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  • Raman spectroscopy of isogenic breast cancer cells derived from organ-specific metastases reveals distinct biochemical signatures

    Objective characterization of the biomolecular divergences of metastatic lesions, which distinguish them from the primary tumor, remains challenging but is crucial for better understanding of organ-specific adaptations that regulate metastatic progression. Using an orthotopic xenograft model, we have isolated isogenic metastatic human breast cancer cells directly from organ explants that show phenotypic differences from the primary tumor cell line.

    Objective characterization of the biomolecular divergences of metastatic lesions, which distinguish them from the primary tumor, remains challenging but is crucial for better understanding of organ-specific adaptations that regulate metastatic progression. Using an orthotopic xenograft model, we have isolated isogenic metastatic human breast cancer cells directly from organ explants that show phenotypic differences from the primary tumor cell line. Leveraging label-free Raman spectroscopic measurements on these isogenic metastatic breast cancer cells from the brain, spine, lung and liver, we designed decision algorithms to enable accurate differentiation without requiring staining or human interpretation. The Raman spectroscopy-based decision models show significant diagnostic power in resolving these isogenic cell lines by analyzing the nucleic acid, protein, lipid and metabolite content. The latter differences were validated through metabolomic analyses that revealed tissue of origin distinctions between the cell lines. Our findings provide evidence that metastatic spread generates tissue-specific adaptations at the molecular level within cancer cells, and open the door for use of Raman spectroscopy to define organ-specific smart chemotherapeutic approaches.

    Chi Zhang

    Johns Hopkins University

    Mr. Chi Zhang is a Ph.D candidate in Mechanical Engineering, Johns Hopkins University. His current research efforts in Dr. Ishan Barman’s lab are directed towards application of Raman spectroscopy and multivariate data analysis to develop novel quantitative approaches for addressing unmet needs in the biochemical study of cancers. He recent mainly focuses on breast cancer cell biochemical and biomechanical variances diagnosis during metastasis by using Raman spectroscopy and machine learning techniques. He also works on kidney stone identification and otitis media effusion analysis. He has published five papers in journals such as Analytical chemistry and Accounts of Chemical Research. He has been awarded the Whiting School Doctoral Fellowship and Mechanical Engineering Departmental Fellowship by Johns Hopkins University.

  • CRISPR-Mediated Tagging of Endogenous Proteins with a Luminescent Peptide

    The effects of synthetic compounds on signaling pathways are often evaluated using overexpressed genetic reporters. It is now possible with CRISPR/Cas9 to better preserve native biology by appending reporters directly onto the endogenous genes. For this purpose, we introduced the HiBiT peptide (11 amino acids) as a small reporter tag capable of producing bright and quantitative luminescence through complementation (KD = 700 pM) with an 18 kDa subunit derived from NanoLuc (LgBiT).

    The effects of synthetic compounds on signaling pathways are often evaluated using overexpressed genetic reporters.  It is now possible with CRISPR/Cas9 to better preserve native biology by appending reporters directly onto the endogenous genes.  For this purpose, we introduced the HiBiT peptide (11 amino acids) as a small reporter tag capable of producing bright and quantitative luminescence through complementation (KD = 700 pM) with an 18 kDa subunit derived from NanoLuc (LgBiT).  The small size of HiBiT minimally alters protein structure, while the luminescent assay provides sensitive analysis at very low expression levels.  Using CRISPR/Cas9, we demonstrated that HiBiT can be rapidly and efficiently integrated into the genome to serve as a quantitative tag for endogenous proteins.  Without requiring clonal isolation of the edited cells, we were able to determine changes in abundance of the hypoxia inducible factor 1A (HIF1α) and several of its downstream transcriptional targets in response to various stimuli.  In combination with fluorescent antibodies, we further used energy transfer from HiBiT to directly correlate HIF1α levels with the hydroxyproline modification that mediates its degradation.  These assay methods allowed dynamics in protein abundance and covalent modifications to be assessed within 24-48 hours of introducing synthetic oligonucleotides together with Cas9 into the cells, thus circumventing the prerequisite for molecular cloning.

    Keith Wood

    PROMEGA CORPORATION

    Keith Wood is Head of Research, Advanced Technologies and Senior Research Fellow at Promega Corporation. Widely regarded for his work in bioluminescence, he currently leads a cross‐disciplinary team focused on long‐range innovation in biochemical and cellular research.  His current research centers on the development of bioanalytical capabilities, including novel bioluminescent chemistries, intracellular detection technologies, and efficient isolation methods for protein and drug complexes.  He has authored over 64 journal articles and book chapters and is an inventor for 164 issued and 124 pending U.S. and foreign patents.  Keith received his Ph.D. in Biochemistry at University of California‐San Diego, where he also performed post‐doctoral research before joining Promega in 1990.

  • Targeting the DCN1-UBC12 Protein-Protein Interaction in the Neddylation Activation Complex

    The Cullin-RING E3 ubiquitin ligases (CRLs) regulate homeostasis of approximately 20% of cellular proteins and their activation require neddylation of their cullin subunit. Cullin neddylation is modulated by a scaffolding DCN protein through interactions with both the cullin protein and an E2 enzyme such as UBC12. Here we report the discovery of high-affinity, cell-permeable small molecule inhibitors of the DCN1-UBC12 interaction.

    The Cullin-RING E3 ubiquitin ligases (CRLs) regulate homeostasis of approximately 20% of cellular proteins and their activation require neddylation of their cullin subunit. Cullin neddylation is modulated by a scaffolding DCN protein through interactions with both the cullin protein and an E2 enzyme such as UBC12. Here we report the discovery of high-affinity, cell-permeable small molecule inhibitors of the DCN1-UBC12 interaction. Using these small-molecule inhibitors as chemical probes, we have made a surprising discovery that the DCN1-UBC12 protein-protein interaction is much more important for the neddylation of cullin 3 over other cullin family members. Treatment of cells of different tissue types with these potent DCN1 inhibitors selectively convert cellular cullin 3 into a unneddylated inactive form with no or minimum effects on other cullin members. Our data firmly establish a previously unrecognized specific role of the DCN1-UBC12 interaction for cellular neddylation of cullin 3. Our compounds represent the first-in-class of selective inhibitors of a specific cullin member, and are excellent probe compounds to investigate the role of the cullin 3 ligase in biological processes and human diseases. We will also discuss their potential therapeutic applications.

    Shaomeng Wang

    University of Michigan

    Dr. Wang received his B.S. in Chemistry from Peking University and his Ph.D. in Chemistry from Case Western Reserve University. Dr. Wang did his postdoctoral training in drug design at the National Cancer Institute, NIH between1992-1996.  Wang is currently the Warner-Lambert/Parke-Davis Professor in Medicine i.  Dr. Wang serves as the Co-Director of the Molecular Therapeutics Program at the University of Michigan Comprehensive Cancer Center and is the Director of the Cancer Drug Discovery Program at the University of Michigan. Dr. Wang is the Editor-in-Chief for Journal of Medicinal Chemistry, a premier international journal in medicinal chemistry and drug discovery by the American Chemical Society.  Dr. Wang has published more than 270 papers in peer-reviewed scientific journals and 100+ meeting abstracts, and is an inventor on more than 48  patents and patent applications. In addition to his academic role, Dr Wang is a co-founder for several biotech companies.

  • DIY integration of a Hamamatsu FDSS to a High-Throughput Screening System; a problem solving and design-for-manufacture exercise, and supporting case for the value of in-house prototyping ability

    A perception exists in the life sciences field that the creation, implementation, integration, modification and maintenance of instrumentation are tasks exclusively to be outsourced to dedicated vendors. At the National Center for Advancing Translational Sciences (NCATS) we believe that readily available solutions can be quick and cost-effective, but if the science or the scientist dictates a new tool that doesn’t yet exist, the ability to quickly design and produce real, usable instruments can tremendously accelerate progress.

    A perception exists in the life sciences field that the creation, implementation, integration, modification and maintenance of instrumentation are tasks exclusively to be outsourced to dedicated vendors. At the National Center for Advancing Translational Sciences (NCATS) we believe that readily available solutions can be quick and cost-effective, but if the science or the scientist dictates a new tool that doesn’t yet exist, the ability to quickly design and produce real, usable instruments can tremendously accelerate progress. This value is proven by our in-house integration of a Hamamatsu FDSS7000EX Functional Drug Screening System to an existing single-arm High Throughput Robotic Platform, and further integration of an Ion Field Tip Charger plasma pin tool cleaning system to that FDSS. This project demonstrates that the process of problem solving is of enormous importance to the outcome. Good design involves engineering, but not exclusively so; time spent at the very beginning to “consider what bears consideration” is always time well spent, and it’s often the least expensive time billed to the project. “A designer is an emerging synthesis of artist, inventor, mechanic, objective economist and evolutionary strategist” – R. Buckminster Fuller This quote encapsulates the concept that problem solving for life sciences is an open-ended, inquisitive process in which diverse disciplines spanning engineering and sociology must be given consideration, equally.

    Eric Wallgren

    National Institutes of Health - National Center For Advancing Translational Sciences

    Eric Wallgren is an art school graduate who grew up in a house with a small machine shop in the basement.  He has worked as a mechanical and industrial designer and prototyper,  primarily in life sciences instrumentation, photovoltaic/renewable energy and powersports for about twenty years, before which he received an informal mechanical education while working as a bicycle mechanic.  In addition to his position as Instrumentation Lead at NCATS he also is owner/driver/crew  of Area 51 Racing, competing in the SCCA P2 class, and proprietor of MMW Engineering a small machine and fabrication shop.

  • Precision Enabled: Discovery of Gene Networks and New Drug Targets in Metastatic Melanoma with Single Cell Sequencing

    Despite the buzz regarding cloud facilitated data integration, notification, and tracking, LIMS and electronic laboratory notebooks have failed to deliver for multi-omics. Instead, current solutions are open source or have the user-friendliness of an electronic medical records system -- raising the activation energy and time required to install, to collaborate, and ultimately to produce insight. Herein, we describe a workflow-based collaboration and communication approach and its use in a coordinating the analysis of single cell gene expression from 19 melanoma metastases.

    Despite the buzz regarding cloud facilitated data integration, notification, and tracking, LIMS and electronic laboratory notebooks have failed to deliver for multi-omics.  Instead, current solutions are open source or have the user-friendliness of an electronic medical records system -- raising the activation energy and time required to install, to collaborate, and ultimately to produce insight.   Herein, we describe a workflow-based collaboration and communication approach and its use in a coordinating the analysis of single cell gene expression from 19 melanoma metastases. We show that each metastatic tissue is unique to each patient, but identify a rare subpopulation present in each tumor which shares the same gene expression pattern.  Thus, we identify two new drug targets shared between patients, and uncover the gene expression pattern of the immune response, particularly exhausted CD8+ T cells within each metastatic tissue could be reversed.  Thus, we show how single cell phenotyping and gene expression experiment execution may be coordinated and executed to reveal both tumor and immune response drug targets and gene expression networks.  We extend this work to compare the tumor gene expression patterns to the published literature and drug trials, and show that drug repurposing may be an effective strategy for melanoma.

    Michael Stadnisky

    FlowJo, LLC

    Michael Stadnisky, Ph.D. is the CEO of FlowJo, LLC, the leading single cell flow cytometry and sequencing informatics company.  Mike recently led his team to bring a new gene expression analysis platform to scientists in under 9 months in collaboration with Illumina.  He is an author of 4 patents, was a finalist for the 2014 International Society for the Advancement of Cytometry President’s Award. 

  • CROP-seq: Pooled CRISPR screening with single-cell transcriptome readout – a high-throughput method for dissecting gene-regulatory mechanisms

    We are exploring combinations with alternative functions, such as CRISPR inhibition, activation and targeted epigenetic modifications. I will further provide insights into further technical improvements such as higher gRNA detection rates and demonstrate CROP-seq compatibility with single cell sequencing platforms capable of further upscaling screens. Given the increasing throughput of single-cell transcriptomics and the advent of single-cell multi-omics technology (reviewed in: Bock et al. 2016 Trends in Biotechnology), CROP-seq has the potential to provide comprehensive characterization of large CRISPR libraries and constitutes a powerful method for dissecting cellular regulation at scale.

    CRISPR-based genetic screens are accelerating biological discovery, but current methods have inherent limitations. Widely used pooled screens work well for mechanisms that affect cell survival and proliferation, and can be extended by sortable marker proteins. However, they are restricted to measuring the distribution of guide RNAs before and after applying a selective challenge, and do not provide any detailed phenotypic information. Since the actual cellular responses are not measured, the interpretation and validation of screening hits is generally work-intensive and prone to false positive results. Arrayed CRISPR screens, in which only one gene is targeted at a time, allow for more comprehensive molecular readouts, but at much lower throughput. We have recently developed a third and complementary screening paradigm, single-cell CRISPR screens, based on the idea that gRNAs and their induced cellular responses are already compartmentalized within single cells. We combined pooled CRISPR screening with single-cell RNA sequencing into a broadly applicable workflow, directly linking guide RNA expression to transcriptome responses in thousands of individual cells (Datlinger et al. 2017 Nature Methods). Our method for CRISPR droplet sequencing (CROP-seq) enables pooled CRISPR screens for entire gene signatures that can be derived directly from the data. Due to its single-cell resolution, CROP-seq can localize the effect of perturbations in complex tissues and cellular differentiation hierarchies, and can work efficiently on scarce material. Furthermore, CROP-seq is compatible with virtually all current methods for single-cell RNA-seq and established strategies for pooled library cloning.

    Since the original publication, we continued to develop CROP-seq with a particular focus on in vivo screens in Cas9 mice. We are exploring combinations with alternative functions, such as CRISPR inhibition, activation and targeted epigenetic modifications. I will further provide insights into further technical improvements such as higher gRNA detection rates and demonstrate CROP-seq compatibility with single cell sequencing platforms capable of further upscaling screens. Given the increasing throughput of single-cell transcriptomics and the advent of single-cell multi-omics technology (reviewed in: Bock et al. 2016 Trends in Biotechnology), CROP-seq has the potential to provide comprehensive characterization of large CRISPR libraries and constitutes a powerful method for dissecting cellular regulation at scale.

    Andre Rendeiro

    CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences

    More information coming!


  • The use of DNA Encoded Library Technology to identify hits for less tractable targets

    DEL technology has been adopted by many organisations including AstraZeneca. In partnership with X-Chem we have screened over 40 targets using this screening paradigm. In this presentation I will describe the principles of the DEL platform, and how AstraZeneca has applied this platform as part of our integrated hit discovery strategy, providing examples of the identification of hit series for less tractable targets, and the use of the DEL platform to identify novel binding sites on target proteins.

    Over the last decade there has been increasing application of DNA Encoded Library (DEL) technology to complement traditional high throughput screening for hit discovery.  DNA Encoded Libraries consist of hundreds of millions of molecules synthesised on a DNA tag, such that the structure of the small molecule is genetically encoded by the sequence of the tagged DNA.  These libraries are tested against molecular targets in an affinity based selection method.  Through the use of such libraries it is possible to test huge numbers of small molecules without incurring the costs of creating a traditional small molecule library and without the automation infrastructure requirements to house and test such compounds.   It is the rapid advancement in Next Generation Sequencing technologies that has enabled the creation of this screening paradigm, the ability to mine screening data in depth and has reduced the costs of screening.   DEL technology has been adopted by many organisations including AstraZeneca.  In partnership with X-Chem we have screened over 40 targets using this screening paradigm.  In this presentation I will describe the principles of the DEL platform, and how AstraZeneca has applied this platform as part of our integrated hit discovery strategy, providing examples of the identification of hit series for less tractable targets, and the use of the DEL platform to identify novel binding sites on target proteins.

    Stephen Rees

    AstraZeneca

    In March 2017 Steve was appointed as Vice-President of the Discovery Biology department at AstraZeneca with global accountability for protein and cellular reagent generation and assay development, functional genomics and chemical biology. Prior to this Steve led the Screening Sciences and Sample Management department and successfully implemented strategies for hit identification, compound profiling, sample management and open innovation. Steve has led multiple international collaborations and has authored >60 scientific papers. Steve is currently Chair of the European Laboratory Research and Innovation group (ELRIG), has served as Chair of the SLAS Europe Council, and is a member of the Scientific Advisory Board for Axol Biosciences, LifeArc and the Centre for Membrane Protein and Receptor research at the Universities of Nottingham and Birmingham.

  • The Open Targets Cell Line Epigenome Project: Determining the Biological Relevance of Cellular Assay Models through Epigenetic Analysis

    The data and tools we have generated provide an impactful framework enabling biologists to select the most appropriate, predictive cellular model for their research and to better establish optimal assay critical paths for translating target biology & compound pharmacology to the clinic. In this presentation we will demonstrate how we have used this approach to quantify the impact of 2D vs. 3D culture in cellular models of liver drug toxicity; identify the most relevant immune cell models of inflammatory response and validate immortalised cell surrogates for genome wide gene editing studies.

    The Open Targets Cell Line Epigenome Project addresses the challenge of selecting appropriate cellular models for target validation and drug screening that exhibit sufficient relevance to pathways and phenotypes associated with a particular disease or biology. The implementation of more complex, disease relevant models through use of 3D culture, tissue slices and primary cells is improving the predictive power of in vitro assays. However, due to limitations in cell and tissue supply, scalability, assay reproducibility and amenability to genetic manipulation, there often remains a need to utilise transformed cell lines, particularly for higher throughput cellular screens and gene editing studies. Currently cell lines are often chosen for these purposes based on historical usage, even if they are a poor substitute for that cell type or tissue. To address the gap in data driven cell line and model selection, we have developed a novel systematic approach to determine biological relevance through the generation and analysis of transcriptomic and epigenomic data. Epigenomic and transcriptomic profiles (RNA/ChIP/ATAC-seq) from common immortalised cell models have been generated and integrated with publicly available reference data from primary cells. Statistical methods have been developed to score cells based on distance / similarity at the global genome level or more specific gene sets, signaling pathways or genomic loci of interest. The data and tools we have generated provide an impactful framework enabling biologists to select the most appropriate, predictive cellular model for their research and to better establish optimal assay critical paths for translating target biology & compound pharmacology to the clinic. In this presentation we will demonstrate how we have used this approach to quantify the impact of 2D vs. 3D culture in cellular models of liver drug toxicity; identify the most relevant immune cell models of inflammatory response and validate immortalised cell surrogates for genome wide gene editing studies.

    Rebecca Randle

    Screening Profiling & Mechanistic Biology, GlaxoSmithKline

    Following a PhD at Imperial College London focusing on expression of P-glycoprotein and the development of multidrug resistance in cancer, I established a career in the pharmaceutical industry with positions at UCB-Celltech (Cambridge, UK) and GlaxoSmithKine (Stevenage, UK). I have a strong background in cell biology, phenotypic screening and a deep interest in epigenetics. I currently work within GSK’s Screening Profiling and Mechanistic Biology Department (within Platform Technology and Science) as a cell biologist and program leader. My role involves leadership of GSK early drug discovery programs and external collaborative projects such as the Cell Line Epigenome Project, an Open Targets project in collaboration with EMBL-EBI and the Wellcome Trust Sanger Institute. 

  • Chemical and genomic identification of globin regulators that induce fetal hemoglobin reactivation

    We identified multiple druggable components of lipid metabolism, nuclear receptor pathways and transcription/chromatin regulatory pathways that modulate HBgamma mRNA using our automated, cell-based chemical genetic screening platform. Through characterization of these regulators, we have demonstrated that CRISPR targeting of different protein domains of components of the globin regulatory network can have profoundly different effects on globin gene expression patterns.

    Red blood cell disorders like Sickle Cell Disease (SCD) and beta-thalassemias are caused by alterations within the gene for the hemoglobin beta (HBbeta) subunit. A fetal ortholog of HBbeta, hemoglobin gamma (HBgamma) can reverse disease-related pathophysiology in these disorders by also forming complexes with the required hemoglobin alpha subunit. Because beta-like globin expression is developmentally regulated, with a reduction in the fetal ortholog (gamma) occurring shortly after birth concomitantly with an increase in the adult ortholog (beta), it has been postulated that maintaining expression of the anti-sickling gamma ortholog may be of therapeutic benefit in children and adults. Previously, inhibitors of chromatin modifying enzyme G9a/GLP (G9a-i) have been shown to upregulate HBgamma expression relative to HBbeta expression and therefore G9a/GLP has been proposed as a reasonable molecular target for maintenance of the anti-sickling HBgamma ortholog.  However, we have uncovered limitations to G9a-i as a therapeutic strategy to reactivate HBgamma and therefore set out to identify novel modulators and targets of HBgamma expression using both chemical probe and CRISPR-based genetic screening strategies.  We identified multiple druggable components of lipid metabolism, nuclear receptor pathways and transcription/chromatin regulatory pathways that modulate HBgamma mRNA using our automated, cell-based chemical genetic screening platform. Through characterization of these regulators, we have demonstrated that CRISPR targeting of different protein domains of components of the globin regulatory network can have profoundly different effects on globin gene expression patterns.  More specifically, modulation of key domains of chromatin writers, readers and erasers results in markedly different globin expression profiles that informs small molecule discovery against these novel targets. Additionally, we are utilizing a newly developed in vitro SCD cellular model to investigate how these globin gene regulators impact SCD pathophysiology.

    Pete Rahl

    Fulcrum Therapeutics

    More information coming!

  • Microtissues in 4D to Improve Drug Toxicity Risk Assessment

    Our results demonstrate the potential to use sophisticated imaging and machine learning analysis techniques to interrogate increasingly complex cellular systems such as microtissues to assess and mitigate for toxicity risk in preclinical drug discovery.

    Drug discovery and development is often halted or delayed due to toxicological risks associated with the candidate drug and in particular those associated with cardiac toxicity. Cellular models that enable early and accurate assessment of compound liability are required.  We have developed a suite of 384-well based 3D spheroid based multicellular model systems and applied novel kinetic imaging and analytical approaches to better assess compound toicity risk early in drug discovery.  Cardiac microtissues utilised tri-cultures of human primary, IPS cell derived and primary cells to better represent cardiac tissue structure and functional activity. Characterisation of these model systems show physiologically relevant responses. Cardiac microtissues had a spontaneous beat rate of 62 ± 24 beats/minute (mean ± SD) and the microtissues maintained synchronized contraction transients following stimulation at 1, 2 and 3 Hz. To study and quantify changes in cardiac contractility we developed a bespoke fast frame-rate widefield image acquisition methodology coupled with optical flow image analysis and Wavelet decomposition.  Structural cardiotoxicity was assessed using cytotoxicity and live cell high-throughput confocal microscopy, combined with analysis of endoplasmic reticulum integrity and mitochondrial membrane potential from all-in-focus images.  Validation against a panel of in vivo clinical and pre-clinical compounds that represented diverse mechanisms of toxic effect showed improved sensitivity and specificity over 2D model systems.  73% of internal compounds stopped due to changes in cardiac pathology between first GLP dose and FTiH (2001-2014) were detected using this live cell imaging and cytotoxicity approach for structural cardiotoxicity with functional cardiotoxicants identified at 91% sensitivity and 80% specificity.  These developed models and imaging-based screening systems are in use at a scale enabling full dose-response testing of compounds to enable effective decisions to be made early in a drug project lifecycle.  Our results demonstrate the potential to use sophisticated imaging and machine learning analysis techniques to interrogate increasingly complex cellular systems such as microtissues to assess and mitigate for toxicity risk in preclinical drug discovery.

