plates of separation
can be generated in one to a few minutes. Moreover, the microchip CE
cartridge is easy to use and does not require any plumbing to connect the ESI
emitter.
We have also been involved in the development of a new form of mass
spectrometry, HPMS, that can be implemented in a compact form as it operates
at pressures several orders of magnitude higher than conventional MS, i.e.
approximately 1 Torr. Operating at such pressures allows significant
simplification of the vacuum system and the use of a vacuum pump that can
rest in the palm of your hand. The mass analyzer in HPMS is a form of ion
trap with sub-mm scale critical dimensions. We have theoretically and
experimentally demonstrated that HPMS resolution can be increased by
decreasing critical dimensions and correspondingly increasing the RF drive
frequency.
In this presentation, we will describe microchip CE and HPMS and the coupling
of the two technologies to create a compact and useful biochemical analysis
tool. The instrument implemented with a 96 well plate autosampler is
approximately the size of a tower computer. Example applications such as
monitoring bioreactor broth constituents will be presented.
* A Small Footprint Ambient Ionization Enabled High-Throughput Chemical
Detection System
Brian Musselman, IonSense, Inc.
Rapid analysis of the products of chemical reactions produced in
high-throughput experiments (HTE) are completed by thermal desorption of
sub-microliter volume samples into an ionizing gas. The heated ionizing gas
completes the vaporization of the sample typically present in
dimethyl-sulfoxide in 1-3 seconds per sample with rapid mass detection.The
utility for Direct Analysis in Real Time (DART) for ionization of chemicals
in the presence of aprotic solvents such as DMSO, and DMF has been employed
to enable detection of those chemicals from sub-microliter volumes of the
sample thus eliminating the need for sample dilution before analysis by
LC/MS. The sub-microliter samples have been prepared by using several sample
disposition method including low volume automated pipettor station and a high
capacity disposable pin-tool. Using these devices we have chemicals present
in concentrations appropriate for high throughput experiments that have been
deposited onto a wire mesh surface which is then positioned between the DART
source exit and the mass detector entrance for analysis. The use of small
volume samples reduces the potential for matrix effiects by limiting the
abundance of chemicals present in the ionizing gas. A rapid sampling of the
small size droplets present on the sample supporting wire mesh enables
continuous screening of the samples. We document the performance of each
sampling method at analysis 1 per second to demonstrate the potential for a
full 386-well sample plate analysis in under 10 minutes. Automated data
analysis of the continuous collection of spectra in the data file is
demonstrated using a file parsing software to permit the archival of the
results. An outline of the overall workflow and its utility for simplifying
the analytical effort in support of nanochemistry will be discussed.
* ADE-OPP-MS: ESI-Mass Spectrometry-Based Bioanalytical Platform with
Ultra-High Throughput
Hui Zhang, Pfizer Inc.
Recently, a new bioanalytical platform based on the coupling of acoustic
droplet ejection (ADE) and open pore probe (OPP) technologies to mass
spectrometry with standard electrospray ionization (ESI) ion source was
introduced. Extraordinary performance has been demonstrated with this new
platform, including plate-reader sampling speed, label free detection with
MS, simplicity of assay development, just to name a few. As the pioneers to
develop and apply this technology, our group has demonstrated the instrument
capability and shared several seminal proof-of-concept studies supporting
different areas of drug discovery including functional HTS, Drug-Drug
Interaction (DDI), and other ADME applications in previous SLAS conference.
With the commercialization of this new platform coming along, the technology
had been further enhanced especially around system integration, automation,
and robustness. We will be happy to report back the recent technology
advancements, as well as the recent studies of the different screens Pfizer
team has been working on to support live projects.
One lipid based HTS assay has been developed and successfully applied for
hits triage and SAR support. Challenges of the lipid sampling and handling
will be highlighted, and solutions and performance highlights will be
provided. Both false positive and false negative hits identified from other
HTS means were effectively teased out taking advantage of the highly
selective of MS detection. With the integration of liquid handling
workstation (Beckman I7) and other key peripherals to the ADE-OPP-MS
instrument and implementation of automation solutions, ultra-high throughput
screening with mass spec became a reality and can provide up to hundreds of
thousands of compounds per day throughput. Besides pharmacology advancements,
high throughput parallels medicinal chemistry applications enabled by this
ADE-OPP-MS technology will be shared. Ultra-low sample requirements provide
by ADE technology enabled readouts with as little as 1uL reaction, making
100X cost savings for the reagent and enabled much bigger chemical libraries
to be made. Chemical reactions can be thoroughly evaluated with OPP-high
resolution MS (HRMS) at second/reaction speed, 60-100X faster than the
current paradigm. Such large and high-quality dataset enables the generation
of big data around chemical reactions to feed in machine learning/artificial
intelligence builds. Finally, biomarker analysis is another direction that we
are interested in as another big advantage of the ADE-OPP-MS platform is that
it can handle dirty sample matrixes with minimum sample preparation. We will
show some recent example such as detecting N-methyl nicotinamide (NMN) from
human urine samples or plasma pharmacokinetics (PK) studies where
high-quality data (and equivalent to those obtained by conventional LC/MS
method) were acquired without no sample preparation or just one step
dilution; while the analysis time was effectively cut from multiple hours to
a few minutes.
TECHNOLOGY DEVELOPMENT FOR MICRO AND NANOFLUIDIC DEVICES
Session Chair: Élodie Sollier, Ph.D., Benkei (France)
* Limitations and New Methods in the Characterization of Microfluidic Devices
for Manufacturing QC
Maximilian Pitzek, Stratec Consumables
The range of applications for microfluidic devices is constantly expanding
and so are the challenges for manufacturing. There is always exciting for the
development of new manufacturing methods, but the importance of new
analytical methods is often underestimated by contract manufacturers. Here we
present our latest advances in the metrology and derived QC of injection
molded microfluidic devices. Especially in the development of nm-sized
fluidic channels, µm-sized fluidic channels with nm-precision, and devices
with a combination of inorganic and organic coatings we came across
challenges that required new analytical methods. The questions range from a
simple "how deep is a microfluidic channel after bonding", to "what
manufacturing process has the biggest impact on channel roughness - from
Mastering to the finished device". To answer these questions, we had to find
new ways to characterize the different processes along the manufacturing
chain. The analytical methods that we developed opened up the door to new
types of devices, or made it possible to mass manufacture new high complexity
consumables.
