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

    Contains 1 Component(s) Recorded On: 02/05/2018

    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.

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

    Contains 1 Component(s) Recorded On: 02/05/2018

    ​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.

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

    Contains 1 Component(s) Recorded On: 02/05/2018

    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

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

    Contains 1 Component(s) Recorded On: 02/05/2018

    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.

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

    Contains 1 Component(s) Recorded On: 02/05/2018

    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. 

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

    Contains 1 Component(s) Recorded On: 02/05/2018

    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.

  • How AstraZeneca is Revolutionizing Sample Management with Acoustic Tube-based Technologies

    Contains 2 Component(s) Recorded On: 12/12/2017

    Learn about AstraZeneca’s vision to enhance their sample management capabilities by standardizing on acoustic liquid handling throughout sample storage and screening preparation workflows.

    Learn about AstraZeneca’s vision to enhance their sample management capabilities by standardizing on acoustic liquid handling throughout sample storage and screening preparation workflows. In collaboration with Labcyte Inc., Brooks Life Science Systems and Titian, AstraZeneca is helping bring to market an Echo® qualified acoustic tube, in conjunction with a fully automated system, that improves throughput, sample integrity and the overall reliability of screening data. Transferring samples directly from storage tubes to assay plates will not only help AstraZeneca increase throughput, but will reduce operating costs by enabling better conservation of precious samples and eliminating the need for tips and excess labware during processing.  

    Kevin Cross will discuss the benefits of adopting the new acoustic tube technology and how AstraZeneca is approaching its integration into their sample management infrastructure. Labcyte’s Justin Jager will also provide an overview of the new automated system and highlight how it will address the needs of the sample management teams at AstraZeneca.

    Kevin Joseph Cross

    Senior Scientist, Sample Management, AstraZeneca

    An innovative scientist with specialist knowledge of acoustic dispensing, Kevin’s experience extends to collaborative working both internally and externally; developing creative ideas, concepts and solving technical problems. As technical lead on AstraZeneca’s Collaborative Acoustic Tube project Kevin is dedicated to the development of the new Acoustic Tube and Work Cell.

    Justin Jager

    Product Manager, Lab Automation, Labcyte

    Justin is the Automation Product Manager at Labcyte, responsible for overseeing the Access™ workstation and Tempo™ control software. He has a BS in Biology from Santa Clara University and has many years of experience working with lab automation in a HTS lab and as an Automation Field Applications Specialist for Agilent and HighRes Biosolutions.

  • Detecting small molecule non-covalent binders utilizing SAMDI and the Bruker MALDI-TOF – Proof of concept for a new screening format

    Contains 2 Component(s) Recorded On: 10/17/2017

    Advances in technology afford the opportunity to revisit old challenges of detecting compound binding from mixtures.

    Advances in technology afford the opportunity to revisit old challenges of detecting compound binding from mixtures. We combined the ability of mass spectrometry to unambiguously identify and resolve compounds from complex mixtures of analytes with Self-Assembled Monolayers and matrix-assisted laser Desorption Ionization (SAMDI) technology.   SAMDI technology minimizes “hot spots” by uniformly saturating the surface with captured protein. The ability to wash SAMDI targets decreases interferences from salts and detergents and the Bruker ultrafleXtreme™ MALDI-TOF delivers high resolution data with minimal matrix signal interference.  

    This novel screening format uses affinity capture of a target protein of interest that has been incubated with a pool of compounds. Subsequent ionization of the protein and any bound analyte enables the inferred identification of non-covalent compound interactions.  By utilizing a pooled library format and the high speed of the Bruker ultrafleXtreme™ laser, we aim to maximize the throughput of MS-based screening irrespective of enzyme activity. Customized Genedata Expressionist® data analysis workflows identify the hits as masses in each well and hit calling will be determined based on the ratios in samples with protein vs samples without protein.

    Erica C. VanderPorten

    Senior Scientific Researcher, Genentech

    Erica is a Senior Scientific Researcher at Genentech and joined the Department of Biochemical and Cellular Pharmacology in Small Molecule Drug Discovery in 2009. The department develops assays to support medicinal chemistry efforts, characterize and understand compound mechanism of action, and investigate new lead finding technologies. Her recent focus includes exploring mass spectrometry based technologies amenable for high throughput screening. Prior to joining Genentech Erica worked at Sunesis Pharmaceuticals in drug discovery and Five Prime Therapeutics. She obtained her B.S. in Biochemistry and Molecular Biology from the University of California, Davis.