    James Pilling

    AstraZeneca

    James Pilling is an Associate Principal Scientist within the Global High Content Biology Group in AstraZeneca. James joined AstraZeneca in 2004 and has worked with applying novel technologies and approaches to Drug Discovery processes across various therapeutic areas. The remit of the High Content Biology Group is to develop and deploy high content phenotypic assays, mechanistic profiling and high content imaging platforms across AstraZeneca. James holds an MSc in Biochemistry and Biological Chemistry from Nottingham University and a BPS Diploma in Pharmacology. Current research interests include the development and application of Precise Genome Editing technologies to aid Target Identification and the use of advanced 2D and 3D cellular models for the prediction of drug safety and efficacy.

  • Spatial neuron cell-type mapping in mouse brain by in situ sequencing

    Single-cell RNA-seq (scRNA-seq) is a powerful tool to classify cells to molecularly defined cell types. However, the information about absolute frequency of cells and exact spatial location the within the original tissue is lost.

    Single-cell RNA-seq (scRNA-seq) is a powerful tool to classify cells to molecularly defined cell types. However, the information about absolute frequency of cells and exact spatial location the within the original tissue is lost. The brain is the most complex tissue in mammals with respect to the number of different cell-types and the way they are arranged locally and through long range cell-to-cell connections. Here, we demonstrate that in situ sequencing (Ke et al., Nat.Meth., 2013) can be used to build a cell-type spatial map of 100 000s of cells in sections of mouse brain. We use in situ sequencing to map the activity of 99 marker genes within single cells across sections of mouse brains. The marker genes are selected to identify neurons in cortex and hippocampus as defined by scRNAseq. In a single experiment on a single standard microscopy slide, we can analyse four coronal brain sections from adult mice. Each section contains around 100,000 cells and we generate about 3 million reads per section. The read distribution for individual marker genes matches well with the Allen Brain Atlas. To turn the 99 molecular distributions into cell-types, we use a probabilistic approach to assign identity to individual cells based on comparison with the profiles of 35 cell types as defined by scRNA-seq. The sensitivity of the approach is demonstrated by our identification of rare Pvalb-expressing cells among pyramidal cells in stratum pyramidale, and Cck-positive cells, in stratum radiatum.


    Ke, R., Mignardi, M., Pacureanu, A., Svedlund, J., Botling, J., Wahlby, C. & Nilsson, M. In situ sequencing for RNA analysis in preserved tissue and cells Nat. Methods 10, 857-860 (2013).

    Mats Nilsson

    Science for Life Laboratory, Stockholm University

    My research is focused on development and application of novel molecular analysis tools and systems. I have pioneered the development of methods based on DNA circularization, i.e., padlock and selector probes, as well as rolling circle amplification (RCA). The work involves fundamental studies of nuclease- and nucleic acid hybridization mechanisms, design assays based on them and integrate these into methods and systems. I have a large international network of collaborators in academia and industry, ranging from basic molecular biology and physics to clinicians and engineers. The aim is to enable new research and to bring some technologies towards diagnostic use. My group is based at Science for Life Laboratory, which is a joint cross-disciplinary research center at the Karolinska Campus, formed by Stockholm University, Karolinska Institutet, and KTH. I have authored more than 140 scientific articles that have been cited more than 7 000 times (h-index 40).

  • SLAS2018 Innovation Award Finalist: Combinatorial Drug Screening, High-Throughput Flow Cytometry, and Agile Integration: a Modern Platform for Personalized Treatment Discovery for Cancer Patients

    ​Our mission at Notable Labs is to identify actionable, personalized treatments for cancer patients. To help us achieve this goal, we have developed a platform that combines combinatorial testing, drug repurposing, and several high-throughput technologies to automate our phenotypic screens on primary patient samples. Our current focus is in acute myeloid leukemia (AML) and other hematological malignancies, although the platform and assay can be extended to other indications.

    Our mission at Notable Labs is to identify actionable, personalized treatments for cancer patients. To help us achieve this goal, we have developed a platform that combines combinatorial testing, drug repurposing, and several high-throughput technologies to automate our phenotypic screens on primary patient samples. Our current focus is in acute myeloid leukemia (AML) and other hematological malignancies, although the platform and assay can be extended to other indications.

    Our automation platform includes our custom-made laboratory information management system (LIMS) working in tandem with our robotic workcell, which handles all screening and assay operation. The architecture of this system is designed to allow for separation between conceptualization and execution; scientists can plan their screens and experiments through the LIMS, then walk to the workcell and start an automated run that executes their plan, with minimal preparation.

    The core assay in this platform is a high-throughput flow cytometry assay that generates a wealth of phenotypic data on the primary patient samples that are run through the system. Over the course of the assay, the robotic scheduler serves as a middleman for information flow between the LIMS and the workcell instruments themselves. The LIMS sends relevant data about the screen to the scheduler, which in turn acts on the data and directly controls the instruments to run the assay.

    After completion of an assay, raw data flows back from the workcell instruments to the scheduling software, which consolidates the data and uploads it to our cloud-based LIMS. From there, a number of in-house software tools are used to streamline our flow cytometry data analysis, allowing scientists to analyze complex, multi-dimensional flow data across thousands of wells.

    The platform has been validated across a number of patients. Our data has led to actionable treatment options for relapsed and refractory patients that has, in some instances, resulted in complete remission in AML patients. The platform and architecture that we have developed brings together our collective hardware, software, and biological knowledge, and demonstrates the predictive power of our data-driven approach to personalized medicine for cancer patients.

    Transon Nguyen

    Notable Labs

    Transon Nguyen is the lead automation engineer at Notable Labs, where he develops hardware and software systems to advance Notable's high-throughput screening capabilities.  He was previously a biomedical engineer at the Charles Stark Draper Laboratory, developing advanced in vitro organ systems for drug discovery.  Transon holds an M.S. in Mechanical Engineering from the Massachusetts Institute of Technology, and an M.S. in Biomedical Engineering from the University of California, Irvine.

  • NGS-based Genome-wide Genetic Screens for RNA Processing Regulators

    High throughput genetic and chemical screens have been powerful tools to comprehensively identify regulators in specific cellular pathways or drug leads in both industry and academia. However, most screens rely on one or a few functional readouts, even with so-called high content screens. We have developed a robust and fully automatable screen platform that couples with NGS (next-generation sequencing) to monitor the expression of hundred-to-thousand endogenous genes associated with a phenotype without need to purify RNA.

    High throughput genetic and chemical screens have been powerful tools to comprehensively identify regulators in specific cellular pathways or drug leads in both industry and academia.  However, most screens rely on one or a few functional readouts, even with so-called high content screens.  We have developed a robust and fully automatable screen platform that couples with NGS (next-generation sequencing) to monitor the expression of hundred-to-thousand endogenous genes associated with a phenotype without need to purify RNA.  The platform is based on annealing a cohort of specific oligonucleotides to specific transcripts and/or their isoforms followed by solid phase selection, RNA-templated oligonucleotide ligation, and PCR amplification using bar-coded primers. We refer this assay strategy as RASL-seq (RNA Annealing, Selection, Ligation coupled with NGS).  Pooled samples from up to 1500 reactions in 384 wells can then be sequenced in a single lane of an Illumina sequencing flowcell to obtain quantitative information on targeted transcripts. We have previously identified a gene signature associated with activated androgen receptor (AR) on prostate cancer cells and applied RASL-seq to identify chemicals that can specific inactivate the AR pathway, thus establishing the proof-of-concept for gene signature-based chemical screens, which are equally applicable to both druggable and non-druggable targets.  We have also utilized the RASL-seq platform to screen for regulators involved in the regulation of pre-mRNA splicing and alternative polyadenylation in mammalian cells.  Coupled with our efforts in technology development, we have developed a bioinformatics pipeline to process the data for quantitative and network analyses.  The RASL-seq platform thus offers a general solution to pathway dissection in both genetic and chemical screens.

    Hai-Ri Li

    University of California, San Diego

    Name: Hai-Ri Li    Affiliation: University of California, San Diego
    Position Institution Year(s)
    Project Scientist UC, San Diego 2007-Present
    Postdoc Fellow UC, San Diego 2002-2006
    Postdoc Fellow Sanford-Burnham Medical Research Institute 2000-2001
    EDUCATION / TRAINING:
    Institution or Location Degree Year(s) Field of Study
    China Medical University MS 1986-1989 Endocrinology, Medicine
    Jiamushi Medical College, China MD 1977-1983 Medicine
    EXPERTISE AND RELEVANT EXPERIENCE
    I have been involved in genomics, especially in RNA. I developed two simple RNA-seq methods, one for whole transcriptome profiling and another for 3’ end of RNA profiling. In addition, I developed a target gene profiling method, i.e. RASL-seq (RNA-mediated Annealing, Selection and Ligation, combined with high-throughput sequencing). We applied it to chemical screening in prostate cancer cells. We selected hundred genes in androgen receptor pathway as signatures and observe which chemical compounds affect androgen receptor pathway genes. We sequenced 1536 samples in single lane of Illumina flowcell and found a few promising candidates for prostate cancer therapy. Recently we also applied it to identification of RNA processing regulators and found new previously undescribed RNA processing regulators, which will be helpful in exploring new mechanisms in different diseases.

  • Routine lab automation with culture dishes made easy - How the PetriJet platform technology helps to makes drinking water analysis faster and better

    ​Digitalization, Automation and Miniaturization currently change the way we live and work. It also affects daily work in laboratories. The disruptive development of new technologies such as open source automation technology, the Internet of Things (IoT) and 3D-printing offer endless possibilities for an in-house engineering of new laboratory devices which are compact, adaptable and smart.

    Digitalization, Automation and Miniaturization currently change the way we live and work. It also affects daily work in laboratories. The disruptive development of new technologies such as open source automation technology, the Internet of Things (IoT) and 3D-printing offer endless possibilities for an in-house engineering of new laboratory devices which are compact, adaptable and smart.

    At the SmartLab systems department of the Technische Universitaet Dresden, Germany approaches for the laboratory of the future have been developed and implemented. This includes the PetriJet platform technology which was developed the automate all processes associated with culture dishes in environments such as routine laboratories for drinking water or blood samples as well as culture development for the next generation of antibiotics. The device technically is a x-y-robot consisting of two linear axles enabled to transport variable sizes and shapes of culture dishes from A to B through a 3D-printed gripper-system which can also remove the lid of the culture dish. 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 stations – e. g. sample imaging – installed. It is not necessary to specify locations for culture dish piles and treated dishes are allocated dynamically 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. Several processing stations e. g. for sample plating or drug discovery are under development

    The first PetriJet platform designed and build in the SmartLab systems lab in Dresden, Germany now operates in a routine laboratory for drinking water analysis in Hamburg, Germany and currently visually inspects a four-digit number of drinking water samples subject to infection with Legionella bacteria every day.

    The systems integrated image analysis software counts colonies on direct samples as well as on filters, sorts the samples and is linked to the LIMS of the company speeding up to inspection process by factor 4 and making the data available to customers just in time even after a night shift. Inspection quality and throughput has increased significantly and stored proof images are available even weeks after sample treatment enabling a completely new approach to data mining and infection tracking.

    Felix Lenk

    TU Dresden INT

    Felix Lenk is a Postdoc at the Institute of Natural Materials Technology at the TU Dresden, Germany, and head of the SmartLab systems department working on the next generation of laboratory devices and systems. He studied Automation & Control and Electrical Engineering at the TU Dresden, Germany and at the University of Calgary, Calgary, Alberta, Canada and graduated in 2009. In 2014 he received his PhD in Bioprocess Engineering at the TU Dresden in the field of growth modeling of plant in vitro cultures. He currently works in the field of autonomous sensor systems, laboratory automation and assistance systems as well as biological sample imaging and automatic image analysis for different biotech applications.

  • Tumor Organoids for Therapeutic Discovery and Personalized Medicine

    This presentation will discuss our recent innovative tumor organoid models of various cancers, which we have engineered for 3D HCS drug discovery targeting EMT. Our tumor organoid models feature an innovative dual fluorescent biomarker reporter of EMT that can effectively track the forward and reverse EMT transition in live tumor organoids.

    The past decade has seen a revolution in developing 3D tissue models of organ function, anatomy, and disease which can be employed for markedly improved drug screening approaches. These models are referred to as organoid, organotypic, or spheroid and these terms are used interchangeably within the literature. Organoids are defined by their ability to mimic in vivo organ function and/or disease, they can be engineered with multiple cell types and microenvironment components, and organoids have the distinct ability to self-assemble. Like organoids, tumor organoids mimic in vivo tumor biology and recapitulate key interactions between extracellular matrix (ECM) molecules and tumor cell receptors that initiate signaling events regulating and promoting cancer. Tumor organoids prove to be very useful for modeling epithelial-mesenchymal transition (EMT), a reversible process that allows adherent epithelial cells to undergo morphological changes acquiring the motile mesenchymal cell phenotype. This phenotypic plasticity is essential for human and animal body development and wound healing, allowing cells to shed from the epithelium and invade and migrate through the microenvironment to specific locations where mesenchymal cells differentiate or induce differentiation of other cells into specialized cell types and stem cells to produce tissues, organs and bones. However, aberrant EMT is linked as a major driving force in the pathology of the most prominent human diseases: fibrosis, cardiovascular disease, inflammatory disease, eye disease, and cancer progression and metastasis. Therefore, drug discovery targeting EMT has become an attractive strategy towards more effective therapies, particularly for the treatment malignant cancers. This presentation will discuss our recent innovative tumor organoid models of various cancers, which we have engineered for 3D HCS drug discovery targeting EMT. Our tumor organoid models feature an innovative dual fluorescent biomarker reporter of EMT that can effectively track the forward and reverse EMT transition in live tumor organoids. Moreover, we will discuss hit confirmation approaches and secondary assays used to validate compounds that specifically modulate or reverse EMT. Finally, we will discuss our most recent approaches to develop patient derived tumor organoid (PDTO) models suitable for high-content analysis and screening towards achieving the goal of personalized medicine in cancer.

    Dan LaBarbera

    University of Colorado Anschutz Medical Campus

    Dr. LaBarbera is an associate professor of drug discovery and medicinal chemistry at the University of Colorado Anschutz Medical Campus. He received his PhD from Arizona State University in organic and medicinal chemistry focused on cancer drug design and development. He completed a NIH National Research Service Award postdoctoral training fellowship award focused on multidisciplinary cancer research. Dr. LaBarbera’s laboratory is engaged in preclinical drug discovery and development aimed at translating effective therapies targeting cancer, diabetes, and microbial infection. A major focus of his research is the molecular and cancer biology controlling epithelial-mesenchymal transition (EMT) and the
    identification of novel therapeutics that specifically target these mechanisms. Dr. LaBarbera's laboratory has developed pioneering approaches to HTS/HCS drug discovery using 3D tumor organoids and we are applying our innovative approaches to develop patient derived tumor organoid models for drug discovery and personalized medicine.

  • Inflammation-on-a-chip – High-throughput microscale arrays for human neutrophil swarming

    Neutrophil swarms protect healthy tissues by sealing off sites of infection. In the absence of swarming, microbial invasion of surrounding tissues can result in severe infections. Recent observations in animal models have shown that swarming requires rapid neutrophil responses and well-choreographed neutrophil migration patterns.

    Neutrophil swarms protect healthy tissues by sealing off sites of infection. In the absence of swarming, microbial invasion of surrounding tissues can result in severe infections. Recent observations in animal models have shown that swarming requires rapid neutrophil responses and well-choreographed neutrophil migration patterns. However, in animal models, physical access to the molecular signals coordinating neutrophil activities during swarming is limited. Here, we report the development and validation of large microscale arrays of targets for the study of human neutrophils during swarming ex vivo. We characterized the synchronized growth of thousands of swarms at once, towards live-microbe and microbe-like synthetic particles simulating infections.  We took advantage of the synchronized swarming in small volumes to analyze in detail the mediators released at different phases of human-neutrophil swarming against various targets. We found that the mediators coordinating human-neutrophil swarming form a complex network, with multiple levels of redundancy, which includes more than 40 signaling proteins, i.e. stimulatory of neutrophil activity, proteolytic enzymes and enzyme inhibitors, activators of other immune and non-immune cells (monocytes, lymphocytes, endothelial cells, adipocytes, etc).  We identified only one mediator that limits the growth of neutrophil swarms, LAX4, which is a lipid and has been associated before with the restoration of immune homeostasis.  We compared the swarming behavior of neutrophils from patients following major trauma and healthy individuals and found various deficiencies that resolve over time.  Overall, we report a new platform technology for studying neutrophil swarming, a behavior that is relevant to various disease and physiologic processes, and which could serve as discovery and validation platform for novel anti-inflammatory and anti-microbial treatments. 

    Daniel Irimia

    Harvard Medical School - Massachusetts General Hospital

    microfluidics, neutrophils, inflammation, sepsis

  • Identifying new allosteric sites on PTP1B using fragment-based tether scanning

    We have been applying a disulfide-tethering fragment-based approach to identify and characterize new binding and allosteric sites on PTP1B. Here we report our progress to date, and show that this “Tether Scanning” approach has allowed us to identify new binding sites on PTP1B, as well as new disulfide fragments that modulate PTP1B activity.

    Due to its role in regulating insulin receptor kinase, protein-tyrosine phosphatase 1B (PTP1B) has been a long sought after drug target for the treatment of diabetes and other metabolic disorders. Unfortunately, due to the high homology between PTP family members and the charged nature of substrate mimics, developing selective and cell-permeable active site inhibitors of PTP1B has proven notoriously difficult. For this reason, there has been great interest in developing compounds that allosterically modulate PTP1B activity. Towards this goal, we have been applying a disulfide-tethering fragment-based approach to identify and characterize new binding and allosteric sites on PTP1B. Here we report our progress to date, and show that this “Tether Scanning” approach has allowed us to identify new binding sites on PTP1B, as well as new disulfide fragments that modulate PTP1B activity. 

    Zachary Hill

    University of California, San Francisco

    Zachary is currently a postdoctoral fellow in Jim Wells' lab at UCSF, where he works on the development of chemical biology approaches to identify and study new bioactive small molecules. Prior to coming to UCSF, Zachary completed his PhD in Organic Chemistry with Dustin Maly at the University of Washington, where he worked on the development of bivalent kinase inhibitors. During his postdoc, Zachary has been fortunate enough to be supported by a fellowship from the Helen Hay Whitney Foundation, as well as a K99 Transition award from the NIH-NCI. In the next year, Zachary hopes to transition to an independent position where he will continue applying ligand-based approaches to study biological systems. 

  • SLAS2018 Innovation Award Finalist: Pharos – A Torch to Use in Your Journey In the Dark Genome

    Given the heterogeneous set of data types available for individual targets, it is useful to quantify how much and what types of data is available for a target. We describe the development of knowledge profiles and a Knowledge Availability Score (KAS), both derived from the Harmonizome, which is a resource that has characterized data availability across different data sources and types in a uniform manner.

    It is well known that a relatively small set of protein targets receive the bulk of research attention and thus funding. However, there are potential (druggable) opportunities in the remaining under-studied and un-studied proteins. To address this the NIH initiated the "Illuminating the Druggable Genome" program to characterize the dark regions of the druggable genome. As part of this program, a Knowledge Management Center (KMC) was created to aggregate and integrate heterogeneous data sources and data types creating a centralized location for information about all protein targets identified as part of the druggable genome. Since then the KMC has expanded to consider the entire human proteome. In this presentation, we describe Pharos, the user interface for the KMC knowledgebase. We provide an overview of the data sources and types made available via Pharos and then describe the architecture of the system and its integration with KMC & external resources. In particular we highlight the rich search facilities that enable a user to drill down to relevant subsets of data but also support the notion of "serendipitous search".  Given the heterogeneous set of data types available for individual targets, it is useful to quantify how much and what types of data is available for a target. We describe the development of knowledge profiles and a Knowledge Availability Score (KAS), both derived from the Harmonizome, which is a resource that has characterized data availability across different data sources and types in a uniform manner. We then highlight how the KAS is concordant with knowledge trends characterized by traditional metrics such as publications and grants.  We discuss the use of the KAS in the Pharos interface and an example of prioritizing understudied targets by computing the similarity of their knowledge availability profiles with that of well-studied targets.

    Rajarshi Guha

    NIH

    Rajarshi Guha is Group Leader (Research Informatics) in the Division of Pre-Clinical Innovation at NCATS. With over 10 years of experience in handling, analysing and visualizing chemical information, he brings a diverse range of skills and experience to his current role at NCATS. He is involved in small molecule development projects in a variety of therapeutic areas including rare cancers and infectious diseases. He is also involved in software and algorithm development in the areas of cheminformatics methods and large scale infrastructure projects including Pharos (http://pharos.nih.gov/) BARD (http://bard.nih.gov/). His research interests focus on methodology development to analyze and visualize chemical biology data sets, with specific focus on techniques to link chemical structure information to molecular, bibliographic, genomic and clinical covariates.   He has held multiple leadership roles in the American Chemical Society’s Division of Chemical Information and is currently a co-Editor in Chief of the Journal of Cheminformatics.

  • Pathology from the Molecular Scale on Up.

    I will present evidence of deep internal order in immune functionality demonstrating that differentiation and immune activities have evolved with a definable “shape”. Further, specific cellular neighborhoods of immune cells are now definable with unique abilities to affect cellular phenotypes—and these neighborhoods alter in various disease states.