* A Portable Quality Control Lab in The Era of Food and Beverage Craftsmanship
Maciej Grajewski, SG Papertronics B.V. and University of Groningen
In the past decade, we have observed a tremendous growth of interest in food
and beverage craftsmanship due to new trends for sustainability and
eco-friendliness. This has resulted in numerous exciting initiatives in food
and beverage production. However, these initiatives have limited resources
and thus struggle to maintain consistently high-quality processing.
Preventing losses, financial and otherwise, caused by unpredictable events
such as microbiological contamination is often challenging.
Traditionally, these problems are tackled by quality-control (QC) protocols
embedded in the production process. However, the implementation of QC often
requires trained personnel and professional analytical equipment, with
associated costs well beyond the budgets of small entrepreneurs. Therefore,
it is a great opportunity for the rapidly growing field of portable
(bio)chemical analysis to step in and offer a viable solution for this
market. However, tests are often developed for trained chemists who are
capable of proper sample acquisition and data interpretation. We propose an
alternative technology that can accommodate common colorimetric tests, in a
portable format that can be used by non-chemists. Moreover, the technology
provides shorter sample-to-answer times for samples collected and analyzed
directly at the production site by the craftsman. To achieve this, we utilize
a patented sample concentration technology that enables quantitative
analytical tests with enhanced sensitivity, combined with a sample
acquisition system and data interpretation software.
The sample concentrator used in this work was developed by rapid prototyping
with a stereolithographic 3D-printer. The concentrator cartridge consists of
a sample acquisition module for volumetric sampling with subsequent liquid
transfer to a porous particulate column packed into a 3D-printed cartridge. A
series of branched air ducts embedded in the sample concentrator guide
pressurized air from a simple gas supply to a selected region of porous
membrane fixed into the bottom of the cartridge. Liquid samples are reacted
with reagents in the 3D cartridge and then concentrated on the membrane
through evaporation of solvent by the gas. The analysis is subsequently
carried out by colorimetry. Integrated software analyzes the test results and
compares it to results stored in our database so that every craftsman can use
our system without the need for extensive chemical training. Additionally,
our cartridges provide these tests with better protection against
contamination, with improved user-friendliness, and the possibility of
combining multiple materials for one test.
The described technology has been applied for QC testing in different
branches of the food and beverage industry. Our technology contributes to the
market of portable analysis because it provides a tool that can be applied
outside an analytical laboratory, but with comparable results. This means
shorter times between sampling and result, and, importantly, provides
substantially better options for the small food-and-beverage entrepreneur to
realize improved QC.
* Single-Cell Hybrid Microfluidics as a Selection and Sorting Tool in the
Mammalian Gene-Editing Pipeline
Kenza Samlali, Concordia University
Developing new engineered clonal cell lines is essential for loss-of-function
studies, investigating protein function and unraveling signaling cascades and
metabolic pathways. The current mammalian cell engineering pipeline of DNA
delivery, selection, screening or sorting, and single-cell clonal expansion
remains challenging and heavily relies on multiple expensive automated
systems like a flow cytometer, cell sorters and colony pickers to increase
experimental success.
Our group has shown the use of digital microfluidics for automating
gene-editing procedures (Sinha et al.,2018), yet these devices cannot still
select for successful edits or sort cells out into single clones.
Hybrid microfluidics combine the digital and droplet microfluidic paradigms
in one device (Ahmadi et al., 2019), with electrode lined channels that can
introduce more control over droplets in channels. In this talk, I will
present four key results: First, we developed a hybrid microfluidic method
for deterministic single-cell encapsulation. I’ll introduce a single-cell
trapping array that is capable to achieve near-perfect one-cell-per-droplet
encapsulation. Second, I will present the droplet operations that can be
performed on this device. This includes precise on-demand droplet operations
including releasing, merging and keeping single-cell containing droplets.
This allows for dynamic assays of mammalian single cells, based on screening
parameters that go beyond the traditional fluorescence based screening or
sorting methods. All these operations, including encapsulation, can be easily
performed with a graphical user interface. Third, I will describe the
efficiency of cell trapping, cell encapsulation, droplet release and droplet
keeping under different flow rates. Fourth, I will describe results that
validate our platform for use in the mammalian cell engineering pipeline,
using a breast cancer cell line (MCF-7) and a lung carcinoma cell line
(NCI-H1299) as a model system. Specifically, I will show results related to
encapsulation of a heterozygous and edited cell population and instant
selection of transfected single-cells with subsequent generation of a clonal,
isogenic edited cell line that could be expanded off chip.
This novel microfluidic device avoids the use of flow cytometry, cell sorters
or limited dilution experiments to establish monoclonal engineered cell
lines. Furthermore, the device can operate with low cell counts, which can
potentially be used to handle sensitive cell lines along with enrichment of
rare populations.
* Microfluidic circuits with fluid walls to study cell migration
Cyril Deroy, Oxford University
A microfluidic technology based upon the use of “fluid walls” was recently
introduced to address the lack of uptake of traditional microfluidic devices
in biomedicine. Reasons cited for this lack of uptake include technical
complexity, high failure rates due to gas-bubbles altering flows and
affecting cells in micro-channels, the questionable bio-compatibility of
materials like polydimethylsiloxane used to make devices, the inaccessibility
of cells growing in them, and – probably the most important – biologists
cannot use their familiar culture dishes and microscopes. The new technology
reshapes fluid interfaces between two immiscible liquids (cell-growth medium
and a bio-inert fluorocarbon, FC40) in a standard cell-culture dish, to form
arrays of isolated liquid chambers. Each aqueous chamber is separated from
its neighbors by transparent liquid walls of FC40. At the microscale, these
fluid walls prove to be strong, pliant, and resilient. We now extend this
fluid-shaping technology to create complicated circuits that can have almost
any imaginable 2D shape, and demonstrate the power of the approach through a
range of dynamic biological assays, in which cells migrate up concentration
gradients established by diffusion. In one, primary mouse macrophages from
the bone marrow are imaged as they migrate over polystyrene towards a
chemo-attractant. More complex circuits in which cells are given a choice
between different competing chemo-attractants allow the analysis of the
decisions those cells make. In another, a steep gradient over less than 100
µm is generated by diffusion between two laminar streams as they flow through
a conduit (width 500 µm, height 50 µm); bacterial cells (Pseudomonas
Aeruginosa) growing in the conduit then migrate over glass towards an
antibiotic. Finally, circuits with fluid-walls are built within wells of
96-well plates, to demonstrate that this technology can be seamlessly
incorporated into standard high-throughput workflows based on microplates.