    SLAS Discovery 

    Now available ahead-of-print: Preview the October 2017 special issue on Advances in MALDI Mass Spectrometry for Drug Discovery

    Identification of Small-Molecule Noncovalent Binders Utilizing SAMDI Technology

    Secretory Proteome Analysis of Streptomycin-Resistant Mycobacterium tuberculosis Clinical Isolates

    A Systematic Investigation of the Best Buffers for Use in Screening by MALDI–Mass Spectrometry

    Filter Plate–Based Screening of MIP SPE Materials for Capture of the Biomarker Pro-Gastrin-Releasing Peptide

    Microenvironment Tumor Metabolic Interactions Highlighted by qMSI: Application to the Tryptophan-Kynurenine Pathway in Immuno-Oncology

    Secretory Proteome Analysis of Streptomycin-Resistant Mycobacterium tuberculosis Clinical Isolates

    Also from SLAS Discovery  

    Matrix-Based Activity Pattern Classification as a Novel Method for the Characterization of Enzyme Inhibitors Derived from High-Throughput Screening

    Exemplifying the Screening Power of Mass Spectrometry Imaging over Label-Based Technologies for Simultaneous Monitoring of Drug and Metabolite Distributions in Tissue Sections

    Coupling Laser Diode Thermal Desorption with Acoustic Sample Deposition to Improve Throughput of Mass Spectrometry–Based Screening

    The Evolution of MALDI-TOF Mass Spectrometry toward Ultra-High-Throughput Screening: 1536-Well Format and Beyond

    SLAS Technology  

    Acoustic Sample Deposition MALDI-MS (ASD-MALDI-MS): A Novel Process Flow for Quality Control Screening of Compound Libraries

    Langartech: A Custom-Made MALDI Matrix Sprayer for MALDI Imaging Mass Spectrometry

    SLAS Electronic Laboratory Neighborhood 

    Exploring the Potential of Mass Spectrometry in Drug Discovery: A JBS Special Issue

    2015 SLAS Innovation Award Winner Jonathan Wingfield: Bringing Screening with Mass Spectrometry to the Next Level

    SLAS LabAutopedia

    Small Volume Pipetting

    Acoustic Droplet Ejection: Transfer of Low Nanoliter Volumes Between Microplates — Automation Considerations

    SLAS Webinars  

    High-Throughput Acoustic Mass Spectrometry: Development and Delivery of a Biochemical Screen

  • 3-Dimensional Assays: What Must Be Done for Setting Up and Validating for Downstream Microplate Reader and Imaging Applications

    Contains 2 Component(s) Recorded On: 09/26/2017

    Today’s webinar will focus on the cellular microenvironment and its importance when developing and screening cell-based assays using primary, stem cell, and immortalized cultures in 3D systems.

    This webinar is OPEN to both SLAS members and non-members. 

    Mammalian cell culture has long been an invaluable tool in cell biology, drug discovery, and regenerative medicine. Advances in our understanding of cell physiology and failures in clinical trials have provided the impetus to move away from our standard 2-dimensional (2D) systems to a more in-vivo-like or 3-dimensional (3D) environment. The advance of new technologies and screening methodologies have allowed scientists to assess more realistic cellular functionality. Today’s webinar will focus on the cellular microenvironment and its importance when developing and screening cell-based assays using primary, stem cell, and immortalized cultures in 3D systems.

    Bradley R. Larson

    Principal Scientist, BioTek Instruments, Inc

    Brad is a Principal Scientist at BioTek Instruments, INC., where he has worked since 2009. Prior to joining BioTek, he acquired extensive experience while employed in various capacities with multiple reagent providers. Brad’s current roles include optimizing new assay processes on BioTek’s line of automation, liquid handling, microplate detection, and imaging instrumentation. He has worked for more than 20 years with numerous automation and detection platforms, as well as a variety of cell models, to optimize 2D and 3D cell culture assays across multiple research fields. His current work has led to publications in Assay and Drug Development Technologies, The Journal of Laboratory Automation, The Journal of Biomolecular Screening, and Combinatorial Chemistry and High Throughput Screening, among others. Brad has additionally presented his work at numerous conferences across the United States, Europe, and Asia. 

    Mark Rothenberg, Ph.D.

    Manager Scientific Training and Education, Corning Incorporated, Life Sciences

    Dr. Rothenberg graduated from Emory University with his PhD in Cell and Developmental Biology. Over the past 25 years Mark has held positions in both Academia and industry where he has developed an expertise in the areas of assay development, cell culture and cell culture scale-up.  Prior to his current position as Manager Scientific Training and Education he worked and managed the applications team.

