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  • Clinical Biobanking: Patient Engagement in Drug Development: What Patients Have to Offer and What They Want You to Know

    Contains 1 Component(s)

    This webinar will explore iConquerMS and other Project programs in the context of biorepositories, patient data, and advocacy.

    Engaging patients in research and clinical trial design has grown since the mid-1980s, when doctors still debated the ethics of informing patients of lifelong diseases like multiple sclerosis (MS). The Accelerated Cure Project, a research-focused patient advocacy organization for MS, supports initiatives such as iConquerMS, a worldwide research network to connect patients and collect biosamples and phenotypic data. This webinar will explore iConquerMS and other Project programs in the context of biorepositories, patient data, and advocacy.

    Hollie Schmidt

    VP of Scientific Operations, Accelerated Cure Project

    Ms. Schmidt is the VP of Scientific Operations at the Accelerated Cure Project, a research-focused patient advocacy organization for MS. She has planned, developed, and directed numerous initiatives aimed at creating research resources and bridging different stakeholder communities. These initiatives include iConquerMS, a PCORI-funded patient-powered research network for MS; the MS Minority Research Engagement Partnership Network; the ACP Biorepository; and the ACP Clinical Research Network.

  • Building Better iPSC Models of Human Disease and Development

    Contains 1 Component(s)

    Since their initial generation in 2007 human induced pluripotent stem cells (hiPSC) have been used to model human development and disease progression, for drug screening and for toxicology testing. It is now possible to reprogram a wide range of cell types allowing a greater diversity of hiPSC to be generated and increasing the availability of hiPSC containing either specific mutations or from subjects with diseases that do not have known genotype.

    Since their initial generation in 2007 human induced pluripotent stem cells (hiPSC) have been used to model human development and disease progression, for drug screening and for toxicology testing.    It is now possible to reprogram a wide range of cell types allowing a greater diversity of hiPSC to be generated and increasing the availability of hiPSC containing either specific mutations or from subjects with diseases that do not have known genotype.  However, the diverse genetic background of the human race has hampered the usefulness of iPSC.  Currently, controls often consist of age and sex-matched non-affected subjects or non-affected family members.  The use of the CRISPR (clustered regularly-interspaced short palindromic repeats)/Cas system can create isogenic cell lines that will serve as better controls and help eliminate effects that are due to genetic variance rather than a biological mechanism.  At RUCDR/Infinite Biologics we have developed a high throughput, cost efficient workflow for generating hiPSC from many different types of source cells and using CRISPR/Cas9 to genetically these cell lines, creating isogenic lines.  Using this strategy, we have generated pairs of iPSC lines that are footprint free, meet all of the criteria necessary to certify the cell lines as pluripotent and use to better understand mechanisms of human disease and development. 

    Dr. Jennifer Moore

    Director of Stem Cell Services and Technologies, RUCDR Infinite Biologics at Rutgers

    Dr. Moore received her Ph.D. from the University of North Carolina at Chapel Hill in Biochemistry and Biophysics and has 16 years of experience in pluripotent stem cell biology, first in human embryonic stem cells and then in induced pluripotent stem cells. At RUCDR, Dr. Moore oversees the generation, expansion, banking, QC and editing of iPSC from both external investigators and iPSC produced by RUCDR. 

  • Mitigation and identification of aggregation and nonspecific reactivity interference in high-throughput screening

    Contains 2 Component(s) Recorded On: 06/07/2018

    Compound-mediated assay interference and bioassay promiscuity are significant burdens in drug and chemical probe discovery. Pursuing artifacts or poorly tractable, nonselective chemical matter from real and virtual high-throughput screening (HTS) can waste significant scientific resources and can lead to tenuous scientific conclusions when used in subsequent studies.

    Compound-mediated assay interference and bioassay promiscuity are significant burdens in drug and chemical probe discovery. Pursuing artifacts or poorly tractable, nonselective chemical matter from real and virtual high-throughput screening (HTS) can waste significant scientific resources and can lead to tenuous scientific conclusions when used in subsequent studies. Two of the more prominent sources of generalized assay interference in biological assays by test compounds are aggregation and nonspecific reactivity. Aggregators and reactive compounds can interfere across multiple assay technologies and formats including biochemical and cellular systems, often leading to poorly tractable, promiscuous bioactivity. Apparent bioactivity from such interference compounds can be highly deceptive and quite convincing, even to experienced scientists. These subversive sources of apparent bioactivity represent significant project risks that can fortunately be mitigated with appropriate experimental design. This webinar will first discuss the fundamental chemical principles of these interferences, then introduce (1) technical recommendations to mitigate the incidence of aggregation and nonspecific reactivity in biological assays, and (2) basic and advanced counter-screens to identify as well as de-risk apparent bioactive compounds for aggregation and nonspecific reactivity. This information should be helpful for those performing HTS and triage, drug and chemical probe development, and chemical biology.