All these circuits are built in minutes on virgin Petri dishes or standard
plastics. The fluid walls allow direct access to any part of the circuit,
they can even be reconfigured during the experiment, and cells can be
recovered through them at any stage for analysis.
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MOLECULAR LIBRARIES
Track Chairs: Andrew Alt, Ph.D., University of Michigan (USA) and Guy
Breitenbucher, Ph.D., University of California San Francisco (USA)
SMALL MOLECULE LIBRARIES
Session Chair: Guy Breitenbucher, Ph.D., University of California San Francisco
(USA)
* Integrated Phenotypic Screening and Chemical Proteomics to Discover Druggable
Immunomodulatory Pathways
Ekaterina Vinogradova, Scripps Research
Modern human genetics has underscored the important role that the immune
system plays in many human diseases ranging from autoimmunity to
neurodegeneration to cancer. Nonetheless, chemical probes are still lacking
for many immunologically relevant proteins and protein classes. We have
applied an integrated phenotypic screening and chemical proteomic strategy to
globally map the druggable proteome of human immune cells. Leveraging
extensive past knowledge on the special capacity of cysteine-reactive
small-molecule electrophiles to perturb immune system function, we have
profiled this class of compounds against thousands of cysteines in primary
human immune cells and will present compelling evidence that this strategy
has already identified hit compounds for diverse classes of proteins with
genetic links to human immune disorders.
* Doubling Down: Betting on the success of HTS & DEL libraries in parallel
David Lancia, FORMA Therapeutics
High-throughput screening (HTS) libraries and DNA-encoded libraries (DELs)
are two key repositories from which active hit compounds can be identified.
FORMA has implemented a screening paradigm that enables HTS and DEL in
parallel to enhance the likelihood of discovering hits for a particular
target. Utilizing both methodologies in parallel allows us to thoroughly
sample an expanded chemical space compared to either individually as well as
evaluate potentially unexpected mechanisms of action (MOA) for each target.
We will present our current success using the combined approach as well as a
retrospective analysis of how expanded chemical space and novel MOAs could
have further enhanced our past success delivering lead compounds.
* Automated Chemistry: From an Idea to Reality
Michael Kossenjans, AstraZeneca
The discovery of bioactive small molecules is generally driven via iterative
design-make-purify-test cycles. Automation is nowadays routinely used at the
purify and test stage of these cycles but still very rarely at the design and
make a stage. However, recent advances in areas such as
microfluidics-assisted and batch chemical synthesis as well as AI systems
that improve a design hypothesis through feedback analysis, are now providing
a basis for the introduction of greater automation into all aspects of this
process.
Here, we describe recent progress we have made with the build of a fully
automated synthesis platform comprising all aspects of the make-purify
workflow. A variety of chemistry transformations have been established on the
platform allowing not only the rapid synthesis of compound libraries but also
complex molecules via multistep sequences. The value and impact of our
platform is illustrated in the context of specific case studies from the
early phase drug discovery.
We also consider the longer-term goal of realizing the fully autonomous
discovery of bioactive small molecules through the integration of our
automated synthesis platform with automated design and testing.
* Library Of Compounds with Really Annoying Pharmacology (LOCRAP)
Jarrod Walsh, AstraZeneca
False positive results have long been the bane of High Throughput Screening
(HTS) campaigns. Depending on the compound library tested, the target itself
and the assay system employed these have been estimated to account for
enrichments of up to 95 % in hit outputs. Many sources of undesirable hits
exist whether they be technology artifacts, redox cycling compounds,
inhibitors of coupled enzyme systems or any other from a myriad of
mechanisms. One strategy to cope has been the development of so called
‘nuisance compound’ sets. Over the past decade numerous pharmaceutical
companies acting in isolation, including AstraZeneca, have generated their
versions. Whilst the rationale, composition, source and application of these
decks have varied between organizations the end goal has remained constant.
Each group has aimed to either minimize the prevalence of undesirable actives
by optimizing assay design or build bespoke triage cascades capable of
identifying them. This presentation details the process by which the
AstraZeneca set was established and shows the impact it’s had on drug
discovery projects. We explore how it differs from those created by some of
our peers and finally introduce a new cross industry and academia initiative
called LOCRAP. This Library Of Compounds with Really Annoying Pharmacology
(LOCRAP) is a collaboration between AstraZeneca, Eli Lilly, Novartis, Pfizer,
Broad Institute, NCATS and lead academics in the area Jonathan Baell (Monash
University) and Mike Walters (University of Minnesota). By pooling our
collective knowledge, the intention is to design and deliver an industry
standard collection that will be available to all through a third-party
commercial partner. This new set will cover multiple classes of problematic
compounds and contain thoroughly validated and well-annotated examples. We’ll
discuss how this has been achieved and what classes are currently included.
We are actively seeking contributors with ideas on compounds to include or to
act as beta-testing supporters once the collection is available. We hope to
make the tools and resources available to large pharmaceutical companies an
option for any organization interested in drug discovery no matter how large
or small. From this arises the aspiration to globally improve the quality of
assays employed for hit identification and subsequently success rates for
discovery campaigns.
DNA-ENCODED LIBRARIES
Session Chair: Martin Matzuk, M.D., Ph.D., Baylor College of Medicine (USA)
* Exploring Reliable and Cost-Effective DNA-Encoded Library Approaches for
Developing Active Compounds
Raphael Franzini, University of Utah
Tagging combinatorial libraries with DNA barcodes allows using a simple
affinity selection protocol to rapidly identify protein binders. A primary
challenge with such DNA-encoded libraries (DELs) is how to design them to
provide the effective screening productivity needed for the routine discovery
of developable hits. The predominantly pursued approach is to make platforms
of very large libraries of chemically complex compounds. While many success
stories have proven the validity of this paradigm, it is unclear whether such
DELs compare favorably to competing technologies with regard to
return-on-investment. Moreover, the often heterogeneous synthesis yields of
very large libraries and undersampling of DNA-barcodes impedes effective hit
triaging. The cost of producing large DEL platforms and identifying hits from
screening data is completely prohibitive for laboratories with limited
resources. We, therefore, explore alternative library designs to find active
compounds at lower DEL synthesis and lead-development costs. We custom-design
DELs for specific target classes, and early studies have demonstrated that
such libraries provide hits rapidly and economically. For example, a small
and chemically simple DEL targeting NAD+-binding sites provided potent and
target-selective hits for ADP-ribosyltransferases. Possible strategies for
advancing early screening hits from such chemically simple libraries will be
discussed.
