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Podium Abstract Compendium

Podium presentations are organized into 10 educational tracks. Podium abstracts and speaker information are organized first by track and then by session below.

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To view a complete schedule of podium presentations and schedule of events for SLAS2018 and to view speaker bios and photos, please visit the SLAS2018 Event Scheduler.

Advances in Bioanalytics, Biomarkers and Diagnostics

Track Chairs: Melanie Leveridge, GSK and Shaun McLoughlin, Abbvie

Label Free Bioanalytical Techniques In Drug Discovery

Session Chair: Andreas Luippold, Boehringer Ingelheim Pharma GmbH & Co KG

  • MALDI-TOF-MS - A label free technology for high throughput screening
    Frank Buettner, Boehringer-Ingelheim Pharma GmbH & Co.KG

    Mass spectrometry (MS) is an emerging technology for identifying and characterizing molecules that modulate biological targets, offering a label free, direct detection method. This technology enables the application of more physiologically relevant assays and reduces time and costs compared to current classical approaches increasing the efficiency of the drug discovery process.

    In the past, the throughput of MS-based assay technologies was limited, but recent developments in the field of MALDI-TOF-MS devices and spotting technologies substantially increased the ability for miniaturization and speed of such approaches. However, the application of MALDI is based on a matrix-compatible sample preparation step and is limited to a certain space of analytes. This requires the identification of MALDI compatible, physiological relevant assay conditions, as well as development of fast and reproducible liquid handling procedures.

    The talk will shed light on challenges in this process and provides results of this application in high throughput screening projects.

  • Label Free Approaches to Quantify Small Molecule-Receptor Binding
    David McLaren, Merck & Co, Inc.

    Ligand-receptor binding assays are commonly employed to study the thermodynamics and kinetics of receptor-ligand interactions. Conventional binding assays use labeled ligands which can be resource-intensive to prepare and are not always suitable. We have developed label-free LC-MS based assays to quantitate small molecule binding to both soluble and membrane associated proteins. In direct binding mode, the methodology enables rapid assessment of ligand affinity to its molecular target as well as the concentration of the bound ligand. Structure-activity relationships can also be assessed in competition binding mode. This presentation will describe the experimental design, validation and application of equilibrium-based, direct and competition binding assays using LC-MS for bound ligand quantitation, and the utility of the method for assessing binding kinetics.

  • Label Free High-Throughput ESI-MS:A Novel Sampling Interface for ADME and HTS
    Hui Zhang, Pfizer Inc.

    Label-free LC/MS based screening technology is routinely used in pharmaceutical industries for hit discovery and various ADME profiling applications. Although the current analysis speed of less than 30 seconds per sample is quite promising, it still cannot match the throughput provided by plate-reader based HTS platforms. In this study direct injection is coupled with an open-port probe (OPP) for direct sampling into a standard ESI ion source. Screening speeds of <2 seconds-per-sample were demonstrated with high sensitivity (attomole loading), good quantitation capability (>3 orders of magnitude), and broad compound coverage (from small molecule pharmaceuticals to peptides and antibodies).

    The use of a “classic” ESI ion source for MS analysis yielded a perfectly Gaussian-shaped signal peak with baseline width of 0.8 - 1.5 seconds. High sensitivity and reproducibility were demonstrated for this approach, showing linearity over three orders of magnitude, and sensitivity (attomole loading for small molecules, and sub-femtomole loading for intact antibody).  The continuous-flow of carrier solvent for the OPP maintained ionization stability and actively cleaned the entire flow system resulting in no observed carry-over.  The advantages of this integrated system approach were demonstrated with a Drug-Drug Interaction (DDI) assay, where various substrates/metabolites were monitored and compared to conventional analysis.