    High parameter single cell analysis has driven deep understanding of immune processes.  Using a next-generation single-cell “mass cytometry” platform we quantify surface and cytokine or drug responsive indices of kinase target with 45 or more parameter analyses (e.g. 45 antibodies, viability, nucleic acid content, and relative cell size).  Similarly, we have developed two advanced technologies that enable deep phenotyping of solid tissue in both fresh frozen and FFPE formats (50 – 100 markers).   I will present evidence of deep internal order in immune functionality demonstrating that differentiation and immune activities have evolved with a definable “shape”.  Further, specific cellular neighborhoods of immune cells are now definable with unique abilities to affect cellular phenotypes—and these neighborhoods alter in various disease states.   These shapes and neighborhoods are altered during immune surveillance and “imprinted” during, and after, pathogen attack, traumatic injury, or auto-immune disease.  Hierarchies of functionally defined trans-cellular modules are observed that can be used for mechanistic and clinical insights in cancer and immune therapies.

    Yury Goltsev

    Stanford University

    More information coming!

  • High-throughput 3D Assays

    In this talk we highlight through a series of case studies how these tools enable a variety of applications including organoid models, immune oncology, and hepatotoxicity models.

    Traditional methods for 3D cell culture are often time consuming, display variability, and lack the necessary throughput for screening applications.  To address these concerns we have developed a set of assay plates and flask formats that enable highly reproducible formation and screening of spheroids.  In this talk we highlight through a series of case studies how these tools enable a variety of applications including organoid models, immune oncology, and hepatotoxicity models. Specifically, we show how a novel combination of Spheroid and Transwell plates enables the investigation of immune cell homing, tumor cytotoxicity, and tumor immune evasion in an easy-to-use 3D high throughput assay.  We  highlight the formation of gastrointestinal organoids derived from human induced pluripotent stem cells.  And we demonstrate how primary human hepatocytes models can be improved with these tools to more closely correlate with in vivo toxicity data.

    Anthony Frutos

    Corning Incorporated

    Dr. Anthony G. Frutos was appointed business technology director, Corning Life Science Development in April 2009. In this role, Tony is responsible for Life Sciences product and process development and delivery. Tony holds 19 U.S. patents and is an author on more than 39 technical publications. He holds a bachelor’s degree in chemistry from Brigham Young University and a Ph.D. in analytical chemistry from the University of Wisconsin, Madison. 

  • Current landscape and future opportunities in implementing human microphysiological models in pre-clinical drug development

    The presentation provide a perspective on the breadth of new opportunities available for the integration of 3D human in vitro models within drug discovery and the related challenges in adoption. It will introduce key technological background and advantages/limitations of each novel 3D human in vitro models with examples from recent studies or cases.

    The pharmaceutical industry is facing great challenges still owing to high R&D costs and low overall success rates of clinical compounds during drug development. In phase I clinical trials the majority of failures are due to safety related issues. While more than 50% of failures in phase II and III clinical trial are due to a lack of efficacy and a quarter due to safety issues, where safety includes those failures that were due to an insufficient therapeutic index.  Drug failures in clinical trials are mainly due to the poor translational relevance and clinical predictive power of existing preclinical models which include human cell based in vitro and animal models. The drug discovery community has recognized the critical need for new testing approaches to generate more translatable and reliable predictions of drug efficacy and safety in humans. This has driven the recent advancements in cell biology, tissue engineering, biomaterials, and emerging platforms such as microfabrication, microfluidics and bioprinting in the development of innovative in vitro technologies that more closely recapitulate human tissues and organs. These three dimensional (3D) human in vitro models such as 3D spheroids/organoids, organs-on-chips, and bioprinted tissues could provide the basis for preclinical assays with greater translatability and predictive power. They could be applied for greater insight into mechanisms of human disease, mechanisms of toxicity or for early confirmation of new therapy efficacy. I will provide a perspective on the breadth of new opportunities available for the integration of these 3D human in vitro models within drug discovery and the related challenges in adoption. I will introduce key technological background and advantages/limitations of each novel 3D human in vitro models with examples from recent studies or cases. Furthermore, I will discuss the essential validation process for these 3D human in vitro technology and the importance of integration of various models and the translatability to the clinic. I will conclude by examining how 3D in vitro technology will begin to tackle major technical challenges at the critical steps of conventional and the evolving drug discovery process.

    Jason Ekert

    R&D Platform Technology & Science, GlaxoSmithKline

    Dr Ekert leads an integrated enterprise strategy for sustained, portfolio driven growth in R&D application of complex human-relevant and translatable complex in vitro models. Dr Ekert’s group drives the coordination and prioritization of development and integrated use of complex in vitro technologies for efficacy, safety and biometabolism studies. Dr Ekert received his PhD in Medical Science from Adelaide University in Australia. He performed post-doctoral training at the University of California, Davis and Coriell Institute for Medical Research. Before coming to GSK Dr Ekert worked for 11 years at Janssen BioThereapeutics in early biotherapeutic drug discovery in target discovery, drug validation and mechanism of action studies applying 3D cell cultures, iPSCs and primary cells in complex cell-based assays across multiple therapeutic areas. His current focus at GSK is to improve predictive validity of early preclinical models leading to better characterized molecules, decreased R&D cycle time and a reduction in attrition.

  • Next generation target discovery: systematic application of the CRISPR toolkit

    Forward genetic screening with CRISPR–Cas9 has provided a promising new way to interrogate the phenotypic consequences of gene manipulation in high-throughput, unbiased analyses in target ID, target validation, drug MOA analysis and patient stratification. Diseases previously refractory to systematic high-throughput interrogation are now coming into the cross-hairs of powerful new functional genomic solutions.

    Forward genetic screening with CRISPR–Cas9 has provided a promising new way to interrogate the phenotypic consequences of gene manipulation in high-throughput, unbiased analyses in target ID, target validation, drug MOA analysis and patient stratification. Diseases previously refractory to systematic high-throughput interrogation are now coming into the cross-hairs of powerful new functional genomic solutions. To date, the majority of screens have been conducted using loss-of-function perturbation driven by CRISPR–Cas9 enacted gene knock-out. Although powerful, this approach does not allow for the examination of activating gene function, leaving a salient gap in the functional genomic analysis. In order to add depth to our discovery platforms, we have constructed new platforms using both CRISPRi and CRISPRa transcriptional regulation tools. Both of these platforms have been adapted to use next generation, highly optimised whole-genome targeting libraries in order to enact maximum gene expression modulation. Our validation analysis of these approaches revealed outstanding performance and sensitivity, with greater than ten-fold improvement in detection rates compared to existing tools.

    Screening for drug resistance with this dual platform yields unambiguous target discovery and simultaneous evaluation of both activating and inhibiting perturbations reveals direct and opposing phenotypic effects within complex gene networks. Thus, in contrast to loss-of-function-only analysis, these tools can switch the response of affected cells to either sensitisation or resistance allowing the discovery of key genes which sit in the centre of the hit nexus. These findings demonstrate the unique power of bi-directional functional genomic screening approaches.

    The application of these tools to new therapeutic areas is expected to yield crucial new target ID. A major global research focus is in immuno-oncology and the discovery of new immuno-oncology drug targets, including those that alter the character and frequency of T-cell-mediated anti-tumour responses. Although we and others have been able to develop tools that allow highly efficient gene editing of primary T-cells by CRISPR–Cas9, the application of pooled functional genomic screening to primary T-cells has proved a technological hurdle. We have optimised and substantially adapted our pooled CRISPR screening platform to the particular challenge of primary T-cell biology and we will present an update on this promising new capability.

    Benedict Cross

    Horizon Discovery Ltd

    After completing his PhD, Ben trained as a post doc at the University of Cambridge. Here his focus was reverse chemical genetic screening, uncovering a novel mechanism for inhibition in the unfolded protein response. Ben joined Horizon in 2013 to expand and develop Horizon’s functional genomics platforms and to lead a major research alliance in synthetic lethal target discovery. Ben now leads and manages Horizon’s functional genomic screening group.

  • New Functional Genomics toolsets: Arrayed loss of function screening with LentiArray CRISPR libraries

    Here we demonstrate a knock-out screening approach that utilizes the Invitrogen™ LentiArray™ CRISPR library to interrogate the impact of individual gene knock-outs on the NFκB pathway as measured by a functional cell-based assay. We describe the library design concepts, the assay development, initial screening results and validation of specific identified hits.

    Identifying and validating targets that underlie disease mechanisms and can be addressed to provide efficacious therapies remains a significant challenge in the drug discovery and development process.  Mechanisms of RNAi have provided the use of siRNA and shRNA to knock-down RNA and suppress gene function.  However, depending on the nature of the targets, cells, biology and end-point assays, these approaches may suffer variously from their transient nature, design complexity, incomplete knock-down or off-target effects.  The use of CRISPR (clustered regularly interspaced short palindromic repeat)-associated Cas9 nuclease and guide RNA (gRNA) provides a strong alternative that can produce transient or long-lasting impact, straightforward design, knock-out of genes and increased specificity.  A number of laboratories have already published reports demonstrating how pools of gRNA can be delivered to cells and “hits” can be established through enrichment or depletion of cells following a “survival” assay and identified by sequencing the introduced gRNAs in the remaining cell population.  Here we demonstrate a knock-out screening approach that utilizes the Invitrogen™ LentiArray™ CRISPR library to interrogate the impact of individual gene knock-outs on the NFκB pathway as measured by a functional cell-based assay.  We describe the library design concepts, the assay development, initial screening results and validation of specific identified hits. We elucidate the key factors in developing a robust assay including both transduction and assay optimization to achieve the highest levels of transduction efficiency and assay window and provide data from initial screens using the Invitrogen™ LentiArray™ CRISPR kinome library.  We expect these approaches to be scalable to the entire human genome and portable to multiple cell types and end-point assays including both high-throughput plate-based assays and high-content imaging based assays.

    Jon Chesnut

    Thermo Fisher Scientific

    Cell and Molecular Biology, Genome Editing.

  • HIPStA, a High Throughput Alternative to CETSA

    This presentation reviews data demonstrating the proof of concept for the HIPStA method, using 3 different classes of drug discovery targets: Receptor tyrosine kinases, Nuclear Hormone Receptors and Cytoplasmic Protein Kinases. HIPStA represents a more scale-able alternative to CETSA for detecting drug-target interaction in cells.

    The measurement of drug – target interaction in the cellular context is critical to many drug development programs. The Cellular Thermal Stability Assay (CETSA) represents an established broadly applicable method for measuring drug target interaction. However CETSA has some major limitations that make it difficult to scale to the throughput typically required for a drug development project. It requires heating samples to different temperatures and centrifugation and / or filtration steps which limit throughput. The HSP90 Inhibitor Protein Stability Assay (HIPStA) is a novel method for measuring drug target interaction. Like CETSA, HIPStA is based on the premise that the binding of a ligand to a target protein can influence that protein’s stability. Instead of using heat to destabilize a protein, HIPStA uses a Heat Shock Protein 90 inhibitor (HSP90i) to cause protein instability. Instead of scanning a range of different temperatures to establish a thermal denaturation curve, HIPStA applies a range of concentrations of an HSP90i to determine an HSP90i induced denaturation curve, and ultimately measures the ability of a compound to stabilize a protein. We present data demonstrating the proof of concept for the HIPStA method, using 3 different classes of drug discovery targets: Receptor tyrosine kinases, Nuclear Hormone Receptors and Cytoplasmic Protein Kinases. HIPStA represents a more scale-able alternative to CETSA for detecting drug-target interaction in cells.

    Robert Blake

    Genentech

    Robert A. Blake (DPhil) is a scientist in drug and target discovery specializing in oncology drug development, cellular and biochemical assays for high throughput screening, automated fluorescence imaging, signal transduction and protein degradation. He is currently a scientist in the department of Biochemical and Cellular Pharmacology at Genentech and worked previously at Sugen, Exelixis, and iPierian. He has published on the discovery of novel selective kinase inhibitors including the Src inhibitor SU6656, HSP90 inhibitors, high content fluorescence imaging based methods and was a member of the team that developed SUTENT (SU11248). His current focus is the development of drugs whose mechanism of action includes the degradation of the target protein. 

  • Large scale profiling in human primary-cell based phenotypic assays identifies novel outcome pathways for drug efficacy in cardiovascular disease

    Findings support the value of a large chemical biology database of reference drugs profiled through primary human cell-based phenotypic assays. This database has been mined to reveal several novel associations with adverse events and identified potential mechanisms of toxicity, and here we show how this database can be used to generate new hypotheses for drug efficacy.

    We have previously identified an in vitro signature, characterized by increased cell surface levels of serum amyloid A (SAA) in a human primary cell-based coronary artery smooth muscle cell model of vascular inflammation (BioMAP CASM3C system), shared by certain compound classes associated with cardiovascular toxicity. Data mining a large reference database containing more than 4,500 test agents (drugs, experimental chemicals, etc.) profiled in this assay identified certain mechanisms to be associated with this signature:  MEK inhibitors, HDAC inhibitors, GR/MR Agonists, IL-6 pathway agonists, as well as modulators of SIRT1.  Since SAA is a clinical biomarker associated with risk of cardiovascular disease in humans, these results suggested that these mechanisms might contribute to cardiotoxicity by direct promotion of vascular dysfunction through SAA within vascular tissues. To further extend these studies, we mined the reference database to identify agents that decrease levels of SAA in the BioMAP CASM3C system without causing overt cytotoxicity. Notable agents that were found to decrease the cell surface level of SAA relative to vehicle control include GLP-1, an endogenous peptide developed as a drug used for treatment of diabetes, roflumilast, a PDE IV inhibitor used for the treatment of chronic obstructive pulmonary disorder, the BCR-Abl inhibitor and oncology drug, imatinib, and a mimetic of ApoA-1, the major lipoprotein of HDL.  These represent agents that have been shown to have cardiovascular protective effects in clinical or in vivo studies (some within their class).  The results here suggest a potential mechanism for this cardiovascular benefit through regulation of SAA, possibly through interfering with the involvement of SAA in the recruitment and activation of monocytes in the vascular wall. These findings support the value of a large chemical biology database of reference drugs profiled through primary human cell-based phenotypic assays.  This database has been mined to reveal several novel associations with adverse events and identified potential mechanisms of toxicity, and here we show how this database can be used to generate new hypotheses for drug efficacy.  Collectively these data support a disease and adverse outcome pathway for cardiovascular disease involving the regulation of SAA.

    Ellen Berg

    DiscoverX Corporation

    Ellen L. Berg, PhD, is Chief Scientific Officer at DiscoverX, BioMAP Division. She held prior positions at BioSeek and Protein Design Labs, earned her PhD from Northwestern University and was a postdoc at Stanford University. She is an SLAS fellow (Society for Laboratory Automation and Screening), a board member of ASCCT (American Society of Cellular and Computational Toxicology), and a member of the Society of Toxicology (SOT) and the Inflammation Research Association (IRA). Her research interests include human-based in vitro models of tissue and disease, chemical biology for predicting drug and toxicity mechanisms of action and phenotypic drug discovery.  Dr. Berg holds a number of patents in the field of inflammation and has authored >80 publications. 

  • Open development from user to vendor and back again; how everybody wins

    This presentation will discuss how this ‘overlap’ can be leveraged to produce better products, better interaction and better results for all parties. This presentation will explore opportunities to further these aims and bring the supplier and user of everyday laboratory equipment together.

    The ‘vendor’ community and ‘user’ community are today becoming commonly intertwined; with the user community taking advantage of modern prototyping and manufacturing technologies such as 3D printing, micro-controllers and laser cutting. In addition; the vendor community is often using these technologies to producing products.  This means that there is a significant overlap such as we have never seen before.

    The presenter has previously worked in the instrument user community at major pharmaceutical companies, large biotech, startup biotech and academia.  During this period a close collaborative relationship between the user and supplier lead to improved performance of the equipment purchased and increased reliability.  Now the same person runs an instrument company which sells to the end user and we now see the other side of the coin – how to support the equipment in the field as a manufacturer.  Concepts such as printing your own spare parts and even the concept of flat pack style delivery will be explored.  In addition the reality of this will be discussed; issues such as giving out the design for internal parts of a product could leave a company’s designs open to be reused by a competitor and in addition also there is a degree of willingness by the user of the equipment to do the repairs by themselves.

    This presentation will discuss how this ‘overlap’ can be leveraged to produce better products, better interaction and better results for all parties.  This presentation will explore opportunities to further these aims and bring the supplier and user of everyday laboratory equipment together.

    Neil Benn

    Ziath

    Neil is co-founder and Managing Director of Ziath.  Since 1994, Neil has experience with a range of companies; GlaxoSmithKline; Cambridge Antibody Technology, Cenix Bioscience GmbH and the Max Planck Institute of Cell Biology and Genomics. Within these companies Neil has been responsible for the development, maintenance and implementation of laboratory automation and associated software with a focus on process control and information management.

    Neil has served on the board of the European Laboratory Robotics Interest Group (ELRIG) in both Germany and the UK. He was the informatics chair for Lab Automation 2009, has edited for the Journal for the Association for Laboratory Automation and also serves on the board of The Journal for Laboratory Automation. Neil has a Bachelor’s degree in Biotechnology and a Master’s degree in Computer Science.

  • Inline, Label-free Detection Using the Droplet Frequency Sensor

    ​Inline detectors are extensively used in chemical separations and other life sciences workflows to quantify analytes based on fundamental properties.

    Inline detectors are extensively used in chemical separations and other life sciences workflows to quantify analytes based on fundamental properties.  For example, absorbance (UV-VIS) detectors measure the analyte’s light-absorbing chromophores, refractive index (RI) detectors measure molecular cross section, and electrochemical (EC) detectors and mass spectrometers (MS) measures the analyte’s charge or mass to charge ratio.  Although hydrophobicity and solubility are important properties of an analyte, to date there are no inline detectors based on such properties.  Here, we present the drop frequency sensor (DFS), a novel inline detector which quantifies an analyte based on its adsorption to a liquid interface.  

    The DFS is based on the surfactant retardation effect, a phenomenon first described by Levich in the 1960s.  Levich observed that the velocity of a rising bubble is lower than expected if surfactants are present.  Surfactants adsorb to the bubble’s interface, and surface flows convect them to the trailing end, where they aggregate into a stagnant cap.  The cap has two effects, both of which increase drag: 1) the interface becomes immobile, and 2) the nonuniform surfactant concentration results in a surface tension gradient, which induces a Marangoni force opposing the motion of the bubble.  The DFS exploits a similar effect in droplets flowing through a microchannel.  Droplets of the analyte are generated by combining the sample stream with a stream of oil in a microfluidic tee junction.  If the droplet contains hydrophobic molecules or other surface-active species, the molecules adsorb to the interface and are convected to the trailing end, similar to Levich’s experiments.  Here, they form a stagnant cap which increases drag on the droplet train, and therefore increases channel’s hydrodynamic resistance. In a pressure-driven system, the increased resistance reduces flow rate as well as the frequency of drop generation.  The droplet frequency is measured with a light scattering detector.

    The DFS demonstrates excellent quantitation capability for Bovine Serum Albumin (BSA), a globular protein with known hydrophobic regions.  Injection of BSA into the analyte stream temporarily reduces the drop frequency, and the frequency returns to baseline, generating a chromatographic peak.  The peak area increase linearly with the quantity of injected BSA with a correlation coefficient R2=0.997.  This process is highly repeatable, which is important for measurement precision.  The limit of detection for BSA is 2ng, and  < 200pg for L-galectin, a hydrophobic protein with smaller molecular weight.  The high signal-to-noise ratio suggests that even lower detection limits are possible.  The low detection limits are achieved because the high surface area to volume ratio favors adsorption phenomena.

    Amar Basu

    Wayne State University

    Amar Basu received a BSE and MSE in electrical engineering, an MS in biomedical engineering, and a Ph.D. in electrical engineering, all with honors from the University of Michigan Ann Arbor.  His dissertation, under Prof. Yogesh Gianchandani at the NSF Center for Wireless Integrated Microsystems, investigated interfacial tension-driven microfluidics.  He has been a visiting scholar at Purdue University under Prof. Graham Cooks and Intel's New Devices group, and has served as an adjunct faculty at the University of Michigan.  Amar is currently associate professor of electrical engineering and biomedical engineering at Wayne State University.  His research, supported primarily by the NSF, focuses on microfluidic and microelectronic instrumentation for high-throughput screening and point of care monitoring.  He received the NSF BRIGE award, WSU CoE Outstanding Faculty Award, the IEEE-WSU Professor of the Year, and the Whitaker Foundation Fellowship.  More information about his lab can be found at www.microfluidics.wayne.edu.

  • In-house software and processes to support High Content Screening of Primary Neurons

    This presentation will focus on the development and implementation of novel in-house software utilities used at Scripps Florida to support the Synaptogenesis neuroscience drug discovery project.

    The integration of High Content Screening (HCS) devices onto High Throughput Screening (HTS) platforms to support neuroscience research presents unique challenges for drug discovery teams. In particular, the informatics aspect of HCS applied to neuroscience is an area where advances in software automation can result in substantial throughput and efficiency gains for researchers. In addition to the data processing and storage requirements of HCS above traditional HTS readers, neuroscience assays present a number of unique challenges for the HTS environment. These challenges include ensuring data integrity from acquisition through analysis & QC, porting data between multiple distinct HCS platforms and providing end-user analytic tools for ongoing intermediate assay results.

    This presentation will focus on the development and implementation of novel in-house software utilities used at Scripps Florida to support the Synaptogenesis neuroscience drug discovery project. This project utilizes multiple HCS platforms, has an ongoing non-traditional HTS timeline and requires on-demand access to the full HCS data stream, from raw source images to final endpoint results. The biology of the Synaptogenesis project is currently amenable to 384 well format while the Scripps Florida uHTS platform is optimized for 1536 well screening. Supporting a HTS campaign where the compound collection resides in a different plate density than the assay plate required the development of custom robotic and informatics procedures. The Synaptogenesis endpoint calculation requires measurements at DIV 12 and DIV 14 where each assay plate is represented by 3,072 images (384 wells at 4 images per well for each of two separate reads) which must be associated with relevant metadata (plate barcode, well row, well column and well quadrant) for downstream tracking. Previous neuroscience assays in this format were not amenable to robotics screening and were limited in throughput. To date, we have successfully screened a large portion (greater than 40,000 compounds) of the Scripps Drug Discovery library, in quadruplicate, iteratively over a 9 month period.

    To meet these challenges, custom software tools have been developed which enables scientists to manage what would otherwise be an overwhelming amount of data.  These tools include a web based portal that allows end users to easily review HCS neuroscience data as it comes off the HTS platform and to quickly drill down on endpoint data back to the images acquired by the reader. The advantages of developing in-house informatics over commercial products and the impact of these tools on the ongoing neuroscience research at Scripps Florida is presented.