* Drug Discovery with DNA-Encoded Chemical Libraries
John Faver, Baylor College of Medicine
DNA-Encoded chemical Libraries (DEL) enable efficient screening of billions
of drug-like small molecules for binding affinity to protein targets. With
DEL, products of combinatorial chemical synthesis can be screened as a single
mixture, because each compound is covalently linked to a DNA segment with a
known identifying sequence. Affinity selection experiments are conducted to
isolate small molecules that bind to protein targets under specific
conditions, and DNA sequencing is used to identify binders and quantify
enrichment. We have developed a DEL synthesis and screening platform in the
Center for Drug Discovery at Baylor College of Medicine which utilizes novel
on-DNA chemistries to generate both general and target-specific libraries.
These libraries have produced hit series with robust structure-activity
relationships for multiple target families. We have also developed enhanced
data analysis strategies that allow for quantitative comparisons of
enrichment from multiple screens, providing information such as target
selectivity, locations of binding sites, and relative binding affinities.
These strategies led us to the swift discovery of potent and selective hit
compounds for a variety of targets with little additional medicinal chemistry
optimization.
* Off-DNA DNA Encoded Library Affinity Screening
Amber Hackler, Scripps Research
DNA-encoded library (DEL) technology is emerging as a key element of the
small molecule discovery toolbox. DELs are highly diverse collections of
combinatorially synthesized small molecules (~300-800 Da) attached to very
large encoding DNA molecules. During affinity selection, the DNA tag can
participate in the binding interaction, leading to false positive results and
confounding the investigation of nucleic acid-binding targets (e.g.
polymerases, transcription factors). An ideal affinity screen would only
interrogate the library member for binding. Here, we use solid-phase DELs and
microfluidic screening to separate each DEL member from its encoding tag and
detect target binding using laser-induced fluorescence polarization (FP). DEL
beads and an FP probe (dye-labeled ligand) are encapsulated in water-in-oil
emulsion droplets containing the macromolecular target. Inside the droplet,
the DEL member is photochemically cleaved from the DNA-encoded bead and
laser-induced FP is measured. If the photocleaved library member competes
with the probe for target binding, the probe emission is relatively
depolarized, triggering electrokinetic droplet sorting and collection for
follow up DNA sequencing. We prototyped this screening mode using the
receptor tyrosine kinase (RTK) discoidin domain receptor 1 (DDR1), which is
overexpressed in many cancers (e.g., leukemia, brain). A fluorescein-labeled
DDR1 ligand (discovered in a previous affinity-based DEL screen) was used to
build the droplet-scale competition binding assay. The FP signal difference
between droplets containing either DDR1 or DDR1 and unlabeled competitor (20
µM) resulted in a Z’ of 0.58. After confirming assay robustness, a 67,100
member solid-phase DEL of drug-like small molecules was screened for ligands
of DDR1 using the droplet-scale competition binding assay. Of the
high-priority hit structures, several known RTK inhibitor pharmacophores were
identified, including azaindole- and quinazoline-containing monomers. Off-DNA
DEL affinity screening is amenable to screening in cell lysate and more
complex affinity-based interrogations, such as interactome perturbation, in
addition to providing an avenue to conduct mechanism-based screening using
DEL.
* DEL out of Water
Philip Dawson, Scripps Research
The structural diversity of DNA Encoded Libraries has been limited since the
hydrophilic, unprotected nature of the DNA tag severely limits the repertoire
of compatible chemical reactions. Rather than pursuing the optimization of
individual synthetic organic reactions for water compatibility, we reasoned
that a general strategy for transferring DNA-substrates into organic solvents
could significantly expand the structural diversity explored by DEL.
Reversible absorption of macromolecules to a solid support (RASS) has
facilitated peptide and protein modification, enabling the use of anhydrous
solvents and multistep synthetic procedures. This RASS strategy was adapted
for DEL through a polystyrene based, quaternary ammonium resin. Adsorption of
DNA headpiece substrates to this resin was found to facilitate transfer to
organic solvents such as DMA, THF, and CH2Cl2. This RASS approach for DEL has
enabled the development of Ni mediated carbon-carbon (C(sp2)-C(sp3)) and
carbon-heteroatom (C-N, C-S, C-P) cross couplings with broad substrate scope
and with excellent DNA compatibility. The immobilization of the DNA has also
facilitated the use of electrochemical transformations. This expanded scope
of reaction conditions compatible with DEL library generation has the promise
to contribute to the generation of conformationally diverse scaffolds with
drug-like properties.
CHEMISTRY AI
Session Chair: Gerard Rosse, Ph.D., Dart Neuroscience (USA)
* De Novo Drug Design with Chemistry-Savvy Machine Intelligence
Gisbert Schneider, ETH Zurich
Chemical creativity in the design of synthetic chemical entities with
druglike properties has been the domain of medicinal chemists. At the same
time, constructive machine learning models have been shown to autonomously
sample drug-like molecules from chemical space without the need for explicit
design rules. A machine learning method that combines a rule-based approach
with a machine learning model was trained on synthetic routes described in
chemical patent literature. This unique combination enables a balance between
ligand-similarity based generation of innovative compounds by scaffold
hopping and forward-synthetic feasibility of the designs. Prospective results
demonstrate the capability of this hybrid machine learning model to capture
implicit chemical knowledge from chemical reaction data and suggest feasible
syntheses of new chemical matter. We will present various applications of
molecular de novo design with machine intelligence, and discuss the
advantages and limitations of these design concepts.
Button, A., Merk, D., Hiss, J. A., Schneider, G. Nat. Mach. Intell. 2019, 1,
307–315.