  • Small molecule direct binding by use of ASMS for target tractability assessment and high throughput hit identification
    Geoff Quinque, GlaxoSmithKline

    Affinity Selection Mass Spectrometry (ASMS), a label free assay that connects a binding event to the accurate mass identity of the ligand involved, is an established HTS triage platform at GSK that has been used to generate hit qualification data on more than 60 targets during the past three years. As part of a paradigm shift to screen novel targets, we are exploring the use of ASMS for hit identification, target tractability assessments and tool compound identification.  The benefits include reduced cycle time through streamlined assay development, and reduced attrition through identification of compounds that directly engage the target protein. A mass-encoded 180,000 compound library has been created for ASMS screening, and is comprised of compounds that represent aspirational chemical space in terms of molecular weight, cLogP and property forecast index. The output of the ASMS platform has been evaluated against existing target-specific biochemical and biophysical data to develop a better methodology that maximizes the identification of biochemically active compounds while minimizing the overall hit rate. Nearly 85% of compounds with known biochemical and/or biophysical activity showed binding to a protein target with our platform. A sub-set of the full library is being used to evaluate target tractability, and has been used to screen 30+ historical targets, with the goal of correlating compound binding to tractability predictions.  Overall, ASMS tractability outcomes align well with Encoded Library Technology (ELT) and HTS tractability observations. From a methods optimization perspective, continued development of the sample preparation protocols and the LC-MS platform are being targeted to maximize sensitivity and increase platform throughput. Furthermore, the development of an end-to-end informatics solution will complement the analytical platform. This presentation will highlight the ASMS platform developed for hit identification and target tractability assessments and illustrate its application of a kinase screening campaign as a proof of concept.

Omics Approaches to Biomarker Analysis

Session Chair: Christina Rau, Cellzome GmbH, a GSK Company

  • A highly-reproducible automated protein sample preparation workflow for quantitative mass spectrometry in plasma or blood
    Jennifer Van Eyk, Cedar Sinai Medical Center

    BACKGROUND. Sample preparation for protein quantification by mass spectrometry requires multiple processing steps including denaturation, reduction, alkylation, protease digestion, and peptide cleanup. Scaling these procedures for the analysis of numerous complex biological samples, such as plasma, can be tedious and time-consuming, as there are many liquid transfer steps and timed reactions where technical variations can be introduced and propagated. Therefore, we have automated this digestion workflow and adapted it to include the preparation of dried blood obtained from remote sampling devices, allowing high throughput analysis of both archived and “real-time” sampling of our pathological surveillance biomarkers. Our pathological surveillance biomarker assay is composed of 72 plasma proteins that screen for 8 pathological signatures. METHODS. We established an automated sample preparation workflow with a total processing time for 96 plasma or blood samples of 5 hours, including a 2-hour incubation with trypsin. Peptide cleanup is accomplished by online diversion during the LC/MS/MS analysis. RESULTS. In a selected reaction monitoring (SRM) assay targeting 6 plasma biomarkers and spiked β-galactosidase, mean intra-day CVs for 5 samples ranged from 5.5%-8.9% for serum and 3.9%-7.2% for plasma, and mean inter-day CVs over 5 days ranged from 5.8%-10.6% for serum and 3.9%-6.0% for plasma. As well for the highly multiplex surveillance biomarker assay, 90% of the transitions from 6 plasma samples repeated on 3 separate days had total CVs below 20%. Similar results were obtained when the workflow was transferred to a second site: 93% of peptides had CVs below 20%. In an analysis of plasma samples from 48 individuals (disease and healthy), the average CVs for spiked β-galactosidase was < 15%. The workflow was adapted for the direct processing of remote blood sampling devices (Neoteryx) and achieved equivalent high performance for spiked β-galactosidase when part of a 10 and 72 protein SRM assays.