    Pierre Baillargeon

    Scripps Florida

    Pierre established the Compound Management team within the Lead Identification/HTS group at Scripps Florida when the lab was established in 2005. The Compound Management team is responsible for supporting both industrial and academic drug discovery efforts with a proprietary >600,000 sample library and the NIH's >300,000 sample MLPCN collection. Aside from typical Compound Management duties, Pierre has developed, assembled and integrated novel automated hardware and software for the purpose of drug discovery.

  • The Ig Nobel Prizes: The Fine Line Between Sound and Silly Science

    The Ig Nobel Prizes are renowned as a spoof alternative to the Nobel Prizes. The annual Ig Nobel awards ceremony is a celebration of curious, imaginative studies that make people laugh. Yet while studies of cats behaving like liquids or frogs levitating inside of a magnet might have you chortling, its founder Marc Abrahams has an equally important purpose in mind for the Prizes: to get you to think.

    The Ig Nobel Prizes are renowned as a spoof alternative to the Nobel Prizes. The annual Ig Nobel awards ceremony is a celebration of curious, imaginative studies that make people laugh. Yet while studies of cats behaving like liquids or frogs levitating inside of a magnet might have you chortling, its founder Marc Abrahams has an equally important purpose in mind for the Prizes: to get you to think. Once something becomes generally understood and accepted, then it comes to be seen as serious and important. Almost everybody either forgets or doesn’t become aware that this thing started out as something that everyone else regarded as nuts! Any scientific discovery seems like such an easy thing after it has been discovered, and it almost never was. Your understanding of a study might change – drastically – if you spend time looking at its details!

    Marc Abrahams

    Co-founder/Editer, Annals of Improbable Research

    Marc Abrahams writes about research that makes people LAUGH, then THINK. Marc founded Ig Nobel Prize Ceremony in 1991, and serves as its Master of Ceremonies. He co-founded and edits the magazine Annals of Improbable Research (AIR), hosts the Improbable Research weekly podcast (distributed by CBS), and wrote This is Improbable, The Ig Nobel Prizes, and other books. He edits and writes much of the web site and blog www.improbable.com, and the monthly newsletter mini-AIR.

  • High-throughput imaging and selection of viable clones in line with single cell sorting improves viability of clones for downstream analysis

    An FDA requirement for biologics production is to provide evidence that the host cell line being employed is derived from a single, parental cell (i.e. monoclonal). Here we present the optimization of a microfluidics-based method—the single cell printing method—for imaging and screening of clones prior to single cell sorting, which significantly improved cell viability compared to other cell sorting techniques.

    An FDA requirement for biologics production is to provide evidence that the host cell line being employed is derived from a single, parental cell (i.e. monoclonal). Conventional techniques for isolating single cells such as limiting dilution and flow cytometry-based methods are significantly limited by process inefficiencies, including low plating densities and low viabilities. These inefficiencies, in turn, reduce the capability to screen for high-producing clones, thereby increasing timelines and costs at early stages of antibody discovery and cell line development processes.  Microfluidics-based methods hold promise for improving upon such inefficiencies due to their ability to sort single cells in a low stress environment. Here we present the optimization of a microfluidics-based method—the single cell printing method—for imaging and screening of clones prior to single cell sorting, which significantly improved cell viability compared to other cell sorting techniques.

    Steven Wiltgen

    Molecular Devices

    My PhD and post-doc focused on the development of a novel super-resolution imaging technique based on TIRF imaging of calcium permeable ion channels. I then served as an Adjunct Professor at several community colleges in the Southern California region before beginning my career at Molecular Devices 4 years ago.  I first served as a Field Application Scientist for our high-content imaging products, then switched gears to marketing where I served as an application scientist for our bioproduction development line of products.  I now serve as the product manager for these same instruments and have been in this role for 1 year.

  • Hit Triage and Mechanism Validation for Phenotypic Screening: Considerations and Strategies

    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.

    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. 

    Fabien Vincent

    Pfizer

    Fabien Vincent, Ph.D., is Associate Research Fellow in the department of Hit Discovery and Lead Profiling at Pfizer.  He received a Diplome d’Ingenieur in organic chemistry from CPE Lyon (France) before conducting graduate research in the fields of chemical biology and enzymology in the laboratory of Pr. Harold Kohn at the University of Houston. He later became a post-doctoral fellow in chemical biology at the Genomics Institute of the Novartis Research Foundation in San Diego. Fabien Vincent then entered the field of drug discovery as both a research project leader and molecular pharmacology group leader. His main research interests are centered on improving the translation of pre-clinical research to patients and specifically include physiologically relevant assays, phenotypic screening and atypical molecular mechanisms of action. 

  • A Low-Cost Open-Source Cloud-based Liquid Handling Robotic Platform for Performing Remote Real-Time Collaborative Experiments

    We have developed a robotic-system capable of performing routine liquid-handling experiments, as well as artificial chemical life experiments. Our platform consists of an actuation-layer on top, an experimental-layer in the middle, and a sensing-layer at the bottom. The actuation-layer comprises the robot-head and modules mounted on it.

    We have developed a robotic-system capable of performing routine liquid-handling experiments, as well as artificial chemical life experiments. Our platform consists of an actuation-layer on top, an experimental-layer in the middle, and a sensing-layer at the bottom. The actuation-layer comprises the robot-head and modules mounted on it. The modules, e.g. pipet-modules, OCT-scanner, extruder, PH-probe, are designed to perform actions on experiments. The head holds modules and moves in the horizontal plane. The experimental-layer holds the reaction vessels. The sensing-layer consists of a camera below the experimental-layer to monitor the experiment. It collects data from experiment, and provides feedback for robot to interact with experiment. 

    To develop an open-source multi-platform user-interface for remote real-time control of our robotic-system, we decouple user software for programing experiments from robot control-software. Therefore, we use an integrated controller-hardware, namely a Raspberry-Pi3 single-board computer, instead of a dedicated computer. The resulting platform eases software management as installing, and managing software libraries required for feedback-based experiments on different hardware, and operating-systems was difficult. Furthermore, it is affordable owing to the low cost of Raspberry-Pi. This approach also enables us to implement a cloud-based software architecture for our platform. 

    The cloud-based software architecture for our robotic-system provides resource sharing and reusability of experiment protocols, the ability to work on the robotic-system collaboratively, and parallelizing experiments on different robotic-systems. Sharing resources allows users to benefit from experiment protocol-templates provided for common experiments, and also protocol-examples developed by other users. This is specifically helpful as our liquid-handling robot can be used for numerous applications by different users, therefore sample experiment-protocols can save a significant amount of time for the user-community. Collaboration on robotic-platforms, i.e. multiple users can work on the same experiment simultaneously, provides novel opportunities for researchers. On the user-interface, they see changes other users are making to the experiment protocol real-time. They can modify the same experiment as a team, or receive notifications regarding experiment progress. Moreover, users can continue to work on the same experiment on another machine. Finally, parallelizing experiments improves efficiency, specifically for artificial-chemical-life experiments, as several long-lasting experiments are performed on multiple-platforms.  

    A cloud-based implementation of the user-interface of our robotic-platform is a paradigm shift from single-user single-platform concept to single-user multi-platform, multi-user single-platform, and multi-user multi-platform approaches. A single-user multi-platform paradigm, i.e. a user being able to control several robotic-systems at the same time, and run the same code on multiple-robots, allows for a high degree of parallelism. A multi-user single-platform, i.e. several users can work on the same robot simultaneously, provides a great potential for collaboration on the robotic-platform. A multi-user multi-platform approach, i.e. several users, e.g. a team, being able to work on multiple-robots, enhances resource sharing, and reusability of experiment-protocols.

    Kasper Stoy

    IT University of Copenhagen

    More information coming!

  • Towards a comprehensive strategy to target identification and mode of action elucidation for bioactive small molecules

    ​Target identification and the elucidation of mechanism of action (MoA) for bioactive small molecules are key steps in phenotypic and pathway-centric approaches to drug discovery. In recent years, various strategies have been introduced and refined that address these questions from different angles and provide glimpses of different aspects of the often complex physical and functional interactions of a compound when exerting its biological effects in vivo.

    Target identification and the elucidation of mechanism of action (MoA) for bioactive small molecules are key steps in phenotypic and
    pathway-centric approaches to drug discovery. In recent years, various strategies have been introduced and refined that address these
    questions from different angles and provide glimpses of different aspects of the often complex physical and functional interactions of
    a compound when exerting its biological effects in vivo: Affinity-based approaches aim to describe the (protein) interactome of drug
    candidates which constitutes the full spectrum of potential efficacy and off-targets. These include quantitative chemoproteomics such
    the combinations of small molecule affinity chromatography or photo-affinity labeling with mass spectrometry-based protein
    identification and quantitation, as well as large scale implementations of biophysical approaches in vitro such as size-exclusion
    chromatography. On the other hand, a variety of functional genetic and genomic strategies have been introduced that include
    (unbiased or targeted) generation of compound-resistant cells followed by identification of the resistance-conferring genetic changes
    by next generation sequencing as well as the utilization of genome-wide knock-down and deletion approaches including RNAi and
    CRISPR. In these cases, the generation of target/MoA hypotheses is based on the elucidation of functional relationships between a
    gene and the compound-induced phenotype. In contrast to the individual protein or gene resolution provided by these former
    strategies, cellular profiling approaches interrogate the overall cellular response to compound treatment at the level of signaling, gene
    expression, viability or metabolism. Finally, knowledge-based approaches rely on empirical and computational approaches and a
    reference collection of compounds with known targets and MoA to make inferences. Since the various approaches provide orthogonal
    information and have unique strengths, multipronged strategies are best suited to provide a comprehensive picture of the target/MoA
    space of a bioactive compound and ultimately enable successful elucidation of the efficacy target and its functional link to the
    phenotype under investigation. The various classes of target ID platforms will be presented and discussed in the context of real-life
    applications.

    Markus Schirle

    Novartis Institutes for Biomedical Research

    Markus Schirle received his master’s degree in biochemistry at University of Tubingen, Germany and his Ph.D. in 2001 for his work with H.G. Rammensee/Tubingen on the identification of disease-associated MHC peptides by mass spectrometry-based approaches. After postdoctoral studies in proteomics with Alfred Nordheim/Tubingen, he joined Cellzome (Heidelberg, Germany, now part of GSK) from 2001 – 2007 where his work focused on protein and small molecule affinity proteomics for target identification (ID) and mechanism of action (MoA) studies. Since joining Novartis in 2007, he established a platform for chemical and affinity proteomics for target ID and MoA studies; since 2013 he is group leader for the ChemGx hub which also covers biophysical and biochemical in vitro methods for studying protein–compound interactions. The hub is responsible for affinity-based approaches to target ID/MoA and hit finding for Novartis drug discovery projects globally.

  • UPT and SCLS, two unique workflow for Drug Target Identification

    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.

    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. 

    Chaitanya Saxena

    Shantani Proteome Analytics Pvt. Ltd.

    With 12+ years of experience in utilizing biophysical techniques to solve the relevant problems in life sciences, Chaitanya is a seasoned drug discovery professional. Chaitanya completed his Ph.D. in Biophysics from Dept. of Physics, The Ohio State University, Columbus, Ohio, USA and later worked with Eli Lilly and Company at Indianapolis. Presently he is serving as Chief Executive Officer at Shantani Proteome Analytics Pvt. Ltd. (Shantani), a wet-lab technology based company founded by him and Dr. Yanping Yan at Venture Center, National Chemical Laboratory Innovation Park, Pune, India. Shantani provides drug target deconvolution technologies to drug discovery organizations and proteomics and protein chemistry based path-forward solutions to bio-pharma and other life-sciences based companies. Chaitanya has published several scientific articles in divers’ scientific areas ranging from the Femto-second electron transfer processes in biology to the applications of Mass Spectrometry in drug-discovery.

  • A Quantitative Target Engagement Approach to Profile Compound Affinity and Residence Time Across Enzyme Classes In Live Cells

    Intracellular target selectivity is fundamental to pharmacological mechanism. Although there are currently a number of acellular techniques to quantitatively measure target binding or enzymatic inhibition, no biophysical approach exists that offer quantitative, equilibrium-based analysis of target engagement across enzyme classes in live cells. Here we report the application of an energy transfer technique (NanoBRET) that enables the first quantitative approach to broadly profile target occupancy, compound affinity, and residence time for a variety of target classes including kinases and chromatin modifying enzymes.

    Intracellular target selectivity is fundamental to pharmacological mechanism. Although there are currently a number of acellular techniques to quantitatively measure target binding or enzymatic inhibition, no biophysical approach exists that offer quantitative, equilibrium-based analysis of target engagement across enzyme classes in live cells. Here we report the application of an energy transfer technique (NanoBRET) that enables the first quantitative approach to broadly profile target occupancy, compound affinity, and residence time for a variety of target classes including kinases and chromatin modifying enzymes. The NanoBRET method allows for broad kinome profiling of inhibitor selectivity against nearly 200 kinases, and enables a mechanistic interrogation of the potency offsets observed between cellular and acellular analysis. Compared to published biochemical profiling results, we observed an improved intracellular selectivity profile for certain clinically-relevant multi-kinase inhibitors. Due to high levels of intracellular ATP, a number of putative drug targets are unexpectedly disengaged in live cells at a clinically-relevant drug dose. The energy transfer technique can also be performed in real time, allowing for measurements of drug residence time. Broad kinase profiling of compound residence time reveals surprising kinetic selectivity mechanisms.

    Matthew Robers

    Promega Corporation

    Matthew Robers is a Senior Research Scientist and Group Leader at Promega Corporation. Matthew received his B.A. Degree in the Dept of Genetics and his M.S. Degree in the Dept of Bacteriology at the University of Wisconsin - Madison. Matthew has authored over 20 peer-reviewed publications and published patents on the application of novel assay chemistries to measure intracellular protein dynamics. Matthew's team currently focuses on the development of new technologies to assess target engagement, and has developed a biophysical technique for quantifying compound affinity and residence time at selected targets within intact cells.

  • ExVive™ 3D Bioprinted Tissue Modeling of Liver Injury and Disease In Vitro

    Here we characterize progression of TGFβ-mediated induction of fibrosis and blockade by Galunisertib as evidenced by key biomarkers, cytokine production, regulation of fibrotic genes, and collagen deposition, collectively demonstrating the utility of the model for the evaluation of interventional strategies and providing evidence of clinically relevant pathway modulation in vitro.

    Successful prediction of candidate drugs can be hampered by the lack of in vitro tools to model complexities of human tissue biology.  This translational challenge can result in low safety and efficacy predictability and contribute to attrition in drug development.  To bridge this gap, the Organovo NovoGen® Bioprinting Platform was utilized to develop ExVive™ 3D Bioprinted Tissues, fully cellular 3D tissue models fabricated by automated spatially controlled cellular deposition.  The multicellular architecture of the 3D model can better recapitulate native tissue structure and function compared to standard in vitro models, allowing for complex, tissue-level phenotypes associated with chronic injury and disease.  Biochemical and histological characterization demonstrates that ExVive™ Human Liver Tissue enables detection of compound-induced progressive liver fibrogenesis.  Here we characterize progression of TGFβ-mediated induction of fibrosis and blockade by Galunisertib as evidenced by key biomarkers, cytokine production, regulation of fibrotic genes, and collagen deposition, collectively demonstrating the utility of the model for the evaluation of interventional strategies and providing evidence of clinically relevant pathway modulation in vitro.

    Kelsey Retting

    Organovo Inc.

    Kelsey Retting is an Associate Director at Organovo Inc. designing functional human tissues using proprietary three-dimensional bioprinting technology.  Prior to Organovo, Kelsey worked in drug discovery at Pfizer supporting the development of novel biotherapeutics for metabolic disease.  Kelsey has a PhD from the University of California, Los Angeles in Biological Chemistry.

  • Label-free Raman spectroscopy for rapid identification of biologics

    We have developed partial least squares-discriminant analysis derived decision algorithms that provide near-perfect classification accuracy in predicting the identity of these drugs based on the subtle, but consistent, differences in their spectra, which are otherwise invisible to gross visual inspection. We have shown that the performance of the decision algorithm with plasmon-enhanced Raman spectroscopy, even at much lower biologic concentrations, is comparable with that of spontaneous Raman spectroscopy. Together, these results establish the feasibility of developing an automated non-perturbative spectroscopic pipeline for rapid identification and quality control during manufacturing and fill-finish testing of biologics – thus alleviating the principal limitations of conventional wet chemistry analyses.

    Monoclonal antibody based biologics are gaining immense popularity as therapeutic agents to treat a wide array of diseases such as cancer and inflammation. As a result, increasing number of biologics are currently undergoing clinical development and approval for clinical translation. Such a rise in demand for biologics necessitate the development of rapid, label-free and automated characterization tools for meeting stringent quality control requirements during their manufacturing. To meet regulatory requirements and reduce business risk associated with fill operations, accurate identification of the drug products is a critical and necessary analysis during multiple stages of manufacturing and distribution. However, due to high similarity in the chemical structures of these drugs, establishing product identification is challenging and the traditional wet lab techniques are destructive, labor intensive and expensive to perform multiple times during production and, even more so, for fill finish testing. Therefore, there is an urgent need for quick, inexpensive and reliable methods for biologics identification. Here, we report the first application of spontaneous and label-free plasmon-enhanced Raman spectroscopy coupled with multivariate data analysis for identification of a cohort of closely related human and murine antibody drugs. Building on finite difference time domain simulations, we synthesized nanoparticles of optimal morphology to compare the feasibility of performing SERS-based bulk sample detection with that of spontaneous Raman spectroscopy. We have developed partial least squares-discriminant analysis derived decision algorithms that provide near-perfect classification accuracy in predicting the identity of these drugs based on the subtle, but consistent, differences in their spectra, which are otherwise invisible to gross visual inspection. We have shown that the performance of the decision algorithm with plasmon-enhanced Raman spectroscopy, even at much lower biologic concentrations, is comparable with that of spontaneous Raman spectroscopy. Together, these results establish the feasibility of developing an automated non-perturbative spectroscopic pipeline for rapid identification and quality control during manufacturing and fill-finish testing of biologics – thus alleviating the principal limitations of conventional wet chemistry analyses.

    Santosh Paidi

    Department of Mechanical Engineering, Johns Hopkins University

    Santosh Paidi is a graduate student in the Department of Mechanical Engineering at Johns Hopkins University. His current research efforts in Dr. Ishan Barman’s lab are directed towards application of Raman spectroscopy and multivariate data analysis to develop novel quantitative approaches for addressing unmet needs in life sciences. A major focus of Santosh’s graduate study is the development of non-perturbative tool for rapid identification of closely related biologics in real time during their manufacturing, with the ultimate goal of translation to fill-finish sites. Prior to commencing graduate study at Johns Hopkins University, Santosh obtained a B.Tech in Mechanical Engineering and a minor in Aerospace Engineering from Indian Institute of Technology Bombay.

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

    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).

    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.

    Jon Oyer

    Abbvie

    Jon Oyer works within the Target Identification & Validation group of the Genomic Research Center at AbbVie. This group specializes in applying a diverse stack of technologies and methods to the challenge of small molecule characterization. A partial list of these collaborative efforts include transcriptome analysis, proteomics, phage display, cellular thermal shift assays, and functional genomic approaches. Jon received his undergraduate degree from University of Washington before completing his graduate studies in Molecular & Medical Genetics at Oregon Health & Science University. Prior to joining AbbVie, Jon also conducted postdoctoral research studying epigenetic regulation in embryonic stem cells with Gail Mandel at Oregon Health & Science University and epigenetic disruptions that drive hematological malignancies with Jonathan Licht at Northwestern University.

  • A high-throughput arrayed CRISPR/Cas9 functional genomics approach to study NF-kB signaling

    We undertook an array-based CRISPR/Cas9 screen at 800 kinome-scale to investigate mediators of TNFα-mediated NF-κB activation. Our results demonstrate the potential for genome-scale screens at high specificity using CRISPR/Cas9 and in a wide variety of cell backgrounds and phenotypes.

    CRISPR/Cas9 is increasingly being used as a tool to prosecute functional genomic screens.  Array-based CRISPR/Cas9 screens offer the ability to interrogate more diverse phenotypes than pool-based screens but their execution at scale in difficult to transfect cells brings challenges.  We undertook an array-based CRISPR/Cas9 screen at 800 kinome-scale to investigate mediators of TNFα-mediated NF-κB activation.  We used an ME180 cell line stably expressing Cas9 and a beta-lactamase reporter of Nf-κB activation alongside a developed lentiviral sgRNA library.  Hits were validated by confirmation of DNA insertion/deletion and screening orthogonal reagents.  Screening data quality was within acceptable limits (Z’>0.6) and genes associated with canonical NF-κB signalling were identified.  Our data provide unique insights into approaches and tools to explore novel biology with array-based gene editing in cellular assays.  Our results demonstrate the potential for genome-scale screens at high specificity using CRISPR/Cas9 and in a wide variety of cell backgrounds and phenotypes.

    Patrick O'Shea

    Astrazeneca

    Patrick O'Shea is a Senior Scientist in the High Content Biology group within Discovery Sciences at AstraZeneca in Cambridge UK; a multidisciplinary R&D unit with a global remit. The team develops novel phenotypic assays and uses high-content and functional genomic approaches to understand novel biology, provide an early insight into compound toxicity, and to characterize compound mechanism of action in disease relevant models. Prior to joining AstraZeneca, Patrick studied Pharmacology at the University of Leeds. He completed a PhD at Imperial College London, studying the developmental effects of thyroid hormones in bone and cartilage, and was a postdoctoral fellow at Imperial College London and at the National Cancer Institute, NIH. 

  • Protein quality and assay development for successful DNA-encoded library screening

    In this presentation, case studies of protein target assessment enabling DNA-encoded library screening success will be shown.

    Active hit identification from DNA-encoded library screens is driven by high quality protein targets. Because the effective concentration of individual DNA-encoded library molecules in the screen is very low, the immobilized protein target concentration must exceed the dissociation constant to drive protein-library molecule binding. The protein target should also be a consistent conformation and without aggregates so the resulting data is associated with a single protein form. Ensuring that the immobilized protein target maintains biochemical or biophysical activity in the course of selection biases the outcome to functionally active hits. In this presentation, case studies of protein target assessment enabling DNA-encoded library screening success will be shown. 