    Jayme L. Dahlin, M.D., Ph.D.

    Department of Pathology, Brigham and Women’s Hospital

    Dr. Dahlin joined the Mayo Clinic (Rochester, MN) Medical Scientist Training Program in 2007 after earning his B.A. in chemistry from Carleton College (Northfield, MN). In 2016, he graduated with an M.D. from Mayo Medical School and a Ph.D. in Molecular Pharmacology and Experimental Therapeutics from Mayo Graduate School. He is currently Chief Resident in Clinical Pathology at Brigham and Women’s Hospital (Boston, MA) and a postdoctoral research fellow in the laboratory of Dr. Stuart L. Schreiber at the Broad Institute of Harvard/Massachusetts Institute of Technology. His graduate and postdoctoral work have focused on chemical mechanisms of biological assay interference and post-HTS triage. His research interests include HTS and triage tool development, bioassay promiscuity, and compound-mediated assay interference. Dr. Dahlin serves on the editorial board for the NIH Assay Guidance Manual and the Scientific Advisory Board of the Chemical Probes Portal.

  • Using AI and IoT to Accelerate Research

    Contains 2 Component(s) Recorded On: 05/08/2018

    In this webinar, we will explore how new technologies can be used to accelerate scientific research. Join us for an in-depth look at how we can also overcome challenges by practically incorporating new tech into research processes to uncover and decipher hidden confounding variables.

    In recent years we’ve seen an explosion of technologies surrounding seemingly “new” fields of artificial intelligence / machine learning (AI/ML), the Internet of Things (IOT), and the like. Whilst many of the underlying technologies have existed for decades, only recently has compute power become affordable and powerful enough to apply them to new fields. In this webinar, we will explore how these new technologies can be used to accelerate scientific research. Many of the AI tools currently being used are focused on data mining; whilst this is a necessary part of the process, it is important to note that any AI system is only as good as the data that’s fed into it. This is where the integration of sensors and IOT can make a meaningful impact – by intelligently incorporating protocol design and real-time sensing of physical parameters with machine learning, we can dramatically improve research outcomes by increasing the reproducibility of experiments. How many times have you run an experiment and not been able to reproduce the results – only to find out (after months of searching) that the root cause was something trivial like improper storage of reagents, or mis-calibrated instruments, or environmental variations in the lab? Join us for an in-depth look at how we can overcome these challenges by practically incorporating new tech into research processes to uncover and decipher these hidden confounding variables.

    Sridhar Iyengar, PhD

    CEO & Founder, Elemental Machines

    A serial entrepreneur in sensors, IoT, medical devices, and wearables, Sridhar is founded Elemental Machines with the mission to build products to help science-based companies decipher and understand physical processes from R&D to manufacturing. Previously, Sridhar was a founder of Misfit, makers of elegant wearable products, which was acquired by Fossil in 2015. Prior to Misfit, he founded AgaMatrix, a blood glucose monitoring company that made the world’s first medical device connecting directly to the iPhone. AgaMatrix shipped 15+ FDA-cleared medical products, 2B+ biosensors, 6M+ glucose meters, with partnerships with Apple, Sanofi, and Walgreens. Sridhar holds over 50 US and international patents and received his Ph.D. from Cambridge University as a Marshall Scholar. Beyond Elemental Machines, Sridhar has been known to run 13.1 miles on occasion and has sometimes been spotted on stage behind a wall of drums.

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

    Contains 1 Component(s) Recorded On: 02/07/2018

    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. 

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

    Contains 1 Component(s) Recorded On: 02/07/2018

    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

  • Tumor Organoids for Therapeutic Discovery and Personalized Medicine

    Contains 1 Component(s) Recorded On: 02/07/2018

    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.

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

    Contains 1 Component(s) Recorded On: 02/07/2018

    ​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.

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

    Contains 1 Component(s) Recorded On: 02/07/2018

    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.

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

    Contains 1 Component(s) Recorded On: 02/07/2018

    ​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.