  • The human secretome and kidney fibrosis – identification of novel fibroblast biology through exploitation of the human secretomics library.
    Douglas Ross-Thriepland, AstraZeneca

    Diabetic nephropathy is the world’s leading and most rapidly growing cause of end stage renal disease, with up to 40 % of all diabetic patients developing chronic kidney damage – a common manifestation of which is tubulointerstitial fibrosis, driven by overactive fibroblast cells. The human secretomics project is a collaboration between KTH and AstraZeneca to develop methods to purify from cell factories all 6400 human membrane and secreted proteins. The resultant library of highly bioactive molecules will enable exploration of novel biology and identification of tractable protein targets for drug discovery. We have for the first time used a 700 set secretomics library as a novel modality to probe the biology of the causative cell type in chronic kidney disease, fibroblasts. By building a high content imaging assay to follow the phenotypic fate of primary human kidney fibroblasts we have screened the secretomics library alongside a standard small molecule campaign. This innovative use of the human secretome library enabled us to identify novel regulators of fibroblast biology not previously identified, and whose identification will now enable strategies to develop next generation biological treatments that will halt or slowdown disease progression in patients with chronic kidney disease.

  • Integrating high resolution mass spectrometry with cheminformatics for standardized, routine non-targeted metabolomics
    Oliver Fiehn, UC Davis

    Over the past 20 years, metabolomics has evolved into using either multi-targeted assays, usually with nominal mass resolution spectrometers, or non-targeted approaches with high resolution mass spectrometry. We will here show that how to merge targeted approaches with high quality non-targeted discovery metabolomics. We will highlight the importance of advanced, open access data processing, the proper use of quality controls and internal standards, and full reporting of raw data as well as result data.

    At the NIH West Coast Metabolomics Center, we use 17 mass spectrometers in the central facility for providing data, informatics services and collaborative research for over 400 projects and more than 25,000 samples per year. These services include commercial assays for plasma analytics, the p180 kit, in addition to steroid, bile acid and oxylipin assays for more than 100 target compounds. Most projects, however, use our three integrated non-targeted metabolomics assays: primary metabolism for up to 200 identified compounds per study using GC-TOF MS, complex lipids for more than 600 identified lipids per study using high resolution liquid chromatography / tandem mass spectrometry and more than 150 identified compounds per study for biogenic amines using hydrophilic interaction chromatography/ high resolution mass spectrometry.

    We use standardized data processing in free-access MS-DIAL 2.0 software that is far superior standard solutions with respect to data deconvolution, compound identification and false positive/false negative peak detection. This software is now integrated with MS-FINDER 2.0 software for predicting and annotating spectra of biomarkers with unknown chemical structures. Both programs work excellently for high resolution GC-MS and LC-MS data. In addition, we harness the power of legacy data from more than 2,000 projects we have acquired since 2004 that is available to the biomedical and biological research community at large, the BinVestigate interface to our BinBase metabolome database. We showcase how the integrated use of these resources identified novel epimetabolites in cancer metabolism, both on a prospective cohort scale (in lung cancer) and as new epitranscriptome metabolites from modified RNA molecules (in a range of cancers except for liver cancer).

  • Combining 3D liver microtissues with lipid loading and lipidomics as a screening model for non-alcoholic fatty liver disease
    Patrick Guye, InSphero AG

    Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease in the world, affecting all racial, ethnic, and age groups without sex predilection. NAFLD is characterized by an excessive accumulation of lipids in hepatocytes (steatosis) and in combination with inflammatory processes (NASH) progressively develops into end stage liver disease, making it a major clinical concern.

    Here, we describe a novel, screening-compatible human liver microtissue in vitro model for studying the etiology of steatosis and therapeutic strategies in a 3D configuration. The steatosis model is based on incubation with Oleate/Palmitate and displays a distinct and quantifiable accumulation of macro- and/or microvesicular lipid droplets within the hepatocytes. It maintains prolonged viability and liver-specific functionality in comparison to 2D cultures and can be produced in a 96-well SBS-compatible format.

    Lipid accumulation was studied using fluorescent imaging followed by algorithmic analysis as well as by a novel LC/MS method for a full lipidomics analysis using unsupervised learning techniques.