    Allison Olszewski

    X-Chem

    Dr. Olszewski joined X-Chem in 2016 as Associate Director of Protein Biochemistry. She developed Avimer panning techniques against membrane-bound targets at Avidia, Inc. (acquired by Amgen in 2006) from 2006 to 2007. From 2007 to 2015 she worked at GlaxoSmithKline, where she expanded the use of DNA-encoded library technology to non-soluble targets. Before joining X-Chem, Dr. Olszewski managed the screening hit validation effort, and developed protein-protein interaction assays for the Small Molecule Assisted Receptor Targeting (SMART) technology platform at Warp Drive Bio. Dr. Olszewski received her B.S. in Biochemistry from the University of Delaware, and her Ph.D. in Organic Chemistry/Chemical Biology from the University of California, Irvine.

  • An end-to-end automated solution for provisioning compounds from a large liquid library for target and hit identification efforts

    Pfizer, like many large pharma, holds millions of compounds in its collection. This presentation will detail the migration from a single-use tube technology requiring a fit-for-purpose building, to a standard lab footprint automated system utilizing multi-use containers and acoustic-based liquid dispensing.

    Pfizer, like many large pharma, holds millions of compounds in its collection.  This presentation will detail the migration from a single-use tube technology requiring a fit-for-purpose building, to a standard lab footprint automated system utilizing multi-use containers and acoustic-based liquid dispensing.  The resulting solution is seamlessly integrated with a commercially available Enterprise compound-to-assay requesting tool.  Any member of the global organization has the ability to order compounds for plating to any number of assays, with plate shipment to any location. The solution, called Hit ID Provisioning System (HIPS) incorporates rule-based automation behavior in making final deliverables of assay ready plates that ensure plate quality under minimized stock consumption.  A novel compound binning algorithm compensated for the limitations of current acoustic liquid handling logistics.  Key considerations around implementation of new technology platforms will be reviewed in evaluating how the HIPS was rolled out to enable Pfizer researchers and collaborators access to the compound collection without interruption while improving plate quality and saving resources.

    Keith Miller

    Pfizer WR&D

    Keith obtained his Bachelors in Biomedical Engineering from Cornell University and an MBA from the University of Connecticut.  He has been working in Pharma at Pfizer since 2000, and is currently located at the Groton, CT campus.  Keith heads up the Compound Management & Distribution group's hit identification lab.  His group oversees Pfizer's largest compound collection - roughly 4 million unique compounds stored in liquid format.  Keith's lab serves not only as the stewards for this collection, but also oversees the plating & distribution of compounds to support Pfizer's global portfolio of plate-based early discovery projects.  Prior to his current role, Keith has worked with a broad range of research disciplines, either directly or through his expertise with automation and liquid-handling instrumentation: High-Throughput Screening, Analytical Chemistry, Protein Crystallization, NMR Screening, Protein Cloning & Expression, and Biophysics. 

  • DNA Encoded Library Selection Method to Rank Order Primary Hits by Affinity

    DNA encoded libraries are now routinely employed as part of reductionist lead generation campaigns in Pharma. The large number of compounds contained in many of these libraries (> 1 Billion) when combined with modest hit rates (0.1%) often result in thousands of potential hits.

    DNA encoded libraries are now routinely employed as part of reductionist lead generation campaigns in Pharma. The large number of compounds contained in many of these libraries (> 1 Billion) when combined with modest hit rates (0.1%) often result in thousands of potential hits. The compounds are generated as large combinatorial mixtures and “selected” for affinity to the target of interest. As a result the first step in hit triage is to resynthesize the compounds of interest without the DNA tag and confirm that the observed affinity for the target translates into the desired functional activity. Here we present experimental protocols and informatics methods that can estimate the affinity of the hits in the DNA encoded library mixture, thus enabling the incorporation of a ligand efficiency estimate into the decision making process for compound resynthesis. 

    Jeff Messer

    GlaxoSmithKline

    Biology, Drug Discovery, Informatics, Scientific Computing, Software Engineering

  • An Acoustic Microfluidic Device for Hematopoietic Stem Cell Enrichment from Whole Blood

    Here, we present a system that continuously separates HSCs from both healthy and diseased whole blood using acoustically-mediated separation in a plastic microfluidic device. We and others have previously demonstrated acoustic separation of bacteria, beads, and liposomes from blood cells, but this is the first report showing enrichment of HSCs directly from patient samples.

    Emerging cell therapies require efficient methods for purification of target cells prior to subsequent processing. In the case of stem cell-based therapies large numbers of hematopoietic stem cells (HSCs) must be collected and purified from patient peripheral blood; a challenging task because even after mobilization, the concentration of HSCs in the collected product is typically less than 1% of all cells. Existing processing techniques, such as density gradient centrifugation and subsequent magnetic separation, achieve some of the requirements, however, they often provide low yield, are costly, time-consuming, and labor intensive. Acoustic separation has emerged as a versatile technology for flow-through liquid handling and particle manipulation. The technique relies upon differences in the size, density, and compressibility of various blood components in order to achieve rapid label-free discrimination between target and off-target cells.

    Here, we present a system that continuously separates HSCs from both healthy and diseased whole blood using acoustically-mediated separation in a plastic microfluidic device. We and others have previously demonstrated acoustic separation of bacteria, beads, and liposomes from blood cells, but this is the first report showing enrichment of HSCs directly from patient samples. In addition, because our microchannel is constructed entirely of polystyrene, it is suitable for scale-up to clinically relevant processing rates, with the potential for flow rates approaching 100 ml/hr. Our device consists of a microchannel mounted on a piezoelectric actuator and a temperature-controlled stage. The actuator excites an acoustic standing wave within the fluid cavity, transverse to the flow direction. This standing wave exerts a force on blood cells which drives them toward the centerline of the flow. Larger and denser cells experience a larger force compared to smaller and less dense cells, and are more strongly focused. At the downstream end of the channel, a trifurcating outlet allows for the separation of strongly focused cells (e.g., red blood cells and neutrophils) from those that are weakly focused  (e.g., HSCs and lymphocytes). In this work the system is tuned to enable the separation and collection of HSCs.

    We achieve enrichment of the HSC population (CD34+ as % total white blood cells) from 9% to 22%, a factor of 2.4x, starting from unpurified whole patient blood. This enrichment was achieved in a single pass through the device with HSC recovery of 40% and reduction of the red blood cell concentration by 62%. These figures can be improved by multiple passes through the system and by device optimization. Our results demonstrate that we are able to efficiently and specifically purify HSCs from whole blood in a continuous flow-through device. In addition, our device is fabricated from low-cost components and is straightforward to operate, giving it the potential for future use in sample purification for cell therapy.

    Charles Lissandrello

    Draper

    Charles Lissandrello is a Senior Member of the Technical Staff in the Nano Structured Materials group at Draper. He received his Ph.D. in Mechanical Engineering at Boston University in 2015, where he conducted research with Kamil Ekinci on the transition from hydrodynamic to kinetic gas behavior in fluid systems far from equilibrium. At Draper, he has worked with a team of collaborators to develop novel microfluidic devices for biological sample processing.

  • Integrating Environmentally Friendly Tactics into a High-Throughput Screening Setting

    Throughout everyday life there are many considerations and practices in place when it comes to recycling, minimizing waste, cleaner energy and reuse to cut down on the impact to our planet’s ecosystem, with millions of individuals around the world making the choice to conserve keeping these principles in mind.

    Throughout everyday life there are many considerations and practices in place when it comes to recycling, minimizing waste, cleaner energy and reuse to cut down on the impact to our planet’s ecosystem, with millions of individuals around the world making the choice to conserve keeping these principles in mind.  However, this mindset and conscientiousness to conserve is not on the radar when it comes to the world of high-throughput screening and science in general, where the term ‘consumable’ is ubiquitous and pipette tips, petri dishes, microplates, solvents and an extensive list of materials are disposed of after one use every day, with most of this waste needing to be handled as chemical or biohazardous, further increasing the negative environmental impact.  Luckily this mentality is changing, with the availability of new technologies and the use of experimental data proving its effectiveness NCATS has been able to implement and adopt several methods into many aspects of their high-throughput screening processes which are friendlier to our environment than the traditional equivalents.  In many cases these eco conscious practices yield higher quality, cleaner data as well as even eliminating the need for automated assays having to be repeated by catching detrimental issues in real time.  Here the focus will be about the integration of equipment onto peripheral devices of the robotic screening platforms, processes and supporting modular operations with the overall goal of conservation.  Not only will the use of these concepts be demonstrated but more importantly the successful adaptation will be shown with supporting data.  Spanning the last 7 years NCATS has not only been mindful but has been continuously advancing and developing tactics in order to minimize waste without sacrificing high quality data.  This ultimately proves that science including high-throughput screening specifically can evolve to incorporate environmentally friendly techniques while continuously advancing the field.

    Carleen Klumpp-Thomas

    NIH/NCATS

    Carleen Klumpp-Thomas currently leads the Automation Group at the National Center for Advancing Translational Sciences (NIH/NCATS) in Rockville MD. Carleen manages and runs all of the automated screening platforms for NCATS Research Services Section (RSS). RSS’ multi-disciplinary capabilities enables the ongoing operation of all of NCATS’ research activities. These automated platforms perform a wide variety of experiment types ranging from biochemical, cell based, RNAi and other existing and novel assay technologies. Carleen’s automation and engineering expertise has been critical for projects ranging from cancer to Ebola to Parkinson’s disease.  The advanced instrumentation, protocols and methods are necessary to keep NCATS at the leading edge of scientific research and Carleen manages these requirements with ease, all while staying in constant communication with all researchers. Carleen earned her B.S. degree in Bioengineering from Syracuse University and her M.S. in Biomedical Engineering from NYU Tandon School of Engineering.

  • Lab Automation Drones for Mobile Manipulation in High Throughput Systems

    In lab automation, there is a wide range of robots. Robots are employed to accelerate sample handling, such as in high throughput screening (HTS), manipulators and transfer lines rapidly manipulate micro-plates amongst numerous test stations. The net result is that a typical HTS system can handle over 500,000 samples a week. In the age of big data, higher throughput means faster pharmaceutical development and hence quicker patent registrations and earlier market penetration.

    In lab automation, there is a wide range of robots. Robots are employed to accelerate sample handling, such as in high throughput screening (HTS), manipulators and transfer lines rapidly manipulate micro-plates amongst numerous test stations. The net result is that a typical HTS system can handle over 500,000 samples a week.  In the age of big data, higher throughput means faster pharmaceutical development and hence quicker patent registrations and earlier market penetration. HTS systems are often custom-tailored to maximize throughput with many high- precision 6-DOF robot manipulators. Such robots employ parallel jaw grippers to gently and precisely position and orient micro-plates. However, once configured, they are not easily changed. This is important because as new tests emerge, older HTS systems cannot easily perform them. The National Institutes of Health (NIH) in the United States are looking at the potential of lab automation drones to add flexibility to existing HTS systems. The notion has merit; aerial manipulation research is an active area. High degree of freedom (DOF) robots with dexterous arms has been addressed in transformative applications such as material handling, disaster response, and personal assistance. And micro-plates are relatively easy to robotically lift and orient. Issues like ground effect, limited battery life, and obstacle avoidance are indeed relevant to lab automation but also remain open research topics. The critical gap in a lab automation drone appears to be the lack of aerial manipulation arms and grippers. Recently, several configuration systems including single DOF aerial grasping, non-redundant and fully redundant articulated aerial manipulation, have been explored to create manipulation systems. But all the arms in aerial manipulation are serial; a motor in each joint results in a heavy arm. To the author’s best knowledge, the author’s lab has been the first to introduce a parallel-mechanism arm for aerial manipulation. The previous work concluded its higher degree of precision and lower toque impact on the drone’s stability versus serial manipulators. In this work, the authors present a design of a 6-DOF parallel mechanism arm with a sensorized parallel jaw gripper. The test-and-evaluation approach and results are given.

    Dongbin Kim

    University of Nevada, Las Vegas

    Dongbin Kim has completed his B.S. in aircraft systems engineering from Korea Aerospace University, S. Korea in 2016. He is currently studying PhD in Mechanical Engineering in University of Nevada in Las Vegas. He serves as lab manager in Drones and Autonomous Systems Lab.

  • Complex Tissue Biology and Throughput in a Microplate-Based Organ-on-a-Chip System

    In this presentation, I will focus on biological and technological aspects of both healthy and diseased tissue models in the OrganoPlate, including platform specific assays, such as a barrier integrity assay and neuronal network activity assays. I will present data demonstrating that 3D tissues cultured in the OrganoPlate are suitable for any-throughput drug efficacy and toxicity screening, trans-epithelial transport studies, and complex co-culture models in an in vivo-like microenvironment.

    The OrganoPlate is a microfluidic tissue culture platform, which enables high-throughput culture of microtissues in miniaturized organ models. In the OrganoPlate(1), extracellular matrix (ECM) gels can be freely patterned in microchambers through the use of phaseguide technology. Phaseguides (capillary pressure barriers) define barrier-free channels in microchambers that can be used for ECM deposition or medium perfusion. The microfluidic channel dimensions not only allow solid tissue and barrier formation, but also perfused tubular epithelial vessel structures can be grown. We have developed a range of multi-cellular organ- and tissue models for drug efficacy and toxicity studies, including blood vessels, brain, gut(2), and kidney.

    In this presentation, I will focus on biological and technological aspects of both healthy and diseased tissue models in the OrganoPlate, including platform specific assays, such as a barrier integrity assay and neuronal network activity assays. I will present data demonstrating that 3D tissues cultured in the OrganoPlate are suitable for any-throughput drug efficacy and toxicity screening, trans-epithelial transport studies, and complex co-culture models in an in vivo-like microenvironment.

    References:
    1. S. J. Trietsch, G. D. Israëls, J. Joore, T. Hankemeier, and P. Vulto, “Microfluidic titer plate for stratified 3D cell culture.,” Lab Chip, vol. 13, no. 18, pp. 3548–54, Sep. 2013
    2. S. J. Trietsch, E. Naumovska, D. Kurek, M. C. Setyawati, M. K. Vormann, K. J. Wilschut, H. L. Lanz, A. Nicholas, C. P. Ng, J. Joore, S. Kustermann, A. Roth, T. Hankemeier, A. Moisan, P. Vulto, “Membrane-free culture and real-time barrier integrity assessment of perfused intestinal epithelium tubes.”, Nature Communications, 2017 accepted

    Jos Joore

    MIMETAS - the Organ-on-a-Chip Company

    Jos Joore is co-founder and Managing Director of MIMETAS. He is a biotech entrepreneur, co-founder of four companies with over 17 years of executive level biotech experience in a variety of companies including Pepscan, Skyline Diagnostics, Kreatech and Westburg. During his ten-year research career, he worked as a postdoctoral researcher at the Hubrecht Institute (Utrecht) and King's College (London). He holds a cum laude Masters degree in business marketing (MBM), a Ph.D. in developmental biology and a Masters degree in biology.

  • Designed diversity and bioannotated compound libraries for obtaining maximal value from screens in induced pluripotent stem cell-derived cells and other complex biological systems

    ​As part of the current resurgence in phenotypic screening, early stage assay systems are becoming increasingly complex in an attempt to better model the disease state and therefore improve translation to the clinic. One downside to this complexity is that it substantially reduces the throughput of such systems, and it is generally not feasible to screen millions of molecules in them as would be common in a more traditional HTS campaign.

    As part of the current resurgence in phenotypic screening, early stage assay systems are becoming increasingly complex in an attempt to better model the disease state and therefore improve translation to the clinic. One downside to this complexity is that it substantially reduces the throughput of such systems, and it is generally not feasible to screen millions of molecules in them as would be common in a more traditional HTS campaign. In response to this constraint we have developed two focused compound collections for use in phenotypic screening projects. The first is a bioannotated or chemogenomic library containing molecules with well-characterised pharmacology, intended for use in repurposing and knowledge-driven target deconvolution approaches. The second is a diverse phenotypic library that attempts to maximise chemical and pharmacological diversity within a compact set of 20,000 compounds, intended as a representative sample of our regular HTS collection. In this presentation the design, construction and annotation of these libraries will be outlined. Some examples of our experiences with screening them in drug discovery projects will then be discussed. Finally, analysis of the extent to which these first generation collections have fulfilled their design criteria to date will be presented, and directions of future enhancements reviewed.

    Tim James

    Evotec

    With a background in computational chemistry and data analysis, my current focus within the Research Informatics group at Evotec is the area of chemical biology. This includes the design of compound libraries, the analysis of phenotypic screening results and integrating the output from various 'omics technologies.

  • SLAS2018 Innovation Award Finalist: Microfluidic Siphoning Array (MSA) – A Novel Scalable Digital PCR Integrated Platform

    We have developed the patented Microfluidic Siphoning Array (MSA) Technology where bulk qPCR reagents can be partitioned into “lollipops”, a novel injection molded microfluidic device coupled with a semi-permeable thin film.

    Digital PCR offers compelling advantages over the current gold standard qPCR with the ability to: 1) detect rare events (high sensitivity); 2) be less prone to inhibition (high specificity); 3) quantify nucleic acids in an absolute manner without a standard-curve (high precision). However, widespread adoption has not occurred despite the proven advantages of dPCR over qPCR as existing dPCR platforms are capital intensive, cost prohibitive, have workflows with many steps and are not easily accessible to automation.

    We have developed the patented Microfluidic Siphoning Array (MSA) Technology where bulk qPCR reagents can be partitioned into “lollipops”, a novel injection molded microfluidic device coupled with a semi-permeable thin film. The key advantages of the MSA include (a) Open source chemistry, which allows direct assay translation from qPCR to dPCR without tailored reagent formulations. (b) Experiment-to-experiment reproducibility with high fidelity microstructures with fixed number and known volume partitions insensitive to liquid handling errors. (c) Low cost due to a highly scalable manufacturing process (d) No cross talk with physically isolated partitions. The prototype device utilizes a standard format, making it compatible with automated liquid handlers. There are 8 units per prototype device, and 5,000 partitions per unit (1 μL total assay volume), with the model to create “application-specific” dPCR consumables balancing between throughput and sensitivity. To enable walkaway dPCR workflow with the MSA device, an instrument integrating pneumatic control, thermal cycling, and optical imaging was developed. An Image J pipeline was used to subtract background, extract fluorescent intensities from each lollipop, and converting them into scattered plot before applying Poisson statistics for absolute quantification. An HIV viral load assay and a Copy Number Variation (CNV) analysis assay were demonstrated with the prototype platform and achieved equal performance to the current market leader. An additional benefit of this platform is that real-time imaging of each partition during the thermal cycling process can be monitored, minimizing false positives, and enabling digital high-resolution melt analysis (dHRMA) to further improve multiplexing capability.

    In summary, the advantages enabled by this platform include lowering both the workflow and cost barriers of digital PCR without compromising the performance in precision, and sensitivity. The real-time imaging capability allows background subtraction to minimize false positives, as well as digital melt analysis to improve multiplexity. We envision a scalable and automatable digital PCR platform which can easily be integrated to research laboratories, and extend to the clinic.

    Paul Hung

    COMBiNATi Inc

    Paul Hung has 11 years of experience developing life science research tools using microfluidic technology. After receiving his PhD from UC Berkeley in 2005, he has successfully grown CellASIC Corporation, which he co-founded in 2006, to self-sufficiency with the commercialization of the ONIX live cell imaging platform, and sold to MillporeSigma (then EMD Millipore) in 2012. After the acquisition, he worked as a senior R&D manager to gain more knowledge in systematic product development in a large corporate. He founded COMBiNATi in 2016 to continue driving the vision of disrupting the life science industry with microfluidic technology, one consumable at a time. 

  • SLAS2018 Innovation Award Finalist: An Ultra High-Throughput 3D Assay Platform for Evaluating T-cell-Mediated Tumor Killing

    We have developed a novel microphysiological 3D assay that quantitates T-cell-mediated killing of 3D colorectal cancer tumor spheroids using a new 1536-well spheroid plate. This assay incorporates CD3-stimulated primary patient T-cells in culture with colorectal cancer tumor spheroids and enables parallel assessment of spheroid size and viability as well as T-cell penetration into the 3D spheroid structure.

    3-dimensional cellular assay platforms are increasingly recognized as robust surrogates for mimicking in vivo disease pathology. In particular, the multicellular spheroid model has been widely utilized in exploratory drug discovery campaigns. However, these complex 3D cell models have previously been restricted to low- or medium-throughput formats due to the technical logistics of forming spheroids in a 1536-well microtiter plate. We have developed a novel microphysiological 3D assay that quantitates T-cell-mediated killing of 3D colorectal cancer tumor spheroids using a new 1536-well spheroid plate. This assay incorporates CD3-stimulated primary patient T-cells in culture with colorectal cancer tumor spheroids and enables parallel assessment of spheroid size and viability as well as T-cell penetration into the 3D spheroid structure. Using this assay platform we screened a library of annotated compounds for spheroid viability and discovered several small molecule candidates that synergize with CD3 stimulation and enhance T-cell-mediated tumor spheroid killing. This phenotypic 3D cell model represents a robust organotypic ultra-HTS platform that can greatly enhance immuno-oncology drug discovery programs.

    Shane Horman

    GNF

    Dr. Shane Horman runs the Advanced Assay group at the Genomics Institute of the Novartis Research Foundation (GNF) in San Diego, California. He received his Ph.D. from King’s College-London in molecular genetics and was a postdoc at the University of Pennsylvania-School of Medicine and then at Cincinnati Children’s Hospital Medical Center investigating mouse models of human leukemias. Dr. Horman’s Advanced Assay group at GNF is dedicated to the development and implementation of complex and 3D high content screening platforms that may better reflect in vivo patient biology for early stage drug discovery. Dr. Horman has published numerous papers on high content 3D screening platforms and regularly presents at phenotypic drug discovery conferences. 

  • Microfluidics and Commercial Success? Experience and examples of the last 16 years.

    The presenter will try to help the audience to understand the factors that have shaped successes and failures to ensure that future ventures try to avoid the pitfalls of the past.

    The presenter has built a group of companies over the last 16 years which exploit Microfluidics in a wide range of ways. Using Microfluidics to make products such as:
    - Pioneering the field of flow chemistry
    - microfluidic components
    - microfluidic 3d printing
    - particle engineering
    - Single cell Biology
    During this time, the Dolomite part of the group was also a leading consulting team in microfluidics, and attacked challenges in very varied application areas from the oil industry, through food, pharmaceuticals and diagnostics to name a few. As a result of this history the presenter has extremely diverse knowledge and experience of the successes and failures of exploitation of microfluidics, as well as understanding why these outcomes were arrived at. This coupled with the presenter having been an Editorial board member of the RSC Journal "Lab on a Chip" since 2012 gives yet another insight from the academic perspective. The presenter will try to help the audience to understand the factors that have shaped successes and failures to ensure that future ventures try to avoid the pitfalls of the past.