Schneider, G. Nat. Mach. Intell. 2019, 1, 128–130.
Schneider, G., Clark, D. Angew. Chem. Int. Ed. 2019, 58, 10792–10803.
Schneider, G. Nat. Rev. Drug Discov. 2018, 17, 97–113.
* Discovering Multi-Target Pharmacology of Drugs and Drug Candidates by 3D
Target Models and Machine Learning
Ruben Abagyan, University of California, San Diego
Small molecule therapeutics have an extensive, and only partially known,
multi-target pharmacology that defines both their beneficial and adverse
effects. We have characterized these networks for all cancer drugs.
Furthermore, a team of researchers at Molsoft and UCSD developed a set of
thousands of models in which 3D models are combined with the machine-learning
layer to predict the activity of any chemical against protein targets
included in this panel. The models can be used to discover targets of any
known drug or drug candidate, search for compounds with specific multi-target
profile, repurpose drugs for a new indication or disease, or identify
potential liabilities. Applications of a multi-profile approach are
presented.
* Applying Artificial Intelligence and Machine Learning Techniques and Cross
Platform Communication to Enable Informatics Driven Experimentation
Carleen Klumpp-Thomas, NIH/NCATS
Over the past decade, there has been a shift away from the traditional static
method of performing high throughput screening (HTS) against large chemical
libraries where experiments are designed in advance, executed and then the
generated data is processed. Traditionally, this results in additional rounds
of biological validation, testing and lead compound follow up for medicinal
chemistry. More recently there has been a movement to focus instead on an
increased number of targeted chemical libraries and smaller initial HTS
experiments which can be run more dynamically with the resultant data
processed automatically and in near real time to initiate new biological
experimentation and even automated chemical synthesis on the fly. To make
this possible it is necessary to have an underlying software and messaging
infrastructure that can connect informatics platforms that utilize Artificial
Intelligence and Machine Learning techniques to design experiments that can
then be transferred to physical systems to initiate new experiments or small
molecule synthesis. NCATS has developed such a platform with the initial
validation being used to perform dynamic assay optimization but which is
extensible to far more complex experimentation types to move beyond
automation and instead towards autonomy.
* Case Studies in AI-Driven Drug Design
John Griffin, Numerate, Inc.
Breakthroughs in machine learning theory and practice, coupled with ready
access to cloud based supercomputing resources and ever-increasing amounts of
experimental data, are enabling truly AI centric processes for small molecule
drug design wherein predictive models successfully substitute for laboratory
assays throughout the Discovery critical path. This presentation will
describe how diverse applications of machine learning techniques, ranging
from multidimensional and multitask boosting to deep neural networks, can
extract accurate, scaffold independent, ligand based predictive models for
important phenomena: target binding, functional activity, selectivity,
PK/ADME properties, and toxicity. Applications of these models will be
illustrated with examples from therapeutic programs and discussed in terms of
their potential to enhance success/reduce attrition in drug discovery.
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PRECISION MEDICINE TECHNOLOGIES
Track Chairs: Kristen Brennand, Ph.D., Mount Sinai School of Medicine (USA) and
John Joslin, Ph.D., Genomics Institute of the Novartis Research Foundation (GNF)
(USA)
TOOLS TO RESOLVE DISEASE COMPLEXITY
Session Chair: John Joslin, The Genomics Institute of the Novartis Research
Foundation (USA)
* Toward Precision Medicines for Rare Diseases
Anna Greka, BWH/Harvard/Broad
Intracellular accumulation of misfolded proteins causes toxic
proteinopathies, diseases without targeted therapies. Mucin 1 kidney disease
(MKD) results from a frameshift mutation in the MUC1 gene (MUC1-fs). Here, we
show that MKD is a toxic proteinopathy.
Intracellular MUC1-fs accumulation activated the ATF6 unfolded protein
response (UPR) branch. We identified BRD4780, a small molecule that clears
MUC1-fs from patient cells, from kidneys of knockin mice and from patient
kidney organoids.
MUC1-fs is trapped in TMED9 cargo receptor-containing vesicles of the early
secretory pathway. BRD4780 binds TMED9, releases MUC1-fs, and reroutes it for
lysosomal degradation, an effect phenocopied by TMED9 deletion. Our findings
reveal BRD4780 as a promising lead for the treatment of MKD and other toxic
proteinopathies. Generally, we elucidate a novel mechanism for the entrapment
of misfolded proteins by cargo receptors and a strategy for their release and
anterograde trafficking to the lysosome.
* A Hydrogel-Enabled 3D Liver Fibrosis Model for High-Throughput Phenotypic
Screening Applications
Zhixiang Tong, GNF/NIBR
Hepatic stellate cell (HSC) is one of the major cell types responsible for
the progression of liver fibrosis. Inhibition of HSC activation (i.e.
transdifferentiation from an inactive/quiescent state to a myofibroblast-like
state) represents a compelling strategy for resolving liver fibrosis.
Conventional 2D HSC culture cannot recapitulate the in-vivo 3D cell-ECM
interactions and often causes undesirable cell activation due to the
intrinsic mechanical properties of the plastic substrates. Hydrogel has
emerged as a powerful tool for modeling the 3D cellular microenvironment in
vitro, largely due to its chemical and physical versatility. To this end, GNF
team has developed a comprehensive toolbox comprised of a variety of
polyethylene, hyaluronic acid and gelatin-based hydrogel derivatives.
Specifically for modeling HSC activation, we’ve identified a gelatin
methacrylate (GelMA)-based hydrogel formulation that preserves the quiescent
state of HSCs much better than 2D culture on tissue culture polystyrene, and
precisely controls the pro-fibrotic signal (i.e. TGFβ) induced activation in
3D. Such control offers optimal TGFβ induced response window superior to that
of standard 2D culture, leading to robust assay performance in a highly
miniaturized format. By leveraging GNF’s proprietary engineering/automation
technologies, the 3D culture can be efficiently implemented in a 1536-well
plate format with minimal inter-/intra-plate variations. Using a tool GNF
compound set (with ~1800 compounds), our pilot high-content imaging (HCI)
based phenotypic screen reveals an assay robust Z’ factor over 0.45 and a
hit-picking rate ~3%. Overall, our automation-friendly, hydrogel-enabled 3D
HSC assay can be readily scaled up either for primary screen or lead
profiling applications, and the novel screening platform shown herein could
offer broad utility to identifying novel targets or therapeutic modalities
for diseases beyond liver fibrosis.