    Oleate as well as Palmitate induced a time- and concentration-dependent lipid accumulation, preferentially causing microvesicular (Oleate) or macrovesicular (Palmitate) steatosis. The highest lipid accumulation was observed after 7 days of Oleate treatment. The combination of both fatty acids in a physiological relevant 2:1 (Oleate:Palmitate) ratio resulted in a mixed phenotype. Lipidomics analysis confirmed increased concentrations of di- (18:1/18:1) and triglycerides (18:1/18:1/18:1) in microtissues upon treatment with Oleate or Oleate/Palmitate compared to medium and BSA control. In microtissues treated with Palmitate, increased concentrations of triglycerides (14:0/16:0/16:0) were observed. Lipidome principal component analysis allow for a clear distinction between the different treatment groups by corresponding clustering.

    This 3D human liver microtissue model is particularly well-suited to study the formation as well as the prevention of steatosis by whole lipidome profiling, and is highly amenable for running comparisons to clinical samples. Moving beyond steatosis, the immune-competent status of these microtissues may even serve as starting point to study the etiology of NASH when combined with inflammatory stimuli.

Target and Mechanism Identification After Phenotypic Screens

Session Chair: Shaun McLoughlin, AbbVie

  • Hit Triage and Mechanism Validation for Phenotypic Screening: Considerations and Strategies
    Fabien Vincent, Pfizer

    Phenotypic drug discovery approaches can positively affect the translation of preclinical findings to patients. However, significant differences exist between target-based and phenotypic screening, prompting a need to re-assess our strategies and processes to most effectively prosecute phenotypic projects. First, phenotypic screens have dual goals of delivering both efficacious compound series as well as novel molecular targets for diseases of interest whereas only desirable chemical matter is sought for target screens. Second, while confirming binding and functional impact is sufficient for target screening hits, the situation is noticeably more complex for phenotypic screening hits. Here, hits acting through a number of (largely unknown) mechanisms in a large and often poorly understood biological space need to be triaged to differentiate desirable mechanisms from undesirable ones.

    Given these fundamental differences, the hit triage and validation process was critically re-evaluated in light of the unique characteristics of phenotypic screening. Key considerations and specific strategies will be shared and exemplified by in house and literature case studies.

  • Genome-wide CRISPR-mediated Gene Disruption Presents a Shortcut to Acquired Resistance that Reveals Small Molecule Mechanism of Action
    Jon Oyer, Abbvie

    Phenotypic screening in small molecule drug discovery presents the opportunity to discover novel therapies, but thorough identification of a small molecule target remains an obstacle. To address this challenge we applied whole-genome pooled CRISPR screening as a Shortcut To Acquired Resistance in Search of mechanism (STAR-Search). This strategy uses CRISPR to generate a population where individual cells each possess a distinct targeted mutation. This comprehensive pool of mutations is then subjected to positive selection, which enriches cells that acquire resistance to compound treatment. The resistance is caused by targeted mutations that are readily identified by sequencing the stably integrated targeting construct. We hypothesize that the identity of gene disruptions underlying resistance can reveal mechanism of action or factors proximal to the direct target. Our group has successfully applied STAR-Search to multiple phenotypic screening hits, thus demonstrating its strong potential as a tool in target identification/validation.

    Our application of STAR-Search examined three small molecules that each elicits cytotoxic effects against a unique spectrum of cancer lines. CGS-18, which preferentially induces apoptosis in breast cancer lines, was dosed onto MDA-MB-468 cells stably transduced with the Brunello CRISPR gRNA library. Cells that survived CGS-18 selection showed enrichment of gRNAs targeting a single gene SULT1A1. MDA-MB-468 cells also undergo apoptosis in response to CGS-59 treatment, so this positive selection was performed in parallel with the previous screen. In this selected population, gRNAs targeting MGST1 were the most highly enriched. Validation experiments have confirmed that individual disruption of SULT1A1 or MGST1 confers resistance to CGS-18 or CGS-59, respectively. The third small molecule, CGS-85, displayed selective killing of multiple myeloma cell lines. This compound was profiled in the BioMap Diversity+ Panel where its phenotypic effects showed strong correlation to the reference database profile generated by the oxidative phosphorylation inhibitor oligomycin. LP-1 cells transduced with the CRISPR library that survived either CGS-85 or oligomycin selection showed enrichment of gRNAs targeting a large number of genes, but this group converged on a common mechanism: mitochondrial oxidative phosphorylation. Despite substantial overlap between the majority of screening hits, prominent differences suggested distinct direct molecular targets. Subsequent enzyme assays showed CGS-85 potently inhibits isolated mitochondrial complex I, whereas oligomycin confirmed as an inhibitor of complex V. Together these examples illustrate the potential of STAR-Search to reveal small molecule mechanisms of action and specifically uncover novel biological connections due to the comprehensive and systematic nature of the genome-wide CRISPR targeted disruptions.