    Mark Gilligan

    Blacktrace Holdings Ltd

    https://www.linkedin.com/in/ma...

  • Combining CRISPR/Cas9 screening with custom engineered reporter cell lines to identify genes required for tubulin formation

    This case-study describes an effective methodology to combine multi-pronged gene-editing with phenotypic screening to enrich our knowledge of gene and molecular interactions in complex biological systems. Further, with an expanded array of reporter cell lines at the researcher’s disposal, this type of strategy can be adjusted to dissect many other relevant pathways and phenotypes.

    Phenotypic high-throughput / high content screens have become popular tools for elucidating molecular and genetic pathways in biological systems.  Phenomics, or high-dimensional biology, incorporates screening methods that can enable many parameters to be tested in concert under similar or identical conditions, providing a potential wealth of information about a specific biological process.  Here we describe the use of a gene-edited reporter cell line, U2OS LMNB1-TUBA1B-ACTB (Sigma-Aldrich CLL1218), to phenotypically detect genes responsible for tubulin formation.  CLL1218 was transduced with CAS9 Blasticidin Lentiviral Particles (Sigma-Aldrich LVCAS9BST) and selected. Following selection, the pool was cloned, and derived clones were then screened for CRISPR/Cas9 activity using a known active gRNA.  Preferred clones were expanded and banked to be used in a semi-automated high-throughput CRISPR library screens to identify modulators of tubulin expression, formation, and distribution.  Proof-of-concept was demonstrated using a set of CRISPR guides specific for vimentin.  Creation of a vimentin knock-out in the CLL1218-Cas9 reporter line alters cell morphology that can be visually detected  on a variety of imagining platforms, including high-content instruments.  This case-study describes an effective methodology to combine multi-pronged gene-editing with phenotypic screening to enrich our knowledge of gene and molecular interactions in complex biological systems. Further, with an expanded array of reporter cell lines at the researcher’s disposal, this type of strategy can be adjusted to dissect many other relevant pathways and phenotypes.

    Mark Gerber

    MilliporeSigma

    Mark joined Sigma-Aldrich in 2006, and has worked in the areas of biotherapeutic production, stem cell applications and gene regulation. In 2014, Mark was recruited to lead the Cell Design Studio team in the engineering of custom cell lines utilizing ZFN, CRISPR and shRNA technologies. Mark obtained his Ph.D. in Biochemistry and Molecular Biology from Saint Louis University School of Medicine where he used RNAi in Drosophila models to elucidate developmental and biochemical roles for RNA polymerase II-associated transcription factors. Following graduate school, Mark served as a Postdoctoral Fellow at Washington University in St. Louis where he investigated signalling pathways involved in the development of human meningioma. 

  • Highthroughput Binder Confirmation (HTBC): A new non-combinatorial synthesis platform created to enhance and accelerate hit ID.

    Encoded Library Technology (ELT) is a hit identification platform that uses ultra-large collections of chemically diverse DNA-encoded small molecule libraries selected for affinity against a therapeutically relevant target. Recent advances in ELT libraries, library pooling strategies, selections and DNA sequencing have vastly increased the number of actionable chemotypes produced for a given selection campaign.

    Highthroughput Binder Confirmation (HTBC): A new non-combinatorial synthesis platform created to enhance and accelerate hit ID.
    Joseph Franklin, Xiaopeng Bai, Lijun Fan, Kenneth Lind, Heather O’Keefe, Eric Shi, Jennifer Summerfield, Jerry Yap & Jeffrey Messer; NCE Molecular Discovery - GSK

    Encoded Library Technology (ELT) is a hit identification platform that uses ultra-large collections of chemically diverse DNA-encoded small molecule libraries selected for affinity against a therapeutically relevant target. Recent advances in ELT libraries, library pooling strategies, selections and DNA sequencing have vastly increased the number of actionable chemotypes produced for a given selection campaign. In practice, only a small fraction of these chemotypes are synthesized as discrete molecules without the encoding DNA using traditional organic synthesis. To address this bottleneck we developed an automated microscale parallel synthesis platform that uses double stranded DNA with a cleavable linker as a chemical handle. This High Throughput Binder Confirmation (HTBC) platform uses the original DNA-Encoded Library (DEL) chemistry and will recapitulate the products, side-products and intermediates produced in the original library synthesis. The resulting compounds are cleaved from the DNA support and are screened as small molecule mixtures by Affinity Selection Mass Spectrometry. The platform is capable of assessing target engagement for hundreds of compounds per month and is used at GSK to prioritize synthesis decisions for more traditional scale organic synthesis.

    Joe Franklin

    GlaxoSmithKline

    DNA Encoded Library on-DNA chemistry 

  • DNA-encoded library screening on a GPCR: identification of agonists and antagonist to protease-activated receptor 2 (PAR2) with novel and diverse mechanisms of action.

    Functional and binding studies reveal that AZ8838 exhibits slow binding kinetics, which is an attractive feature for a PAR2 antagonist competing against a tethered ligand. Antagonist AZ3451 binds to a remote allosteric site outside the helical bundle. We propose that antagonist binding prevents structural rearrangements required for receptor activation and signalling.

    DNA-encoded library screening on a GPCR: identification of agonists and antagonist to protease-activated receptor 2 (PAR2) with novel and diverse mechanisms of action. Niek Dekker1 AstraZeneca, Innovative Medicines Biotech Unit, Gothenburg, Mölndal SE-431 83, Sweden Protease-activated receptor-2 (PAR2) is irreversibly activated by proteolytic cleavage of the N-terminus which unmasks a tethered peptide ligand that binds and activates the transmembrane receptor domain eliciting a cellular cascade in response to inflammatory signals and other stimuli. PAR2 is implicated in a wide range of inflammatory and other diseases including cancer. Activation of PAR2 on sensory neurons leads to hyperphophorylation of TRP channels resulting in pain and hyperalgesia. The discovery of small molecule antagonists to PAR2 has proven challenging. DNA-encoded library (DEL) screening on purified PAR2 delivered both antagonists and agonists, exemplified by AZ3451 (SLIGRL PAR2  IP-one IC50 = 23 nM) and AZ8838 (SLIGRL PAR2 IP-one IC50 = 1500 nM), and agonist AZ2429 (EC50 of 53 nM in IP-one). Crystal structures of antagonist bound to the GPCR revealed that AZ8838 binds in a fully occluded pocket near the extracellular surface. Functional and binding studies reveal that AZ8838 exhibits slow binding kinetics, which is an attractive feature for a PAR2 antagonist competing against a tethered ligand. Antagonist AZ3451 binds to a remote allosteric site outside the helical bundle. We propose that antagonist binding prevents structural rearrangements required for receptor activation and signalling.  AZ3451 and AZ8838 were tested in a rat model of PAR2-induced oedema using 2fLIGRL-NH2 (350 µg/paw in 100 µL and trypsin (20 µg/ paw in 100 µL). At a 10 mg/kg dose, both compounds exhibited reduction of paw swelling in both in vivo models. These results confirm that at least two allosteric sites exist on the PAR2 receptor and can be blocked resulting in reversal of in vitro and in vivo PAR2 mediated signaling. DEL screening on purified PAR2 combined with crystallography provided a basis for the development of selective PAR2 antagonists for a range of therapeutic indications.

    co-authors: Dean G. Brown1, Giles A. Brown2, Robert K.Y. Cheng2, Matt Clark3,Miles S. Congreve2, Robert Cooke2, John Cuozzo3, Andrew S. Doré2, Christoph Dumelin3, Karl Edman1, Rink-Jan Lohman4, Yuhong Jiang4, David P. Fairlie4, Cedric Fiez-Vandal2, Stefan Geschwinder1, Christoph Grebner1, Marie-Aude Guie3, Nils-Olov Hermansson1, Ali Jazayeri2, Patrik Johansson1, Anthony Keefe3, Rudi Prihandoko2, Mathieu Rappas2, Oliver Schlenker2, Eric Sigel3, Arjan Snijder1, Holly Souter3, Linda Sundström1, Benjamin Tehan2, Barry Teobald2, Peter Thornton1Dawn Troast3, Giselle Wiggin2, Ying Zhang3, Andrei Zhukov2 and Fiona H. Marshall2

    1AstraZeneca, Innovative Medicines Biotech Unit, Gothenburg, Mölndal SE-431 83, Sweden
    2Heptares Therapeutics Ltd, Biopark, Broadwater Road, Welwyn Garden City, Hertfordshire, AL7 3AX, UK
    3X-Chem Inc., 100 Beaver St. Waltham MA 02453
    4Institute for Molecular Bioscience, The University of Queensland, Brisbane, Qld 4072, Australia

    Niek Dekker

    AstraZeneca

    Strong delivery- and collaboration-focus with experience working in matrix organizations. Science-driven with excellent background in lead-discovery technologies. Worked in large number of early discovery projects (small molecule and biologics), both supporting projects and leading capability projects. Strong team and people skills from a number of years of line management responsibility. Experienced working with external academic and biotech partners on new technologies and with contract research organizations (outsourcing). Portfolio management skills. Excellent leadership skills from working in academia and pharma industries, training and from a range of different roles.
     
    Professional career
    2012-present   Principal scientist in Reagents & Assay Development, Discovery Sciences;
    2008-2012       Delivery Leader CNSP iMed, Cell, Protein & Structural Sciences, Discovery Enabling Capabilities and Sciences, Mölndal, AstraZeneca;
    2004-2008        Associate Director Protein Engineering Section, Structural Chemistry Laboratories, Mölndal, AstraZeneca;
    2000-2004        Team Leader Protein Engineering, Structural Chemistry Laboratories-Mölndal, AstraZeneca, Sweden.;
    1994-2000        Assistant Professor Utrecht University, the Netherlands.

  • Development Of 3-Dimensional Human Cortical Spheroid Platforms With High Homogeneity And Functionality For High Throughput And High Content Screening

    Here we describe the development of a highly homogenous human induced Pluripotent Stem ell (hiPSC)-derived cortical spheroid screening platform in 384 well format, composed of cortical neurons and astrocytes. Immunofluorescence analysis indicated that these derived neurons and astrocytes display key markers of cellular identity as well as maturity, such as synaptic proteins and glutamate transporters.

    The human cerebral cortex is organized in a complex 3-dimensional (3D) structure comprising different neural cell types. The coordinated work of these different cell types is key for brain function and homeostasis. Recently, much work has been focused on obtaining 3D brain organoids in an attempt to better recapitulate the brain development/function in vitro. However, current protocols may lead to variable organoid size and function, making the use of these powerful tools impractical in a drug screening scenario. Here we describe the development of a highly homogenous human induced Pluripotent Stem ell (hiPSC)-derived cortical spheroid screening platform in 384 well format, composed of cortical neurons and astrocytes. Immunofluorescence analysis indicated that these derived neurons and astrocytes display key markers of cellular identity as well as maturity, such as synaptic proteins and glutamate transporters. Viability assays carried out with compounds with known mechanism of action indicated scaleability and feasibility of the assays, with results comparable to a standard 2D model employing the same culture composition. Kinetic, high trhoughput calcium flux analysis performed in a in a Fluorometric Imaging Plate Reader (FLIPR) highlighted that the spheroids present quantifiable, robust and uniform spontaneous calcium oscillations. The calcium signal was modified with excitatory and inhibitory modulators coherently and in a highly reproducible fashion, confirming the presence of a functionally integrated glutamatergic/GABAergic circuit. High speed confocal imaging confirmed homogenous calcium oscillations at the cellular level, whereas multielectrode array (MEA) analysis demonstrated robust synchronous neurophysiological activity at the network level. Additionally, these cortical organoids are amenable to immunostaining in suspension, enabling scalable high content image-based assays focused on key protein markers. Altogether, the developed 3D cortical spheroid platform can be easily implemented as a reliable high throughput screening platform to investigate complex cortical phenotypes in vitro, as a reliable high-throughput screening platform for toxicology studies, disease modeling and drug testing.

    Cassiano Carromeu

    StemoniX

    Experienced Neuroscientist with expertise in the use of human induced pluripotent stem cells (hiPSCs) for safety pharmacology, toxicology, drug screening and for modeling of neurodevelopmental disorders.

  • New approaches for single cell genome sequencing and mutation analysis

    This presentation reviews two new methods for single-cell genome analysis, one that requires no microfluidics or specialized equipment for direct single-cell genome amplification and another that leverages culture-based amplification rather than biochemical amplification to enable studies of de novo mutations in single cells.​

    Microfluidics and whole-genome amplification are enabling single-cell genomic analyses.  At the same time, these technologies limit single-cell genomic studies by imposing cost and complexity (microfluidics) and degrading data quality (whole-genome amplification). Here I will present two new methods for single-cell genome analysis, one that requires no microfluidics or specialized equipment for direct single-cell genome amplification and another that leverages culture-based amplification rather than biochemical amplification to enable studies of de novo mutations in single cells.

    Paul Blainey

    MIT Department of Biological Engineering and Broad Institute of MIT and Harvard

    Dr. Blainey trained in mathematics, chemistry, biophysics, microfluidics, and genomics before joining the Broad Institute and the Department of Biological Engineering at MIT as a faculty member in 2012. Dr. Blainey’s laboratory integrates microfluidic, molecular, and imaging tools to address new challenges in single-cell analysis, genomic screening, and therapeutics development.

  • A 3D High-Content Screening assay as in vitro model to study polycystic kidney disease

    ​Autosomal dominant polycystic kidney disease (ADPKD) is caused by mutations in either the Pkd1 or Pkd2 gene. The most important characteristic of this disease is the formation of cysts in the kidney, which reduces renal function and will lead to end stage renal disease.

    Autosomal dominant polycystic kidney disease (ADPKD) is caused by mutations in either the Pkd1 or Pkd2 gene. The most important characteristic of this disease is the formation of cysts in the kidney, which reduces renal function and will lead to end stage renal disease.  Although it is known that ADPKD is caused by mutations in the Pkd1 or Pkd2 gene, it is not yet understood why this mutation leads to cyst formation.  Since cysts cannot form in conventional in vitro 2D cell culture, current research on ADPKD relies heavily on the use of animal models. The lack of proper in vitro models makes the study of this disease all the more challenging.  To address this, we developed a 3D high-content in vitro screening assay usable for mechanistic studies as well as target discovery in ADPKD. This culture system uses kidney collecting duct Pkd1 KO cells, which spontaneously form small cysts when cultured in our 3D hydrogel.  In the presence of the test compounds, cAMP inducer Forskolin is added to stimulate the cyst swelling. To examine the effect of the compounds on the swelling, cysts are fixed, stained and imaged. The 3D image stacks are analyzed with our OminerTM image analysis software, capable of measuring many phenotypic characteristics, including cyst size, nucleus shape and thickness of cyst wall. This also enables us to identify compounds that are effective and do not influence cell viability, and discard compounds which have undesired therapeutic profiles. These methods are optimized for the use of lab automation, capable of testing large compound libraries in a single experiment. To follow up on previously presented work (Booij et al, SLAS Discovery, 2017) , we screened a collection of 2320 natural products and bioactive compounds. Multiple hit compounds were identified and validated in vitro. Based on the phenotypic profile, we then selected  several of these hit compounds for in vivo validation in mouse models. One of these compounds proved effective in reducing cyst progression and collagen deposition in a dose-dependent manner.

    In these experiments, we show that this 3D in vitro screening model can be used to select compounds that have the desired phenotypic profile, which was validated in vivo. These results prove the applicability and reliability of this model in Drug Discovery for ADPKD.

    Hester Bange

    Leiden University

    Hester graduated in 2016 as MSc in Bio-Pharmaceutical Sciences from Leiden University (8.5/10 average). Following very successful successful Master internship at the division of Toxicology at the Leiden Academic Centre for Drug Research, Hester started her PhD at Leiden University spin-off company OcellO BV. in September 2016 on a collaborative project with Leiden University and the Leiden University Medical Centre. Het PhD research is titled "3D Models for Cystopathies - the missing link in translational Medicine", and focuses on the development on high content 3D in vitro screening models for diseases such as polycystic kidney disease and cystic fibrosis. 

  • Applying 'NewSQL' technologies to scientific data to enable self-guided data discovery and analysis

    Scientific data organization and analysis remains a significant impediment to drug discovery particularly in late-stage animal studies, despite years of effort and ongoing “data lake” projects. Recent shifts to more heavily employ outsourced research have further fragmented data standards, increased reliance on ad hoc reports, and yielded single-use data. We have developed a novel approach to data curation and aggregation that enables scientists to self-serve scientific data regardless of its originating source and deposit those data into self-guided and open-ended analysis.

    Scientific data organization and analysis remains a significant impediment to drug discovery particularly in late-stage animal studies, despite years of effort and ongoing “data lake” projects.   Recent shifts to more heavily employ outsourced research have further fragmented data standards, increased reliance on ad hoc reports, and yielded single-use data.  We have developed a novel approach to data curation and aggregation that enables scientists to self-serve scientific data regardless of its originating source and deposit those data into self-guided and open-ended analysis.  Our approach relies on NoSQL database technologies to connect to structured existing data source(s) (like internally developed data lakes) or ad hoc sources like folders of Excel spreadsheets.  All the results, regardless of source, are indexed into a common data shape that drive performance and ensures a consistent user experience.  Discovered results are presented through RESTful web services or a “NewSQL” front-end.  During the course of the past year, we have refined this approach through a collaborative program with a large drug discovery company.  In this presentation, we will describe the motivation of our approach, show the results, and provide metrics for how much this novel approaches speed data discovery and utilization.

    Daniel Weaver

    PerkinElmer

    Dr. Daniel C. Weaver is a Senior Product Manager for Research Informatics at PerkinElmer Informatics.  Prior to joining PerkinElmer, Dr. Weaver was the Director of Scientific Computing at Array Biopharma, Inc. in Boulder, Colorado, where he led all aspects of scientific software development and acquisition.  Over the course of the last decade, Dr. Weaver’s team delivered systems to support scientific endeavors ranging from target identification though drug discovery and into clinical development and translational medicine.  In a previous life, Dr. Weaver was the Lead Scientist for Gene Expression Analysis at Genomica.  He received his doctorate in developmental genetics from the University of Colorado, Boulder under the direction of Dr. William B. Wood where he studied patterning in early development. 

  • 1-D High-Throughput Screening Assays for Primary Human T Cells

    The parallel microfluidic cytometer (PMC) is an imaging flow cytometer that operates on statistical analysis of low-pixel-count, one-dimensional (1-D) line scans. It is efficient in data collection and operates on suspension cells. Our 1-D instrument leverages both the high throughput aspects of traditional flow cytometry and the high spatial content of 2-D imaging cytometers. In this talk, we present a supervised automated pipeline for the PMC that minimizes operator intervention by incorporating automated multivariate logistic regression for data scoring.

    The parallel microfluidic cytometer (PMC) is an imaging flow cytometer that operates on statistical analysis of low-pixel-count, one-dimensional (1-D) line scans. It is efficient in data collection and operates on suspension cells. Our 1-D instrument leverages both the high throughput aspects of traditional flow cytometry and the high spatial content of 2-D imaging cytometers. In this talk, we present a supervised automated pipeline for the PMC that minimizes operator intervention by incorporating automated multivariate logistic regression for data scoring. The approach quantifies biomarker localization of activated T cells into a single descriptive ‘activity score’ readout. Reducing complex phenotypes into a simple readout has many advantages for drug screening and characterization. We test the self-tuning statistical algorithms in human primary T cells in flow with various drug response assays. We readily achieve an average Z’ of 0.55 and SSMD of 13. The PMC is volume efficient, needing only 4 µL of sample volume per well. Anywhere from 3000 to 9000 independent sample tests can be processed from a single 15 mL blood donation. The parallel nature of our laser scanning system enables high well throughput and is extremely scalable. We conclude that the new technology will support primary cell protein localization assays and “on-the-fly” data scoring at a sample throughput of more than 100,000 wells per day. This is, in principle, consistent with large-scale primary pharmaceutical screens. We demonstrate that 1-D imaging provides many advantages for rapid development of primary T cell assays in flow.

    Steve Wang

    Boston University

    Previous research assistant in Daniel Ehrlich's group at Boston University. Developed 1-D cytometry methods and high throughput automated statistical approaches to screening in primary T cells.

  • A highly-reproducible automated protein sample preparation workflow for quantitative mass spectrometry in plasma or blood

    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.

    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. 

    Jennifer Van Eyk

    Cedar Sinai Medical Center

    PhD in Biochemistry

  • SLAS2018 Innovation Award Finalist: Ultrafast all-optical laser-scanning imaging - Enabling deep single-cell imaging and analysis

    ​Studying cell populations, their transition states and functions at the single cell level is critical for understanding in normal tissue development and pathogenesis of disease. However, current platforms for single-cell analysis (SCA) lack the practical combination of throughput and precision that is limited by the prohibitive costs and time in performing SCA, very often involving thousands to millions individual cells – largely explaining the limited applications of SCA to date.

    Studying cell populations, their transition states and functions at the single cell level is critical for understanding in normal tissue development and pathogenesis of disease. However, current platforms for single-cell analysis (SCA) lack the practical combination of throughput and precision that is limited by the prohibitive costs and time in performing SCA, very often involving thousands to millions individual cells – largely explaining the limited applications of SCA to date. For creating new scientific insights and enriching the diagnostic toolsets, it is valuable to explore alternative biomarkers, notably biophysical markers, which maximizes the cost-effectiveness of SCA because of its label-free nature. Also, as it is closely tied with many cellular behaviours, biophysical markers can complement and correlate with the information retrieved by existing biochemical markers with high statistical precision – providing a comprehensive catalogue of single-cell properties and thus a new landscape of “Cell Altas”. Optical microscopy is an effective tool to visualize cells with high spatiotemporal resolution. However, its full adoption for high-throughput SCA has been hampered by the intrinsic speed limit imposed by the prevalent image capture strategies, which involve the laser scanning technologies (e.g. galvanometric mirrors), and/or the image sensors (e.g. CCD and CMOS). The laser scanning speed is fundamentally limited by the mechanical inertia of the mirrors whereas the image capture rate of CCD/CMOS sensor is fundamentally limited by the required image sensitivity. Notably, this speed-versus-sensitivity trade-off of the image sensor explains why the throughput of flow cytometry has to be scaled down from 100,000 cells/sec to 1,000 cells/sec when the imaging capability is incorporated. To address these challenges, we adopt two related techniques to enable imaging flow cytometry with the unprecedented combination of imaging resolution and speed. Sharing a common concept of all-optical laser-scanning by ultrafast spatiotemporal encoding of laser pulses, these techniques, time-stretch imaging and free-space angular-chirp-enhanced delay (FACED) imaging enable ultrahigh-throughput single-cell imaging with multiple image contrasts (e.g. quantitative phase and fluorescence imaging) at a line-scan rate beyond 10’s MHz (i.e. an imaging throughput up to ~100,000 cells/sec). Moreover, they also enable quantification of intrinsic biophysical markers of individual cells – a largely unexploited class of single-cell signatures that is known to be correlated with the overwhelmingly investigated biochemical markers. All in all, these ultrafast single-cell imaging platforms could find new potentials in deep machine learning complex biological processes from such an enormous size of image data (from molecular signatures to biophysical phenotypes), especially to unveil the unknown heterogeneity between different single cells and to detect (and even quantify) rare aberrant cells.