* Development of Colorectal Cancer Patient-Derived Organoid-Fibroblast Models
Suitable for Drug Testing
Eliza Fong, National University of Singapore
The advent of patient-derived organoid (PDO) technologies has greatly
expanded the toolbox for drug discovery and personalized drug screening for
several cancer types. While PDO models more closely represent the molecular
characteristics and heterogeneity of patient tumors than traditional
immortalized cancer cell lines, they are inherently limited in their ability
to reflect the tumor microenvironment in vitro as they comprise exclusively
of epithelial cells. The lack of stromal cells in PDO models, such as
cancer-associated fibroblasts (CAFs), poses a major problem as these tumor
microenvironmental components contribute to the various hallmarks of cancer
and response to therapy. Particularly for colorectal cancer, CAFs comprise
the majority of the tumor microenvironment and play important roles in cancer
development and progression, from the regulation of cancer cell proliferation
and stem cell maintenance to drug resistance. In this study, we addressed
this problem by establishing in vitro conditions that robustly enable the
co-culture of CRC PDO with patient-derived CAFs for controlled mechanistic
studies and drug testing. We report the development of an engineered tumor
microenvironment consisting of CRC PDO encapsulated within a well-defined
three-dimensional (3D) hyaluronan-gelatin hydrogel and co-cultured with
patient-derived CAFs. Basement membrane extracts (e.g. Matrigel)
conventionally used for PDO culture exhibit batch-to-batch variability.
Considering that the CRC extracellular matrix is high in hyaluronan and
collagen I and that hyaluronan-based matrices are conducive for the culture
of various human cancers, we hypothesized that hyaluronan-gelatin hydrogels
may serve as a suitable alternative 3D matrix to support the culture of CRC
PDO and CAFs. Through RNA- and whole-exome sequencing, we first show that
these hydrogels are capable of maintaining the molecular characteristics of
the original patient tumors in the cultured CRC PDO. Further, based on our
findings that standard PDO culture medium poorly supports CAF viability, we
developed a new co-culture strategy that robustly maintains the viability of
both CRC PDO and CAFs for at least a week in culture. We found that in the
absence of any growth supplements added to the co-culture, CAFs were able to
maintain the growth of the cultured CRC PDO in the hydrogels. Lastly, we
demonstrate that these CRC PDO-CAFs models are suitable for evaluating
standard-of-care drugs, making them potentially very useful for realizing
personalized cancer medicine.
* Liquid Biopsy as a Tool in Ant-Cancer Drug Screening for Personalized Therapy
Decision and Drug Discovery
Kamran Honarnejad, Fraunhofer ITEM
The use of circulating tumor cells (CTCs) isolated from liquid biopsy are
already used to predict disease progression and survival in metastatic
patients. However, the lack of robust drug screening assays has hampered
their application in monitoring patient drug response/resistance and
personalized therapy decision.
We have developed a workflow to isolate tumor cells from pleural effusion and
malignant ascites samples from metastatic lung and breast cancer patients and
subjected them to medium scale drug screens against approved anticancer drug
libraries. This approach allows the realization of personalized treatment
decisions within less than a week by evaluating drug responses directly in
patient-derived tumor cells obtained from liquid biopsy.
In patients with no pleural effusion or malignant ascites, we have
established another workflow to isolate viable CTCs from peripheral blood of
metastatic patients, from which we have generated 2D and 3D in vitro
(spheroids and organoids) and in vivo (CTC-derived xenografts) models.
Particularly, drug screens on CTC-derived organoids were feasible within
therapeutic timeframes which can potentially influence personalized treatment
strategy. Drug responses from the screen mirrored patients’ drug resistance
and revealed promising candidates for the treatment of individual patients.
Beyond that, high-throughput drug screens in CTC-derived preclinical models
closely mimicking patients' settings enable discovery, repurposing and
development of more efficient cancer therapeutics.
Integration of drug screening of liquid biopsy-derived tumor cells
constitutes a powerful tool to better improve personalized treatment
strategies and discovery for metastastic patients.
APPLICATIONS OF SINGLE CELL ANALYSIS TO DISEASE STUDIES
Session Chair: Kevin Eggan, Ph.D., Harvard University (USA)
* Villages in a Dish: Scaling the use of human cell models to detect
drug-genotype interactions
Kevin Eggan, Harvard University
A maturing application of reprogramming and stem cell technologies is their
application to understanding how genetic variation that underlies disease
risk impinge the function of affected cell types. However, a major limitation
of this approach has been the number of patients and genetic variants that
can be reasonably analyzed. I will describe a new strategy we have developed
that allows us to simultaneously measure phenotypes in cell types derived
from as many as 100 individuals in a single tissue culture well. These
approaches, we call “Dropulation Genetics” and “Census sequencing” not only
have allowed us to probe how genotype underlies phenotype at previously
impractical scales, they have also provided a remarkable improvement in
sensitivity and assay reproducibility. I will describe practical application
of these approaches in psychiatry, neuromuscular disease and susceptibility
to infectious agents.
* Developing Epileptic Encephalopathy Models Using iPSC-Based Technologies
Evangelos Kiskinis, Northwestern University Feinberg School of Medicine
Mutations in KCNQ2, which encodes a pore-forming K+channel subunit
responsible for neuronal M-current, cause neonatal epileptic encephalopathy,
a complex disorder presenting with severe early-onset seizures and impaired
neurodevelopment. The condition is exceptionally difficult to treat,
partially because the effects of KCNQ2mutations on the development and
function of human neurons are unknown. Here, we used induced pluripotent stem
cells and gene editing to establish a disease model and measured the
functional properties of patient-derived neurons using electrophysiological
and optical approaches at single-cell resolution. We find that while
patient-derived excitatory neurons exhibit reduced M-current early, they
develop intrinsic and network hyperexcitability progressively. This
hyperexcitability is associated with faster action potential repolarization,
larger afterhyperpolarization, and a functional enhancement of Ca2+-activated
K+(BK and SK) channels. These properties facilitate a burst-suppression
firing pattern that is reminiscent of the interictal electroencephalography
pattern in patients. Importantly, we were able to phenocopy these
excitability features in control neurons only by chronic but not acute
pharmacological inhibition of M-current. Our findings suggest that
dyshomeostatic mechanisms compound KCNQ2 loss-of-function and lead to
alterations in the neurodevelopmental trajectory of patient-derived neurons.