  • UPT and SCLS, two unique workflow for Drug Target Identification
    Chaitanya Saxena, Shantani Proteome Analytics Pvt. Ltd.

    Ever-existing need of identifying the targets of bioactive molecules is recently fuelled by resurgence of Phenotypic Screenings in drug discovery. We will be presenting advantages and case studies of two of our proprietary target identification technologies that can be utilized, in tandem, at different stages of drug development. At ‘Hit’ stage, where compound SAR information is limited, Universal Unique Polymer Technology (UPT), that allows enrichment of targets of underivatized molecule, can be applied in narrowing / identifying the targets of the bioactive molecules. UPT relies on immobilizing the compound utilizing non-covalent, weak-interaction forces of the molecule on a polymer surface, that provides complementary weak-interaction forces for immobilization. Compound immobilized on the polymer are quantified and thus prepared compound specific matrices are incubated with the biological lysate for affinity capture of the target. Captured target proteins are eventually identified using Mass-Spectrometry and the specificity of capture is assigned by comparing the proteins identified from multiple compound loaded and control polymer matrix surface. Key advantage of UPT is that it allows affinity enrichment of target without compound derivatization. For the compounds that have travelled to ‘lead’ stage of development and SAR of the compound is well defined, a SubCellular Location Specific (SCLS) Target Capture Technology is utilized in confirming the identity and the subcellular location of the target. In SCLS, compound of interest is tagged to different subcellular location specific peptide probes. In multiple experiments, probes localize the compound at different cellular location and functional activity of the compound is recorded. The subcellular location, that shows maximum functional response, is then chosen as the target enriched compartment and utilized for target capture experiments. Antibody against the peptide allows the recovery of the probe and the affinity captured protein targets. Eventually captured target proteins are identified using Mass-Spectrometry. Key advantage of SCLS is that it allows investigating the target and mechanism of action in subcellular location manner. For critical evaluation of these new methods, along with the success examples, limitations of these methods will also be presented.

  • Therapeutic Targeting of the Unfolded Protein Response to Treat Disease
    Luke Wiseman, PhD, The Scripps Research Institute

    Imbalances in proteostasis are implicated in the onset and pathogenesis of etiologically-diverse disorders including systemic amyloid diseases and ischemic heart disease. Recent work has shown that activation of the unfolded protein response (UPR)-associated transcription factor ATF6 ameliorates imbalances in proteostasis associated with these disorders. However, the lack of pharmacologic approaches to selectively activate ATF6 has limited the development of this approach to intervene in disease. We employed a high-throughput screening approach to identify first-in-class compounds that preferentially activate the ATF6 arm of the UPR. Here, we will describe the mechanism of action for these compounds and highlight their therapeutic potential to correct pathologic imbalances in proteostasis. Collectively, these results will show that pharmacologic ATF6 activation is a broadly applicable strategy to therapeutically intervene in diverse types of disease.

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Assay Development and Screening

Track Chairs: Ed Ainscow, Carrick Therapeutics and Ralph Garripa, MSKCC

Advanced Imaging-based Phenotypic Assays

Session Chair: Gianluca Pegoraro, National Cancer Institute/NIH

  • A High Throughput Imaging Assay for the Quantification of Gene Expression Dynamics at the Single Cell Level
    Gianluca Pegoraro, National Cancer Institute/NIH