    Kevin Tsia

    The University of Hong Kong

    Kevin Tsia received his Ph.D. degree at the Electrical Engineering Department, at UCLA, in 2009. He is currently an Associate Professor in Department of Electrical and Electronic Engineering at the University of Hong Kong. His research interest covers a broad range of subject matters, including ultra-fast real-time spectroscopy and microscopy for biomedical applications such as imaging flow cytometry, MHz optical coherence tomography. He received Early Career Award 2012-2013 by the Research Grants Council (RGC) in Hong Kong. He also received the Outstanding Young Research Award 2015 at HKU as well as 14th Chinese Science and Technology Award for Young Scientists in 2016. His recent research on ultrafast imaging technology, dubbed “ATOM” and "FACED", has been covered by local media and scientific magazines. He is author/coauthor of over 130 journal/conference papers and book chapters. He holds 2 granted and 3 pending US patents on ultrafast imaging technologies.

  • Addressing the Scalability of Human iPSC-derived Neurons for HTS Implementation and Phenotypic Screening

    Traditional high throughput screening (HTS) assays for neuronal targets employ non-primary non-human neuronal cells due to the scale necessary for HTS as well as the unreliable and economically demanding nature of primary neurons. The discovery of new drugs for neuropsychiatric disorders have further been hampered by lack of access to disease-relevant human primary neurons and appropriate disease models.

    Traditional high throughput screening (HTS) assays for neuronal targets employ non-primary non-human neuronal cells due to the scale necessary for HTS as well as the unreliable and economically demanding nature of primary neurons. The discovery of new drugs for neuropsychiatric disorders have further been hampered by lack of access to disease-relevant human primary neurons and appropriate disease models. Human induced pluripotent stem cell (hiPSC) technology can address some of the obstacles by allowing the generation of human neurons through (1) embryoid body (EB) formation, (2) cultivation on stromal feeder cells, and, (3) employing lineage specific differentiation factors. The former techniques for hiPSC reprogramming (1&2) are slow, variable, and not yet scalable for HTS applications. Straightforward methods to reproducibly differentiate hiPSCs to functional cortical induced neurons (iN) in less than two weeks by forced expression of a single transcription factor has been demonstrated but, never taken to the HTS scale (3). We have successfully recapitulated the aforementioned technique and leveraged the CRISPR technology to define the path to a plate-compatible format amenable for large-scale HTS implementation. The resulting iN cells exhibit appropriate genetic and fluorescent markers that give confidence of bonafide neuronal differentiation. Imminently, we intent to test the preliminary iN cells for their ability to post-mitotically increase synaptogenesis following treatment with LOPAC test compounds via staining for synaptophysin. Ultimately, we will determine reliability and reproducibility over time with industrial scale robotics. Furthermore, we also intend to leverage the CRISPR technology to create a library of disease-relevant-phenotypes from hiPSC-derived cellular models that will provide more opportunities for all biologists to study epigenetic mechanisms and scale-up screening initiatives with Scripps Research Institute Molecular Screening Center (SRIMSC).

    BanuPriya Sridharan

    The Scripps Research Institute Molecular Screening Center, Scripps Florida

    Postdoctoral-Associate at the Molecular Medicine Department in the Scripps Research Institute (Florida), a Ph. D. in Bioengineering with over 6 years of experience with 3D cell models for diagnostic and regenerative medicine applications. Proven record of publications with stem cell applications and enthusiastic about long-term, multidisciplinary collaborations geared towards hit identification and lead optimization. Strong personal interest in the development of the next generation of more physiologically relevant cell-based CRISPR assays relying on stem cells and either high-content or functional readouts.

  • Automating gene editing for deciphering cancer pathways using microfluidics

    In my presentation, I will describe our system to automate gene-editing processes specific to the CRISPR-Cas9 editing workflow, namely cell culturing, lipid-mediated transfection, and cellular analysis. Next, I will show results from optimizing our gene-editing platform to assess the impact of variations in several parameters on the efficacy of cell transfection and gene targeting using Cas9. Finally, we will demonstrate the broad applicability of the device showing results from a knockout loss-of-function screen that is tackling several oncogenes. Overall, this study aims at demonstrating that our genome editing-on-a-chip approach will greatly speed up validation of loss-of-function screens, including genome wide arrayed or pooled screens, at relatively low cost, with minute amount of material and without the need for enrichment analysis based on next-generation sequencing profiles as required by pooled screens.

    In recent years, we have witnessed a breakthrough in genome engineering technology, attributed to the gene-editing technique CRISPR-Cas9 (or often called CRISPR) that works like a pair of scissors to cut, insert or reorder specific genetic fragments, creating changes in the biological cell to understand gene function. CRISPR is full of promise and has already been used in a variety of applications such as to help create mosquitoes that do not transmit malaria (Hammond et al. 2016), to eradicate pathogen genomes from infected species (Ebina et al. 2013, Hu et al. 2014), and more recently to test and to battle cancer (Sanchez-Rivera and Jacks 2015, Shi et al. 2015, Platt et al. 2014). However, with the advent of this technology, there is still a lack of new treatments found for cancer.  Progress in this area has been hindered primarily by the lack of automation tools for manipulating, editing, and analyzing large genomes without any bias – this has limited our understanding of the genes and biological processes involved with cancer.  Here, I will describe how we have developed a new automated microfluidic tool that will target a specific set of genes in lung cancer cells (specifically H1299 cells) and determine which genes are modulators of cancer progression.  This new gene-editing tool powered by droplet-based microfluidics is being used to eliminate multiple perturbations within cells while the readouts will depend on cell population measurements.  Such a technology has emerged as a versatile liquid handling platform for automating biology (Shih et al. 2013) (Ng et al. 2015) and screening-based applications (Dressler, Casadevall, and deMello 2017).  In my presentation, I will describe our system to automate gene-editing processes specific to the CRISPR-Cas9 editing workflow, namely cell culturing, lipid-mediated transfection, and cellular analysis.  Next, I will show results from optimizing our gene-editing platform to assess the impact of variations in several parameters on the efficacy of cell transfection and gene targeting using Cas9. Finally, we will demonstrate the broad applicability of the device showing results from a knockout loss-of-function screen that is tackling several oncogenes.  Overall, this study aims at demonstrating that our genome editing-on-a-chip approach will greatly speed up validation of loss-of-function screens, including genome wide arrayed or pooled screens, at relatively low cost, with minute amount of material and without the need for enrichment analysis based on next-generation sequencing profiles as required by pooled screens.  We believe that this new method will further enhance our understanding of mechanisms related to cancers, which we hope can possibly lead to novel therapies options for those suffering from this disease.

    Hugo Sinha

    Concordia University

    I am French and American and grew up between both continents, following a bilingual curriculum my entire life. I moved to Montreal in 2012 and obtained an BSc in Biology with Distinction in 2016 from Concordia University. I immediately started a research-based MAsc in Electrical and Computer Engineering, attempting to bridge the gap between biology and engineering specifically by automating synthetic biology with digital microfluidics for high-throughput screenings. With the current stalling of traditional biological technique, I am excited by the avenues that this field is opening and look forward to continuing to work with microfluidics.

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

    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.

    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.

    Geoff Quinque

    GlaxoSmithKline

    I have been in my current group for six years at GlaxoSmithKline within the Screening, Profiling & Mechanistic Biology Department. Our group is responsible for assay development, high throughput screening and compound profiling and mechanistic characterization of small molecules from target validation through pre-clinical candidate selection. 

  • Development of a 3D-High Throughput Assay to Identify Compounds that Block the Growth of Patient Derived Glioma Stem Cells

    Glioblastoma (GBM) is the most aggressive primary brain cancer with a recurrence rate of nearly 100% and a 5-year survival rate less than 5%. Recent studies have shown that GBMs contain a small population of glioma stem cells (GSCs) that are thought to be a major contributor to chemotherapy resistance and responsible for relapse disease. Consequently, identifying compounds that modulate GSC proliferation may dramatically improve treatment response.

    Glioblastoma (GBM) is the most aggressive primary brain cancer with a recurrence rate of nearly 100% and a 5-year survival rate less than 5%. Recent studies have shown that GBMs contain a small population of glioma stem cells (GSCs) that are thought to be a major contributor to chemotherapy resistance and responsible for relapse disease. Consequently, identifying compounds that modulate GSC proliferation may dramatically improve treatment response. While high throughput screening (HTS) assays for drug discovery have traditionally used 2D cancer cell models, these monolayer cultures are not representative of tumor complexity. To increase translational relevance three-dimensional (3D) cell culture models have recently received more recognition. Furthermore, patient derived GSCs can be grown as neurospheres and in vivo can functionally recapitulate the heterogeneity of the original tumor. Using patient derived GSC enriched cultures we have developed a 1536-well spheroid-based cytotoxicity assay. In a pilot screening we have tested ~3,400 drugs comprising most Food and Drug Administration (FDA) approved Drugs. This automation-friendly assay yielded an average S/B of 181.3 ± 1.81 and Z’ of 0.77 ± 0.02 demonstrating a robust assay. Importantly, several compounds were identified as potential anti-GBM drugs from this pilot screen, demonstrating the applicability of this assay for large scale HTS. These studies may provide a basis for expedited drug repositioning into a GBM clinical study due to their well characterized pharmacology and safety profile in humans. 

    Victor Quereda

    The Scripps Research Institute

    I am a Senior Research Associate in Dr. Derek Duckett’s laboratory (The Scripps Research Institute, Florida). My studies focus mainly on the biology of cancer and drug discovery fields. As part of a team and using a multidisciplinary approach we are developing novel small molecule inhibitors to block the growth of Glioma Stem Cells, a major contributor to chemotherapy resistance and responsible for relapse disease in Glioblastoma. In collaboration with the Lead Identification Division at Scripps Florida we have generated a 3D-high throughput method to identify novel inhibitors of Glioma Stem Cell growth. This technique together with a battery of other research methods will be used to identify and validate compounds which could be use alone or in combination to maximize their killing effect in Glioblastoma.

  • Something old, something new: Improving genome editing efficiency over CRISPR with a new generation of TALE nucleases

    Taking advantage of the ability to design TALENs to target any sequence and the observation that the success of SNP editing is highly influenced by the proximity of the cut to the desired edit site, we also demonstrate that TALENs can facilitate superior HDR editing efficiency compared to Cas9 by being able to position TALENs at the SNP site regardless of the sequence. This is especially relevant in editing genomic regions with a low abundance of PAMs.

    Genome editing has become easier with the advent of CRISPR-Cas9. However, the CRISPR system has the drawback of requiring a sequence motif (PAM) in order to bind and cleave genomic DNA. Attempts to overcome this limitation have been made by developing a suite of orthogonal Cas9s through directed engineering or through isolation of Cas9 variants with novel PAMs. A more universal approach can be achieved by using Transcription Activator-Like Effector Nucleases (TALENs). In the shadows of the CRISPR revolution, TALENs have been engineered to remove their binding site requirement for a 5’ T, thereby removing any specific sequence requirement. In parallel, improved editing has been achieved through delivery of TALEN mRNA via electroporation and we have developed a high throughput assembly method using pre-made RVD libraries which allows rapid production of TALEN mRNA in a day. We demonstrate that when using TALEN mRNA we can achieve high cleavage efficiency in a variety of cells. Taking advantage of the ability to design TALENs to target any sequence and the observation that the success of SNP editing is highly influenced by the proximity of the cut to the desired edit site, we also demonstrate that TALENs can facilitate superior HDR editing efficiency compared to Cas9 by being able to position TALENs at the SNP site regardless of the sequence. This is especially relevant in editing genomic regions with a low abundance of PAMs.

    Jason Potter

    Thermo Fisher Scientific

    Genome Engineering, Protein Engineering, general molecular biology

  • Answers to questions not yet asked: Informatics strategy applied to scientific questions

    This presentation will describe how we used different technologies to address the specific needs in various scientific domains in a sustainable way. Topics such as software architecture, data integration, visualization will be considered.

    The amount of scientific data generated in current life science research is too large to be analyzed without informatic tools. While automation and new statistical algorithms provide useful tools for the analysis of large amounts of data, one also needs to ask the appropriate scientific questions to pursue discovery. This presentation will describe how we used different technologies to address the specific needs in various scientific domains in a sustainable way. Topics such as software architecture, data integration, visualization will be considered.

    Yohann Potier

    Novartis Institute for Biomedical Research

    Yohann is a Senior Principal Analyst at the Novartis Institute for Biomedical Research. He studied biotechnology and informatics in France followed by a Ph.D. in computational chemistry at the University of Zurich. Yohann joined PerkinElmer Informatics (formerly CambridgeSoft) as a business analyst where he worked with various life sciences customers to deliver informatics solutions. He has been working for the past 3 years at Novartis in the Scientific Information Systems team. During this time, Yohann worked with scientists and engineers from Novartis providing Informatics tools to perform cutting edge biology research in a collaborative open science environment.

  • High throughput 2D and 3D cell and whole-organism screenings in nanoliter format on Droplet-Microarray platform

    Here I will present our latest developments and results on compound screenings on patient-derived leukemia cells, tumor spheroids and embryonic bodies. Droplet-Microarray is universal platform that is compatible with various biological assays including compound screenings and transfection-based assays on different cell types (adherent and suspension cells, stem cells, and primary cells), 3D spheroids, hydrogels and embryos. We believe that this technology will open a new opportunities for high-throughput screenings that were not affordable or possible with other technologies till now.

    Small molecule high-throughput screenings are essential for the fields of drug discovery and toxicology. Hundreds of millions of compounds are screened every year. In these screenings, compounds are tested against molecules (biochemical screens), cells, 3D cellular systems and even whole organisms. Routine screenings in academia and pharma industry are performed in microtiter plates. The main drawbacks of using microplates for large experiments are, first, relatively high volumes and therefore high reagent and cell consumption, and, second, requirement of pipetting robotics. Due to these reasons not every biological laboratory can afford high throughout experiments. Another essential drawback is incompatibility with large screenings of rare but physiologically relevant cells such as patient-derived primary and stem cells due to restricted amount of cell material. We have developed a technology that allows for screenings of cells in 2D and 3D environment and of whole-organism in miniaturized array format. Droplet-Microarray technology is based on patterns of hydrophilic spots separated from each other by superhydrophobic, water repellent, regions. The difference in wettability of spots and borders generates the effect of discontinuous dewetting and enables spontaneous, without pipetting, formation of arrays of separated droplets of nanoliter to microliter volumes trapping live cells and even small animals. In the past years we developed all necessary protocols for culturing cells in 2D and 3D environment, parallel addition of compounds and reagents to individual droplets and performing various phenotypic assays with read-out based on microscopy. Here I will present our latest developments and results on compound screenings on patient-derived leukemia cells, tumor spheroids and embryonic bodies. Droplet-Microarray is universal platform that is compatible with various biological assays including compound screenings and transfection-based assays on different cell types (adherent and suspension cells, stem cells, and primary cells), 3D spheroids, hydrogels and embryos. We believe that this technology will open a new opportunities for high-throughput screenings that were not affordable or possible with other technologies till now.

    Anna Popova

    Institute of Toxicology and Genetics (ITG) , Karlsruhe Institute of Technology

    Dr. Popova graduated from the department of Cell Biology and Immunology of the Faculty of Biology, Lomonosov Moscow State University in Russia. She performed her M.Sc. on “Investigation of polymorphism of latent membrane protein 1 of Epstein-Barr virus” in Institute for Carcinogenesis, Blokhin Cancer Research Center, Moscow. While working on her Master’s Degree she performed part of the project in Institute for Virus Research, Kyoto University, Kyoto, Japan. After graduation Dr. Popova worked as junior scientist in Engelhardt Institute of Molecular Biology, Moscow, Russia on “Mechanisms of termination of protein translation”. During this project she worked as a guest researcher in Institute for Medical Physics and Biophysics, University Hospital Charite, Berlin, Germany. Dr. Popova obtained her Ph.D. in Department of Dermatology and Allergology, University Medical Centre Mannheim, University of Heidelberg, Germany. Since January 2014 Dr. Popova is working as postdoctoral fellow in Institute of Toxicology and Genetics (ITG), Karlsruhe, Germany.

  • A High Throughput Imaging Assay for the Quantification of Gene Expression Dynamics at the Single Cell Level

    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.

    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.

    Gianluca Pegoraro

    National Cancer Institute/NIH

    Gianluca Pegoraro uses high-throughput imaging to identify and characterize molecular mechanisms regulating basic cellular processes such as nuclear architecture, gene expression and the DNA damage response. 

  • Cloud-based qPCR analysis software for rapid-throughput screening of antisense oligonucleotides

    Advances in automation, miniaturization and microfluidics have enabled researchers to develop high-throughput qPCR assays that generate thousands of data points per day creating an increased burden on downstream data management, computation and analysis. Here we present a software tool to complement these high-throughput methods by simplifying the computation and visualization of screening results for standard-curve experiments.

    One distinct advantage of the antisense oligonucleotide (ASO) platform has over other therapeutic approaches is the ability to rapidly screen for safe and effective ASO compounds against new molecular targets.  While RNA screening assays will often utilize sequencing technology like RNA-Seq, today, the gold standard for rapid and cost effective gene expression quantification remains quantitative polymerase chain reactions (qPCR).  Advances in automation, miniaturization and microfluidics have enabled researchers to develop high-throughput qPCR assays that generate thousands of data points per day creating an increased burden on downstream data management, computation and analysis.  Here we present a software tool to complement these high-throughput methods by simplifying the computation and visualization of screening results for standard-curve experiments.  Our qPCR pipeline uses modern cloud technology provided by Amazon Web Services to permit users to dynamically generate workflows for a vast array of plate-based qPCR assays.  Our visualization tools make use of the HELM notation (Hierarchical Editing Language for Macromolecules) to both visualize the genomic targets as well as the distinct chemistries employed in SAR screens.

    Donald Milton

    Ionis Pharmaceuticals

    I have over 20 years of biotech software experience in both academic and industry settings.  I began my career at Molecular Simulations Inc (now Biovia) developing bioinformatics tools before the first draft of the Human Genome. After a short diversion in the aviation industry, I returned to bioinformatics as a developer at the Protein Data Bank where I created and managed some notable projects including the ImmersivePDB; highlighted in the book “Advances in Computers” by Marvin Zelkowitz.   I joined the Research Bioinformatics Department at Genentech (gRED) in 2010 and managed multiple software projects for core labs including research pathology and next-generation sequencing.   In 2013 I accepted a position at Ionis Pharmaceuticals where I currently lead software development for the Drug Discovery department.  My current focus is in-silico oligonucleotide drug design and software to support high-throughput in-vitro screening. 

  • Mining novel CRISPR systems for new genome engineering tools

    ​CRISPR systems exist broadly throughout prokaryotic life and constitute an incredible diversity of adaptive immunity mechanisms. Here we present a framework to computationally mine and experimentally characterize novel CRISPR systems for useful bioengineering tools. ​

    CRISPR systems exist broadly throughout prokaryotic life and constitute an incredible diversity of adaptive immunity mechanisms. Here we present a framework to computationally mine and experimentally characterize novel CRISPR systems for useful bioengineering tools.

    Patrick Hsu

    Salk Institute for Biological Studies

    More information coming!

  • Primary Cell 3D Pancreatic Cancer Organoid Models for Phenotypic High-throughput Therapeutic Screening

    ​Pancreatic cancer remains a leading cause of cancer-associated death, with a median survival of ~ 6 months and 5-year survival rate less than 8%. The tumor microenvironment promotes tumor initiation and progression, and is associated to cancer metastasis and drug resistance.

    Pancreatic cancer remains a leading cause of cancer-associated death, with a median survival of ~ 6 months and 5-year survival rate less than 8%. The tumor microenvironment promotes tumor initiation and progression, and is associated to cancer metastasis and drug resistance. Traditional high throughput screening (HTS) assays for drug discovery use lab adapted 2D monolayer cancer cell models, which inadequately recapitulate the physiologic context of cancer. Primary cell 3D cell culture models have recently received renewed recognition not only due to their ability to better mimic the complexity of in vivo tumors but, are now cost effective and efficient. Here we describe phenotypically relevant 3D cell culture in ultra-low-attachment high density 384 and 1536 well plates using a magnetic force-based bioprinting technology. We have validated HTS amenable 2D and 3D spheroid/organoid-based cytotoxicity assays using 4 pancreatic cancer-associated cell lines against 5 known anti-cancer agents, and thereby screened ~3,400 drugs from Approved Drug and National Cancer Institute (NCI) collections. Assay quality was notable with Z’ averaging >0.8 across all assays and cell lines. As anticipated, results from the 3D screen were significantly different from the parallel screen performed on 2D cell monolayers. Collectively, these data indicate that a complex 3D cell culture can be adapted for quantitative HTS and may improve the disease relevance of assays used for therapeutic screening. Further analysis provides a basis for expedited translation into clinical study due to their well-known pharmacology in humans.

    Shurong Hou

    The Scripps Research Institute - FL

    Shurong Hou is a postdoctoral fellow in The Scripps Research Institute Molecular Screening Center, who has dedicated herself to early drug discovery. She is interested in assay development of biochemical and cell-based assays for high throughput screening, especially developing physiologically relevant 3D tumor models for cancer drug discovery.

  • Leveraging label-free dynamic mass redistribution technology to study G protein-coupled receptor ligand pharmacodynamics

    ​Label-free dynamic mass redistribution (DMR) technology represents a powerful approach to studying G protein-coupled receptor (GPCR) signaling in cultured cells.