Our work has therapeutic implications in explaining why KCNQ2 agonists are
not beneficial unless started at an early disease stage.
* Application of Microwell Plates in Single-Cell Analysis of T Cell-Mediated
Tumor Cell Killing for High-Throughput Pharmacological Analyses
Katherine Kozak, Genentech
The ability to observe and quantitate T cell-mediated tumor cell killing at
the individual cell level is critical for understanding the mechanism of
immune activation and exhaustion to assist therapeutic designs. To acquire a
large amount of single-cell data for statistical analysis, images of cells in
micro-gridded chambers (sub-wells) within a standard microwell are captured
to analyze single-cell interactions. The current available gridded platforms,
manual microscopy imaging or standard automated image cytometer methods,
however, are time-consuming. In addition, the analysis software is typically
used for custom-made sub-wells constructed with Polydimethylsiloxane. In this
work, we reported a high-throughput single T cell killing assay utilizing the
Celigo Image Cytometer and Elplasia SQ plates that convert each 384-well into
86,400 sub-wells. In this assay, both T cells and tumor cells were seeded
with varying densities, resulting in 1 to 100 cells in each sub-well, as well
as varying T cell activation reagent. The plate was scanned immediately after
cell seeding at t = 0, 4, 22, 46, 68, and 168 hours, where the number of
cells were tracked in each individual sub-well over time for each cell type.
The image cytometer was able to rapidly acquire and analyze images at 1
µm2/pixel. The images and results were exported into a custom program to
determine the proper sub-well location of the segmented cells to allow
separate tracking of small groups of tumor and T cells. This approach gave
the image cytometry method greater capability in resolving subpopulations
within the biological sample, resulting in more detail on the cytotoxic
killing as a function of cell demographics in the tumor microenvironment.
* Microfluidic Platform for Screening of Antibiotic Susceptibility at the
Single-Cell Level
Witold Postek, Institute of Physical Chemistry of the Polish Academy of
Sciences
The inoculum effect describes a dependency between the minimum inhibitory
concentration (MIC) of an antibiotic and the concentration of bacteria in the
sample: the less the bacteria, the less concentrated antibiotic is needed to
stop their growth. MIC for populations consisting of a single cell is known
as single-cell MIC (scMIC). scMIC is important for public health, as the
presence of antibiotics at a concentration of scMIC in a large population of
bacteria drives the evolutionary pressure towards resistant strains1, and the
inoculum effect is a source of errors in MIC assessment in the clinic.
However, efficient assessment of scMIC values for large numbers of cells has
not been shown until now.
Here, we demonstrate a method of determining scMIC values in hundreds of
replications per experimental run, and we achieve this without optical
labeling of the reaction conditions. We generate a series of emulsions of
different concentrations of antibiotics at a step emulsifier2. We encapsulate
single cells in each emulsion droplet due to stochastic confinement. Each
emulsion is separated from the others by being encapsulated in a third
immiscible phase and transferred to a piece of tubing, where all the
separated emulsions can be incubated to provide for growth of bacteria. We
measured the scMIC value of cefotaxime in E. coli for hundreds of cells,
recording the inoculum effect when we used higher initial cell densities and
observing the distribution of resistance level in a population of bacteria.
Currently, we use our platform to generate up to 20 separate emulsions with
different and known reaction conditions of ca. 2000 droplets each with
immediate plans to upscale. In the near future we plan to screen for
interactions of antibiotics in relation to inoculum effect, including the
measurements at the single-cell level.
The described method might be useful in the field of antibiotic resistance at
a single-cell level, which is unbiased by the inoculum density. A
microfluidic method of screening multiple chemical conditions in emulsions
without labeling can be also deployed in other fields of research, wherever
several reaction conditions should be replicated hundreds or thousands of
times. For now3, to establish whether the bacteria grow or not, we detect
fluorescence from fluorescent proteins produced by bacteria, but we are
currently working on an add-on module to detect growth without labelling. We
are also integrating our system with optical detection of moving droplets to
automate the liquid handling protocol.
1. T. Artemova, Y. Gerardin, C. Dudley, N. M. Vega and J. Gore, Mol. Syst.
Biol., 2015, 11, 822.
2. W. Postek, T. S. Kaminski and P. Garstecki, Lab Chip, 2017, 17, 1323–1331.
3. W. Postek, P. Gargulinski, O. Scheler, T. S. Kaminski and P. Garstecki,
Lab Chip, 2018, 18, 3668–3677.
SYSTEMATIC DATA-BASED APPROACHES FOR PRECISION MEDICINE
Session Chair: Kelly Frazer, Ph.D., University of California, San Diego
* Overlap of Fetal-Specific Cardiac Regulatory Variants and GWAS Lead Variants
Supports Fetal Origins of Cardiovascular Disease
Kelly Frazer, University of California, San Diego
It has been hypothesized that many disease-causing variants exert their
effects during development, rather than in adult cells. However, it is
difficult to identify these variants and their effects as they could act in
multiple different cell types, and there was a recent moratorium on research
using fetal tissue. We recently established that iPSC-derived cardiovascular
progenitor cells (CVPCs) are fetal-like, and can be utilized to identify
cardiac regulatory variants. Here, we leveraged this system to identify fetal
cell-type-specific eQTLs that underlie GWAS signals for adult cardiac
diseases. We started by characterizing the differentiation of iPSCs into
iPSC-CVPCs via scRNA-seq on eight samples, and found they were comprised of
two cardiac cell types: cardiomyocytes (CMs) and epicardium derived cells
(EPDCs). Next, we derived 180 iPSC-CVPCs, performed bulk RNA-seq, and used
the scRNA-seq expression signatures to deconvolute and determine the relative
proportions of CMs and EPDCs in each sample. We integrated these data with
WGS and identified cell type-specific eQTLs (associated with only CMs or
EPDCs). We next identified fetal-specific eQTLs by colocalizing our iPSC-CVPC
eQTLs with all GTEx adult cardiac tissue eQTLs. To identify variants
underlying the fetal origin of complex adult cardiac traits, we colocalized
these fetal-specific eQTLs with cardiac traits GWAS summary statistics (pulse
rate and myocardial infarction) and found 10 fetal-specific eGenes, including
CLPTM1 which has previously been associated with congenital malformations (as
expected for a fetal-acting gene). Our findings provide genetic evidence
supporting the fetal origin of cardiovascular disease and show that
iPSC-derived tissues can be leveraged to study the fetal origins of diseases
in relevant cell-types.