    The establishment and maintenance of gene expression programs is essential for cellular differentiation and organism development. For this reason, gene expression is tightly regulated at the level of mRNA transcription, splicing, and translation. Recently, a combination of genetically encoded fluorescent reporters capable of binding and visualizing mRNA transcripts in living cells, such as MS2 stem loops and MS2-GFP, and of image processing techniques to detect, track and measure these transcripts has enabled the characterization of the dynamic regulation of these processes in live cells. We will describe the design and implementation of a high-throughput imaging assay consisting of panels of cell lines stably expressing a variety of endogenous genes tagged with MS2-stem loops, automated live-cell confocal microscopy for the long-term visualization of the expression dynamics of these genes at the single allele level, automated image processing for cell and transcription site tracking in time-lapse series, and the generation of gene expression trajectories for hundreds of cells per sample. Furthermore, we will show practical implementations of this imaging-based assay to measure the transcriptional kinetics of several independently MS2-repeats-tagged genes, and to quantify changes in transcriptional on/off cycles for a glucocorticoid receptor (GR) regulated locus. Overall, the development of this approach opens the possibility of screening focused chemical or oligo siRNA libraries to identify and characterize novel molecular mechanisms regulating gene expression dynamics.

  • Collaborative Phenotyping at King's College London: HipSci and the Stem Cell Hotel
    Davide Danovi, King's College London

    We work in the framework of the Human Induced Pluripotent Stem Cells Initiative (HipSci) project, funded by the Wellcome Trust and MRC ( Here, we will present in particular the characterisation of a large panel of human induced pluripotent stem cells, focusing on the integration of high content imaging data with genomics. Imaging over 100 human iPS cell lines from healthy donors we have observed evidence for inter-individual variability in cell behaviour. Cells were plated on different concentrations of fibronectin and phenotypic features describing cell morphology, proliferation and adhesion were obtained by high content imaging as in our previously reported method. Furthermore, we have used dimensionality reduction approaches to understand how different extrinsic (fibronectin concentration), intrinsic (cell line or donor) and technical factors affected variation. We have identified with our platform specific RNAs associated with intrinsic or extrinsic factors and single nucleotide variants that account for outlier cell behaviour.  We will also mention significant progress in the integration of dynamic imaging data with other datasets.  By leveraging the expertise derived on this project, we now provide to internal and external scientists a dedicated laboratory space for collaborative cell phenotyping to study how intrinsic and extrinsic signals impact on human cells to develop assays for disease modeling and drug discovery and to identify new disease mechanisms.

  • Identifying molecules for loss of function genetic diseases and pathological secreted factors using high-dimensional morphological profiling.
    Chadwick Davis, Recursion Pharmaceuticals

    The drug discovery flowchart can be a long and labour intensive process with dozens of single endpoint assays to characterize compound behaviour. At Recursion Pharmaceuticals, we have developed an image-based drug discovery platform that enables the rapid evaluation of compounds using high-dimensional phenotypic signatures that provide efficacy, undesirable toxicity, and potential cellular MoA, earlier in the flowchart, at the hit finding stage. Diseases are modelled in human cells by addition of specific disease-relevant perturbations such as gene disruption, inflammatory cytokines, infectious agents, and others. The cells are  labelled with a proprietary set of cellular stains designed to cover a broad range of morphological features and inform on a large scope of biology. Deep learning and additional computer vision methods are used to extract high-dimensional disease specific signatures from our images which accurately represent distinct and subtle cellular responses to disease perturbants and therapeutic candidates. This unbiased, high-dimensional, phenotypic platform enables us to discover highly disease-specific drug candidates that act through both known and novel biology and allows us to screen disease models in at an unprecedented rate.

  • Automated High Content Confocal Imaging of Organ-Chips
    Samantha Peel, AstraZeneca

    Microphysiological systems are in vitro models that aim to accurately recapitulate the organ microenvironment by including additional physiological cues such as shear stress from the microfluidic component. Implementation of microphysiological systems within the pharmaceutical industry aims to improve the probability of success of drugs by generating models that are human and disease relevant. AstraZeneca in collaboration with Emulate has invested in the use of ‘organs-on-chips’ for pre-clinical efficacy and toxicity prediction.

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