    Label-free dynamic mass redistribution (DMR) technology represents a powerful approach to studying G protein-coupled receptor (GPCR) signaling in cultured cells. Recently, our laboratory has leveraged DMR to study multiple facets of human adrenergic receptor biology, including:
    1) Deconvoluting the α1D-adrenergic receptor (ADRA1D) PDZ-protein macromolecular complex. Tandem-affinity purification/mass spectrometry identified novel PDZ-protein interactors syntrophin and scribble for the ADRA1D in human cells. DMR assays subsequently revealed syntrophin and scribble differentially enhance agonist efficacy. 2) Investigating the importance of PDZ-ligands for GPCR agonist pharmacodynamics. DMR screens were used to assess the importance of PDZ-protein interactions for agonist pharmacodynamics of 24 human GPCRs containing PDZ-ligands in their distal C-termini. DMR agonist concentration response-curves were generated for full length and PDZ-ligand truncated GPCRs expressed in human cells. 3) Structure-function analysis of GPCR structural domains. SNAP-technology revealed the ADRA1D undergoes constitutive N-terminal domain proteolytic cleavage in human cells. DMR assays indicate this N-terminal cleavage event enhances ADRA1D signaling properties. 4) Identification and pharmacological characterization of endogenous adrenergic receptors in human cancer cell lines. DMR assays examining subtype-selective adrenergic receptor drugs revealed previously undetectable adrenergic receptors in SW480 human colon carcinoma cells. Schild plot analysis with adrenergic receptor subtype-selective antagonists permitted pharmacological characterization of functional adrenergic receptors expressed in SW480 cells. DMR data facilitated subsequent examination of adrenergic receptor stimulation on SW480 cell fate. To conclude, label-free DMR technology is a diverse, powerful tool that can be used to study both transfected and endogenous GPCRs in cultured cells; to deconvolute functional modules of GPCR macromolecular complexes; to address the importance of specific structural domains for GPCR function; and can be combined with traditional analytical methods to facilitate pharmacological characterization of ligand-receptor interactions.  

    Chris Hague

    University of Washington - Pharmacology

    Dr. Hague's research focuses on the molecular pharmacology of G protein-coupled receptors (GPCRs). The Hague lab currently focuses on proteomic identification of GPCR macromolecular complexes in human cells, and molecular deconvolution of functional roles of de novo interacting proteins. The long-term goal of the Hague lab is to identify novel GPCR protein-protein interaction interfaces that have the potential to be targeted by novel small molecules to modulate GPCR function. Dr. Hague received his B.Sc from McMaster University (Hamilton, ON, Canada) in Pharmacology, his Ph.D. from Creighton University (Omaha, NE) in Pharmacology, and performed his post-doctoral fellowship in the Department of Pharmacology at Emory University (Atlanta, GA). Dr. Hague has been a faculty member in the Department of Pharmacology at the University of Washington since 2005.

  • Accelerating clinical and translational research for biomarker discovery through advanced, standardized cell isolation methodologies

    ​Specimens are not meant to live in a freezer. Their sole purpose in life is to produce data. Biorepositories are critical to accelerating clinical and translational research technologies and discoveries. Human subject research depends on the availability of standardized biorepository methods for collection, storage, processing, and distribution of biological specimens alongside associated patient metadata.

    Specimens are not meant to live in a freezer. Their sole purpose in life is to produce data. Biorepositories are critical to accelerating clinical and translational research technologies and discoveries. Human subject research depends on the availability of standardized biorepository methods for collection, storage, processing, and distribution of biological specimens alongside associated patient metadata. Stanford Medicine’s growth across the Bay Area has created an opportunity for us to connect participants to bench-side research in ways never before possible. Our biobank has an emphasis on more advanced sample processing geared at downstream, functional analysis using viable cell suspensions. Work is often performed in tandem with specialized assay groups, such as the Human Immune Monitoring Center (directed by Dr. Holden Maecker) to leverage cutting-edge technologies such as CyTOF, single-cell RNA sequencing, flow cytometry, and immunoassay. Many of these assays require specimen types from humans that have been processed using very specific techniques and methodologies to prevent the introduction of artifacts. In particular, the standardization of the procedures for cell isolation is critical to the success of the translational research; by increasing throughput and minimizing ‘hands-on’ time, applications for biomarker discovery have a chance to be accelerated and reproduced.

    At Stanford Medicine, the lab of Dr. Irving Weissman has coordinated the build out of a unique biorepository dedicated to collection and advanced, standardized processing of tissue and tumors into viable single-cell suspensions. Over the course of the last two years, tumors with match normal tissue have been collected alongside archives of clinical, pathology and surgical notes. In November 2016, Sydney Gordon, a graduate student in Weismann’s lab, discovered the novel increased expression of PD-1 on tumor macrophages in colon cancer of mouse models. Sydney was hoping to translate her findings into humans and did so by taking advantage of Stanford’s biorepository. Within a matter of two months, Sydney was able to repeat her discovery on human samples that had been preserved for functional analysis. She validated her findings of increased PD-1 expression on human colon cancer tumors, opening the door to multiple discussions around new drug therapeutics in cancer immunotherapy. Key to her success was the standardization and care taken to procure and process the solid tissues into single-cell suspensions with minimal impact to the cell surface antigens and cryopreserve the cells viably. Automating parts of this pipeline presents an opportunity to greatly improve the throughput, while also standardizing the methodology away from technician variability.

    Rohit Gupta

    Stanford University

    I began my research at Stanford in 2003 and now oversee harmonization and alignment efforts for biobanking infrastructure, alongside directing the largest research focused, ambulatory care unit at Stanford, the Clinical and Translational Research Unit (CTRU). Both efforts are part of Spectrum’s vision to provide innovative and compliant resources for research services to the research community both locally and globally. Notably, I’ve led and established the biorepository and associated data infrastructure for multiple large-scale biobanks, including those associated with Spectrum, Parker Institute for Cancer Immunotherapy, Stem Cell Institute, Institute for Immunology/Transplantation/Infection, Blood and Bone Marrow Transplant Biobank, Google Baseline, and many more.

  • Novel Graphene Field Effect Biosensing Technology for Binding Kinetics

    ​We introduce a breakthrough electrical label-free biosensor that provides a new approach to measuring binding kinetics. This approach uses a label-free technique called Field Effect Biosensing (FEB) to measure biomolecular interactions.

    We introduce a breakthrough electrical label-free biosensor that provides a new approach to measuring binding kinetics. This approach uses a label-free technique called Field Effect Biosensing (FEB) to measure biomolecular interactions. Field effect biosensors use a semiconducting material to monitor changes in binding potential of biomolecules such as proteins, nuceotides, peptides, and small molecules conjugated to the semiconductor surface. Practical use of this technology for biology requires use of a biocompatible semiconductor such as graphene.  Graphene is a 2-dimensional sheet of sp2 hybridized carbon that is well known for its excellent electrical conductivity, high surface area, and unique biocompatibility. Basic electronic devices using graphene were first demonstrated in 2004; this work won the Nobel prize in 2010. In nanotechnology labs, graphene biosensors have pushed existing limits of detection for label free sensors and have shown the ability to measure a large range of biochemical interactions from detecting DNA SNPs to small molecules binding to GPCRs.

    We will present our architecture and implementation of graphene based FEB biosensors for label free kinetics. In our architecture, FEB measures the current through a graphene biosensor with targets conjugated to the surface and used as a functional active-biology gate dielectric. Any interaction or binding that occurs with the target causes a change in conductance that is monitored in real-time. We will also present data from our recently published research demonstrating sensitivity into the pM range to inflammation markers (IL-6) and Zika viral antigen (ZIKV NS1). High precision measurements of protein kinetics captured using this technology, commercially available as the Agile R100, are comparable to both ELISA and standard label free biomolecule characterization tools. Specifically, we show an improvement in signal-to-noise and in lower limit of detection. These results demonstrate that graphene-based platforms are highly attractive biological sensors for next generation kinetics characterization.

    Brett Goldsmith

    Nanomedical Diagnostics

    Late Night with LRIG

  • Developing and Implementing a Scientific Data Strategy for Pharma

    As the use of predictive modeling, analytics and machine learning increases to address the challenges of declining R&D productivity and increasing pressures for demonstrating product value, a cohesive scientific data strategy and scalable approaches are required to handle the ever increasing variety of data types, data sources, data models and analytics patterns.

    The discovery research paradigm requires integration of a broad range of human biology data and knowledge in order to generate and explore diverse hypotheses. Scientists often spend a significant amount of their time and resources in analytics and informatics projects trying to find, access, understand, curate and integrate data. While scientific information is generally managed effectively for its primary use, it often lacks the accessibility and context that facilitates secondary use and cross-functional integration on-demand. As a result, much of the research informatics efforts across the pharmaceutical industry are focused on creating single point solutions to these challenges within a particular problem space or functional area. As the use of predictive modeling, analytics and machine learning increases to address the challenges of declining R&D productivity and increasing pressures for demonstrating product value, a cohesive scientific data strategy and scalable approaches are required to handle the ever increasing variety of data types, data sources, data models and analytics patterns. It also calls for a reevaluation of data access rules, accountability, and data stewardship culture to realize business strategic goals while managing risk.

    Nicole Glazer

    Merck

    Nicole is currently a director in Merck's Scientific Information Management organization. She is an epidemiologist by training and began her career in academia conducting large-scale observational research studies before joining Merck. She now leads the Scientific Data Development team at Merck, responsible for defining and executing a data strategy to improve the utility of Merck’s scientific information across the company’s drug development pipeline through data-centric, analytics-focused solutions.

  • Supervising the Unsupervised: Maximizing Biological Impact in Cellular Imaging

    Avoiding “black box” algorithms, instead favouring those which could be interrogated by biological and data scientists alike, led to faster and more relevant analysis cycles, and helped cement a “marriage” between statistical significance and biological relevance. Here, we discuss the analytical methodologies invoked to achieve this.

    The exciting challenge of imaging data is the sheer number of options to recognize and retrieve meaningful content; while some turn to the ever-growing algorithmic tool-shed of machine learning, others utilize a priori knowledge of the biology at hand to arrive at the answer. With a balance between these two paramount, we implemented a hybrid workflow to re-analyse compound data in a phenotypic COPD screen. Allowing biological subject matter expertise to guide data-driven decisions, and vice-versa, we used a combination of knowledge-based, supervised, and unsupervised methods to de-convolute patient-derived macrophages into patient-specific subpopulations. At this level of granularity, we could discern previously masked effects of compounds on healthy and diseased cells, both in their physical properties and population makeup. These differences proved to be key when understanding the underlying phenotypic changes. Avoiding “black box” algorithms, instead favouring those which could be interrogated by biological and data scientists alike, led to faster and more relevant analysis cycles, and helped cement a “marriage” between statistical significance and biological relevance. Here, we discuss the analytical methodologies invoked to achieve this.

    Finnian Firth

    GlaxoSmithKline

    Degree in mathematics and computational biology from Cambridge University. Started at GSK October 2016.

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

    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.

    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). 

    Oliver Fiehn

    UC Davis, NIH West Coast Metabolomics Center

    Prof. Oliver Fiehn has pioneered developments and applications in metabolomics with over 220 publications to date. He aims at understanding metabolism on a comprehensive level. In order to leverage data from these diverse sets of biological systems, his research laboratory focuses on standardizing metabolomic reports and establishing metabolomic databases, for example the MassBank of North America that hosts over 200,000 public metabolite mass spectra and BinBase, a resource of over 100,000 samples covering more than 2,000 studies. He develops and implements new approaches and technologies in analytical chemistry for covering the metabolome, from increasing peak capacity by ion mobility to compound identifications through cheminformatics workflows and software. He collaborates with a range of investigators in human diseases through statistics, text mining and pathway-based mapping. He studies fundamental biochemical questions from metabolite damage repair to the new concept of epimetabolites.

  • Identification of new negative regulators of ciliogenesis in breast cancer cells through high-throughput siRNA screening

    Three-dimensional spheroid assays are considered valid models to recapitulate features of tumors and, combined with new technologies of automated imaging and analysis, will contribute to a better understanding of ciliogenesis and breast cancer and to an important step in anticancer drug research.

    Breast cancer is a major cause of death in women in the world. The basal subtypes, also recognized as triple negative breast cancers (TBNC), are the most aggressive type and account for the highest mortality rate in patients. Currently, there are no FDA approved targeted therapies for TNBC, and innovative approaches are necessary to develop new therapeutic options. The primary cilium is a membrane-bound, cell surface projection assembled from centrosomes and singularly expressed in the majority of cells in the human body, serving as a cellular 'antenna' in the recognition and transduction of extra-cellular stimuli, such as growth factors. This organelle forms during cellular quiescence and disassembles when cells enter the cell cycle and proliferate. Interestingly, primary cilia are frequently lost in malignant tumors, such as breast tumors. Thus primary cilia may play a repressive role in regulating cell proliferation and could lower breast cancer development. In order to identify negative regulators of ciliogenesis that could represent target for new drugs, we performed a high content screen using an arrayed library containing pooled siRNAs targeting 23,000 human genes in triplicate on Hs578T cells, a basal B breast cancer cell line which forms cilia at low frequency. Detecting cilia by automated immunofluorescence staining and imaging, we identified 350 candidate genes (~1-2%) that increased the number of ciliated cells. Candidate genes were retested in secondary screens in additional cell lines to distinguish the genes involved in cilia formation common to all cell lines and the ones specific to the (sub)types of (breast) cancer. There is overwhelming evidence that in vitro three-dimensional tumor cell cultures more accurately reflect the complex in vivo microenvironment than simple two-dimensional cell monolayers. In order to test the candidate genes from the 2D cell culture experiments in a tertiary screen to see their effect on tumor growth, migration and invasion, we grew Hs578T cells in ultra-low attachment (ULA) 96-well roundbottomed plates, where tumor cell suspensions formed a three-dimensional structure within 24 h. Three-dimensional spheroid assays are considered valid models to recapitulate features of tumors and, combined with new technologies of automated imaging and analysis, will contribute to a better understanding of ciliogenesis and breast cancer and to an important step in anticancer drug research. 

    Marion Failler

    NYU Pelmutter Cancer Institute

    Since my Pharmacy studies, I wanted to work in basic research. I did an internship in the Neuropharmacology Center of the Pharmacy University of Milan where I learned basic proteomic research (Mallei A, et al., 2014). During my Master’s degree, I was in charge of the validation of a small scale siRNA screen on ciliogenesis. During my Ph.D., I focused on the characterization of two new Nephronophthisis candidate genes (Failler M et al., 2014). I used high resolution imaging (SIM and STED microscopy) and participated in setting up this imaging platform at our institution (Alby C et al., 2015). I now wish to continue understanding the role of ciliary dysfunction in cancer. Under the supervision of my mentor, I performed high-throughput siRNA screen in a breast cancer cell lines and identified candidate genes that allow cilia growth in these cells. 

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

    This presentation will review 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.

    We work in the framework of the Human Induced Pluripotent Stem Cells Initiative (HipSci) project, funded by the Wellcome Trust and MRC (www.hipsci.org). 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.

    Davide Danovi

    King's College London

    Davide Danovi holds an MD from University of Milan and a PhD in Molecular Oncology from the European Institute of Oncology where he demonstrated the causative role of the HdmX protein in human cancer. He completed his postdoctoral training working with Prof. Austin Smith and Dr. Steve Pollard at the University of Cambridge and at University College London where he developed a screening platform to isolate compounds active on human neural stem cells from normal or brain tumour samples. Prior to his current role, he worked as principal scientist at a novel biotechnology company founded to isolate drugs for regenerative medicine using innovative stem cell technologies.

  • SLAS2018 Innovation Award Finalist: Optical tools for single-cell manipulations and sequencing

    Here we describe cell labelling via photobleaching (CLaP), a method that enables instant, specific tagging of individual cells based on a phenotypic classification. This technique uses laser irradiation for crosslinking biotin on the plasma membrane of living cells and fluorescent streptavidin conjugates.

    Classical examination of tissue and cellular samples heavily relies on microscopy platforms, where molecular probes and a myriad of contrast agents are routinely used to investigate the molecular biology of cells. Nevertheless, a versatile, efficient and non-invasive approach to tag individual cells chosen upon observation is still lacking.

    Here we describe cell labelling via photobleaching (CLaP), a method that enables instant, specific tagging of individual cells based on a phenotypic classification. This technique uses laser irradiation for crosslinking biotin on the plasma membrane of living cells and fluorescent streptavidin conjugates. Furthermore, the very same instrument used to image cells can tag them based on their morphological characteristics, dynamic behavior and localization within the sample at a given time, or any visible feature that distinguishes particular cells from the ensemble. The incorporated mark is stable, non-toxic, retained for several days, and transferred by cell division but not to adjacent cells in culture. We combined CLaP with microfluidics-based single-cell capture followed by PCR assays and transcriptome-wide next-generation sequencing. We computed a number of quality control metrics to verify that CLaP does not interfere with protocols of sample preparation for transcriptomic experiments. To the best of our knowledge, CLaP is the first simple technology that allows correlating spatial and molecular information visible under a microscope when cells are individually sequenced. 

    Santiago Costantino

    University of Montreal

    Santiago Costantino received his PhD in ultrafast lasers from the Physics Department of the University of Buenos Aires in 2003. He moved to Canada for his postdoctoral training in microscopy and neuroscience at McGill University. He established his biophotonics lab at the Maisonneuve-Rosemont Hospital, Montreal University, in 2007. He is now an associate professor and his current research spans microengineering, image analysis and the development of medical tools for vision health.

  • MALDI-TOF-MS - A label free technology for high throughput screening

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

    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.

    Frank Buettner

    Boehringer-Ingelheim Pharma GmbH & Co.KG

    Laboratory Leader

  • Modeling the contribution of common variants to schizophrenia risk.

    Schizophrenia (SZ) is a debilitating psychiatric disorder for which the complex genetic mechanisms underlying the disease state remain unclear. Whereas highly penetrant variants have proven well-suited to human induced pluripotent stem cell (hiPSC)-based models, the power of hiPSC-based studies to resolve the much smaller effects of common variants within the size of cohorts that can be realistically assembled remains uncertain.

    Schizophrenia (SZ) is a debilitating psychiatric disorder for which the complex genetic mechanisms underlying the disease state remain unclear. Whereas highly penetrant variants have proven well-suited to human induced pluripotent stem cell (hiPSC)-based models, the power of hiPSC-based studies to resolve the much smaller effects of common variants within the size of cohorts that can be realistically assembled remains uncertain. We identified microRNA-9 as having significantly downregulated levels and activity in a subset of SZ hiPSC-derived neural progenitor cells NPCs, a finding that was corroborated by a larger replication cohort and further validated by an independent gene-set enrichment analysis of the largest SZ genome-wide association study (GWAS) to date. Overall, this demonstrated a remarkable convergence of independent hiPSC- and genetics-based discovery approaches.  In developing this larger case/control SZ hiPSC cohort of hiPSC-derived NPCs and neurons, we identified a variety of sources of variation, but by reducing the stochastic effects of the differentiation process, we observed a significant concordance with two large post mortem datasets. We predict a growing convergence between hiPSC and post mortem studies as both approaches expand to larger cohort sizes. Meanwhile, we have been integrating CRISPR-mediated gene editing, activation and repression technologies with our hiPSC-based neural platform, in order to develop a scalable system for testing the effect of a manipulating the growing number of SZ-associated variants and genes in NPCs, neurons and astrocytes. Altogether, our objective is to understand the cell-type specific contributions of SZ risk variants to disease predisposition.

    Kristen Brennand

    ISMMS

    Kristen Brennand, PhD is an Associate Professor of Genetics and Genomics, Neuroscience and Psychiatry at the Icahn School of Medicine at Mount Sinai, in New York, New York. She trained in developmental and stem cell biology at Harvard University and in neurobiology during postdoctoral at the Salk Institute for Biological Studies. By combining expertise in stem cell biology and neurobiology, she has pioneered a new approach by which to study psychiatric disease. Dr. Brennand’s work is funded by the National Institutes of Health, the New York Stem Cell Foundation, the Brain Research Foundation and the Brain and Behavior Research Foundation.

  • Development of an Automated High Throughput CHO Stable Pool Platform for Generating Large Protein Collections

    Innovative solutions ranging from a new software Dashboard to manage projects and execute processes, a recently developed non-invasive Flask Density Reader and an upgraded harvest and purification system compatible with magnetic beads will be presented.

    Recombinant protein expression and purification is a central process in biomedical research and Chinese hamster ovary (CHO) cells are a primary workhorse for protein production from mammalian cells.  GNF has developed a robust suite of software and automated systems to support high throughput CHO (HT-CHO) stable pool establishment, archive of cell banks and protein purification.  Pools are established in 96-well plates, maintained until they are ready for scale up, and then expanded into an AutoFlask™.  Once cells reach the desired density, cell bank archives are created and one or more batch production AutoFlasks™ are inoculated depending on the amount of protein requested.  As an example, a single 50mL culture expressing a human IgG1 antibody typically yields 10 milligrams of protein.  Innovative solutions ranging from a new software Dashboard to manage projects and execute processes, a recently developed non-invasive Flask Density Reader and an upgraded harvest and purification system compatible with magnetic beads will be presented.  This platform enables cost-effective, facile production of proteins at quantities and quality useful for early stage drug discovery tasks such as screening, protein engineering and even in vivo studies. 

    Paul Anderson

    Gnf Systems

    BS Chemical Engineering, UCSB, 2003; MS Biomedical Engineering, Case Western Reserve University, 2005; Senior Automation Engineer, Genomics Institute of the Novartis Research Foundation, 2005-Present

  • Activity-based proteomics – protein and ligand discovery on a global scale

    In this lecture, I will describe the application of ABPP to discover and functionally annotate proteins in mammalian physiology and disease. I will also discuss the generation and implementation of advanced ABPP platforms for proteome-wide ligand discovery.

    Genome sequencing projects have revealed that eukaryotic and prokaryotic organisms universally possess a huge number of uncharacterized proteins. The functional annotation of these proteins should enrich our knowledge of the biochemical pathways that support human physiology and disease, as well as lead to the discovery of new therapeutic targets. To address these problems, we have introduced chemical proteomic technologies that globally profile the functional state of proteins in native biological systems. Prominent among these methods is activity-based protein profiling (ABPP), which utilizes chemical probes to map the activity state of large numbers of proteins in parallel. In this lecture, I will describe the application of ABPP to discover and functionally annotate proteins in mammalian physiology and disease. I will also discuss the generation and implementation of advanced ABPP platforms for proteome-wide ligand discovery.

    Benjamin Cravatt

    Department of Molecular Medicine, The Scripps Research Institute

    Benjamin F. Cravatt is a Professor and Co-Chair of the Department of Molecular Medicine at The Scripps Research Institute. His research group is interested in understanding the roles that enzymes play in physiological and pathological processes, especially as pertains to the nervous system and cancer.