* Presentation Title TBD
Paul de Bakker, Vertex
* CURATE.AI-Enabled Personalised Dosing for Multiple Myeloma
Agata Blasiak, National University of Singapore
Standard of care therapy for various indications, including multiple myeloma
(MM), is a combination of up to 4 drugs. Precision medicine has emerged as a
game-changing approach for selecting drug combinations tailored to an
individual to avoid treatment failure in a common case of drug resistance. To
maximize the therapeutic outcome with the identified combination therapy, the
drug dosing strategy should undergo an analogical approach - personalized
dose selection for each drug tailored to an individual. Conventional
approaches - titration, additive drug design, and dose escalation – often
fail to find the optimal doses. Modern approaches - predictive algorithms and
genotypic modeling – require a substantial amount of data and are costly. In
this pilot study, we use CURATE.AI, a disease mechanism-independent and
indication agnostic platform, to create an N-of-1 drug interaction profile
using only the patient’s own data to identify optimized doses. CURATE.AI has
been already clinically validated and has been used to optimize combination
therapy for acute lymphoblastic leukemia, combination therapy for prostate
cancer, liver transplant immunosuppression, and tuberculosis therapy, among
other indications. We applied CURATE.AI to retrospectively analyze medical
dataset in accordance with institutional IRB. As indicated in the medical
records, a patient was given 14 monthly modulated dosages of revlimid and
cyclophosphamide and a constant monthly dosage of dexamethasone. Quadratic
polynomial correlation between the drugs’ dosages and the platelet count - a
clinical indicator of the disease progression - was used to create the
patient-specific CURATE.AI profile, which served as a map to identify drug
dosages within clinically-accepted ranges that would result in an optimum
platelet count. Using CURATE.AI analysis, the platelet count (P(r,c)) was
correlated to revlimid and cyclophosphamide concentrations (r and c,
respectively) by the following function:
P(r,c)=62+4.690r-0.069rc+0.275r2+0.002c2, with R2value of 0.724 and a fitting
correlation of 0.851. The CURATE.AI profile guided that to sustain the
platelet count within the desired range (132-372x109/L), the patient should
be given above 10 mg matched with c below 150 mg, or cabove180 mg matched
with below 15 mg. CURATE.AI is deterministic and does not involve any
prediction or uncertainty of response. In addition, CURATE.AI recommends
doses within clinically-accepted ranges at patient-specific time points to
optimize treatment response for that particular patient. The ability to
identify patient-specific response constants has a paradigm-shifting
potential – combining precision medicine for drug selection with CURATE.AI
for dose selection brings us a step closer to the true realization of
personalized medicine. We have also initiated a clinical trial that uses
CURATE.AI for prospective dosing in MM (Clinicaltrials.gov: NCT03759093).
* Personalizing Digital Therapeutics with CURATE.AI Identified N.1 Profiles
Theodore Kee, National University of Singapore
Digital therapeutics have emerged as an alternative or complementary modality
of treatment to drug-based therapies for various indications, such as
addiction and cognitive decline. Similar to conventional drug dosing, digital
therapies often rely upon either fixed, or step-wise increased difficulty.
Those approaches lack the flexibility and the ability to personalize the
treatment to the individual. URATE.AI - a clinically validated deterministic
optimization artificial intelligence (AI) platform that has already been used
to modulate optimized dosing regimens for indications ranging from oncology
(solid tumor/hematologic) to infectious diseases (HIV/TB) and
immunosuppression (liver). In this prospective study, CURATE.AI identified
individualized N-of-1 (N.1) learning trajectory profiles of healthy
volunteers (both sexes, ages 21-40) trained on the Multi-Attribute Task
Battery (MATB). MATB is a flight deck simulator developed by the National
Aeronautics and Space Administration (NASA) and United States Air Force
(USAF). The prospective clinical trial study design is a randomized,
multiphase, parallel three-arm, single-blinded, N-of-1, single-center,
exploratory pilot trial with 1:1:1 allocation approved by NUS Institutional
Review Board (S-17-180) and listed under Clinicaltrials.gov identifier
NCT03832101. For the CURATE.AI arm of the study, five subjects were fluent in
English, had no prior experience with the MATB, and no history of perceptual
or memory deficits, and recruited at Yale-NUS to participate in MATB
simulator experiment sessions, conducted at the Yale-NUS campus. Each subject
underwent a 34-minute MATB training session composed of 17 training and
testing blocks of varying intensity levels (high, medium, low).
Individualized CURATE.AI profiles were calibrated from the individual’s data:
performance scores (RMAN-COMM z-scores from the training blocks), performance
improvement, and training intensity levels. From each individual’s
prospectively obtained data, N.1 learning trajectory profiles were derived
and constructed with CURATE.AI, demonstrating the unique relationship between
performance, training intensity, and performance improvement. Each subject
had a different performance range (-1.24 to 0.70, -1.59 to 1.04, -2.13 to
0.66) and different training intensity levels for optimal performance
improvement. As identified from their CURATE.AI N.1 profiles, high-intensity
training in select participants corresponded with greatest gains in
performance improvement, while low-intensity training was identified for
mediating similar gains in the other subjects. Based upon each individual’s
unique interaction between performance and training intensity, these N.1
learning trajectory profiles provide a means of real-time optimization of
performance improvement by dynamically identifying and modulating the
appropriate training intensities. In this prospective in-human study,
interfacing MATB with CURATE.AI revealed substantial differences between
subjects’ N.1 learning profiles and the correlation between tailored training
intensity on performance improvement. The ability of CURATE.AI to identify
N.1 profiles represents the advancement and utilization of AI to actionably
address challenges encountered in personalized learning and the emerging
field of digital therapeutics.
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