    SLAS Discovery

    June 2017 special issue on 3D Cell Culture, Screening and Optimization (Free online access to select articles in this issue is sponsored by Corning Life Sciences)

    • Three-Dimensional Cell Culture: A Rapidly Emerging Approach to Cellular Science and   Drug Discovery
      Three-Dimensional Cell Cultures in Drug Discovery and Development 
    • 3D Models of the NCI60 Cell Lines for Screening Oncology Compounds 
    • Isolation and Characterization of a Distinct Subpopulation from the WM115 Cell Line That Resembles In Vitro Properties of Melanoma Cancer Stem Cells 
    • A High-Throughput Screening Model of the Tumor Microenvironment for Ovarian Cancer Cell Growth 
    • Single and Combination Drug Screening with Aqueous Biphasic Tumor Spheroids 
    • A 1536-Well 3D Viability Assay to Assess the Cytotoxic Effect of Drugs on Spheroids 
    • RNAi High-Throughput Screening of Single- and Multi-Cell-Type Tumor Spheroids: A Comprehensive Analysis in Two and Three Dimensions 
    • Exploring Drug Dosing Regimens In Vitro Using Real-Time 3D Spheroid Tumor Growth Assays 
    • A Novel Multiparametric Drug-Scoring Method for High-Throughput Screening of 3D Multicellular Tumor Spheroids Using the Celigo Image Cytometer 
    • A Novel Cellular Spheroid-Based Autophagy Screen Applying Live Fluorescence Microscopy Identifies Nonactin as a Strong Inducer of Autophagosomal Turnover 
    • Screening of Intestinal Crypt Organoids: A Simple Readout for Complex Biology 
    • Bioengineered 3D Glial Cell Culture Systems and Applications for Neurodegeneration and Neuroinflammation 
    • An Optimized 3D Coculture Assay for Preclinical Testing of Pro- and Antiangiogenic Drugs 
    • An Automated Multiplexed Hepatotoxicity and CYP Induction Assay Using HepaRG Cells in 2D and 3D 
    • Study on a 3D Hydrogel-Based Culture Model for Characterizing Growth of Fibroblasts under Viral Infection and Drug Treatment 
    • Soft Hydrogels Featuring In-Depth Surface Density Gradients for the Simple Establishment of 3D Tissue Models for Screening Applications 
    • High-Throughput Clonogenic Analysis of 3D-Cultured Patient-Derived Cells with a Micropillar and Microwell Chip

    SLAS Technology

    SLAS Electronic Laboratory Neighborhood

    LabAutopedia

    SLAS ePoster Gallery

    SLAS Webinar

  • Modular, Fully-Integrated or Collaborative Automation?

    Contains 2 Component(s) Recorded On: 05/18/2017

    The establishment of the AstraZeneca-Medical Research Council UK Centre for Lead Discovery has led to revamping our screening infrastructure to embrace next generation HTS automation. This webinar will recap AZ’s experience: reviewing what works, what scientists like and most importantly what best conforms to the demands of the assay. The presenter will also present AZ’s vision for scalable, modular automation that can be efficiently deployed across customer demand. In conclusion the webinar will summarise the project learnings in the areas of collaborative robotics, remote operation and unforeseen benefits.

    The establishment of the AstraZeneca-Medical Research Council UK Centre for Lead Discovery has led to revamping our screening infrastructure to embrace next generation HTS automation.  This webinar will recap AZ’s experience: reviewing what works, what scientists like and most importantly what best conforms to the demands of the assay. The presenter will also present AZ’s vision for scalable, modular automation that can be efficiently deployed across customer demand. In conclusion the webinar will summarise the project learnings in the areas of collaborative robotics, remote operation and unforeseen benefits.

    Mark Wigglesworth

    Lead, AstraZeneca Global High Throughput Screening Centre

    Mark Wigglesworth now leads AstraZeneca’s Global High Throughput Screening Centre having previously work at GlaxoSmithKline on early stage drug discovery, target validation, sample management and screening. He is an active member of the European Laboratory Research and Innovation Group (ELRIG) including co-director responsibility for their Research and Innovation conference. Mark has contributed numerous publications in the field of GPCR pharmacology, hit identification and compound management including editing a book on Management of Biological and Chemical Samples for Screening Applications. Throughout his career he has maintained an active interest in technology and how automation can be utilised in a pharmaceutical environment.