Catalog Advanced Search

Search by Categories
Search by Format
Search by Type
Search by Date Range
Products are filtered by different dates, depending on the combination of live and on-demand components that they contain, and on whether any live components are over or not.
Start
End
Search by Keyword
Sort By
  • Development of a Fully Automated Ultra-High Throughput Flow Cytometry Screening System to Enable Novel Drug Discovery

    Contains 1 Component(s) Recorded On: 09/23/2014

    We will describe an industry first automated screening system dedicated to processing and reading suspension cells using flow cytometry. The custom samplers are fully integrated into a GNF Systems ultra-high throughput screening system and feed three Beckman Coulter CyAn cytometers. Our current system can read a 384 well plate in 15 min and a 1536 well plate in less than an hour. This allows for a throughput of approximately 40,000 wells per day with less than one full time employee overseeing the system. Also presented will be an overview of informatics tools used to process the large amount of data in real-time and in a fully automated workflow. As a result of this effort, we are running high throughput flow cytometry phenotypic screens across multiple disease areas to enable novel drug discovery at Novartis.

    The ability to run high content phenotypic screens provides many advantages in drug discovery. Phenotypic screens can be run without prior understanding of the target and with primary cells that closely mimic the therapeutic setting. An additional advantage is that phenotypic screens often enable multiple parameters that can be read from a single experiment. The disadvantage of running high content phenotypic screens is that these assays tend to be slow, expensive, and limited by the throughput of readers available for high throughput screening. The use of automation and miniaturization into 1536 well plates can both increase the throughput and decrease the cost significantly. However, the industry is still plagued by relatively low throughput high content readers.

    While high content is often synonymous with imaging, here we demonstrate the capabilities of using flow cytometry in a true high throughput manner. We have developed a fully automated flow cytometry sampling workflow that is compatible with 1536 or 384 well plates. Progressive high-content screening systems have been demonstrated to process up to 50,000 wells/day on a routine basis with screening campaigns into the millions of wells, but this has been limited to adherent cells.

    We will describe an industry first automated screening system dedicated to processing and reading suspension cells using flow cytometry. The custom samplers are fully integrated into a GNF Systems ultra-high throughput screening system and feed three Beckman Coulter CyAn cytometers. Our current system can read a 384 well plate in 15 min and a 1536 well plate in less than an hour. This allows for a throughput of approximately 40,000 wells per day with less than one full time employee overseeing the system. Also presented will be an overview of informatics tools used to process the large amount of data in real-time and in a fully automated workflow. As a result of this effort, we are running high throughput flow cytometry phenotypic screens across multiple disease areas to enable novel drug discovery at Novartis.

    John Joslin

    Research Investigator

    John Joslin is a research investigator at the Genomics Institute of the Novartis Research Foundation where he leads a group of scientists in early target validation, technology development, and assay miniaturization for high throughput screening.

  • Cellular Protein: Protein Interaction Assays Implemented using BacMam

    Contains 1 Component(s) Recorded On: 05/13/2014

    This seminar will provide an overview of cellular protein: protein interaction methods and the strengths and weaknesses of various assay classes. We have focused on Bioluminescence Resonance Energy Transfer (BRET) assays for detecting and interfering with cellular PPI's and have implemented assays for BH3 family members using BacMam vectors. BacMam vectors afforded an anticipated ease of switching the interacting partners or mutant versions of the partners. In addition, by varying the multiplicity of infection, these vectors provided the ability to increase the sensitivity of the assay by minimally over-expressing the proteins of interest. We will provide examples of the use of this assay and BacMam vectors to measure PPI's using published inhibitors of the interaction of BCL2 and Bad and methods developed for using these vectors for high throughput screening.

    This seminar will provide an overview of cellular protein: protein interaction methods and the strengths and weaknesses of various assay classes. We have focused on Bioluminescence Resonance Energy Transfer (BRET) assays for detecting and interfering with cellular PPI's and have implemented assays for BH3 family members using BacMam vectors. BacMam vectors afforded an anticipated ease of switching the interacting partners or mutant versions of the partners. In addition, by varying the multiplicity of infection, these vectors provided the ability to increase the sensitivity of the assay by minimally over-expressing the proteins of interest. We will provide examples of the use of this assay and BacMam vectors to measure PPI's using published inhibitors of the interaction of BCL2 and Bad and methods developed for using these vectors for high throughput screening.

    Mary Ellen Digan

    Senior Research Investigator I

    Dr. Digan has worked in the biotechnology, agricultural biotechnology and pharmaceutical industries. She presently is responsible for generating and testing reagents and cell lines for new assay formats for medium and high throughput screening.

  • Targeting Protein-Protein Interactions as an Anticancer Strategy

    Contains 1 Component(s) Recorded On: 04/15/2014

    The emergence and convergence of cancer genomics, targeted therapies, and network oncology have significantly expanded the landscape of protein-protein interaction (PPI) networks in cancer for therapeutic discovery. In this webinar, I will provide an overview of the current status of PPI interrogation in cancer and highlight some widely employed high throughput screening technologies for monitoring PPIs. A case study will be presented to illustrate the process from PPI target characterization, validation, and assay development to tool compound discovery.

    The emergence and convergence of cancer genomics, targeted therapies, and network oncology have significantly expanded the landscape of protein-protein interaction (PPI) networks in cancer for therapeutic discovery. In this webinar, I will provide an overview of the current status of PPI interrogation in cancer and highlight some widely employed high throughput screening technologies for monitoring PPIs. A case study will be presented to illustrate the process from PPI target characterization, validation, and assay development to tool compound discovery.

    Haian Fu

    Professor

    Dr. Fu is Professor of Pharmacology, Hematology & Medical Oncology at Emory University, and Director of Emory Chemical Biology Discovery Center. He received Ph.D. from University of Wisconsin-Madison and postdoctoral training at Harvard Medical School.

  • Challenging Targets for Drug Discovery

    Contains 1 Component(s) Recorded On: 03/18/2014

    Many targets of biomedical interest do not have useful small molecule starting points. This is especially true for proteins that engage in protein-protein interactions or that may be regulated by allosteric interactions. For these sites, plasticity and conformational adaptability of proteins has begun to reveal new opportunities for drug discovery on targets previously assumed to be "undruggable".

    Many targets of biomedical interest do not have useful small molecule starting points. This is especially true for proteins that engage in protein-protein interactions or that may be regulated by allosteric interactions. For these sites, plasticity and conformational adaptability of proteins has begun to reveal new opportunities for drug discovery on targets previously assumed to be "undruggable".

    The presentation will review a site-directed fragment-based discovery approach, disulfide-trapping, that is well-suited to probing these challenging surfaces. Although protein-protein interfaces are generally flat and large, small fragment molecules can be found that bind with much greater ligand efficiency to "hot-spots" and in crevices that protein partners do not exploit.

    Second, the site-directed nature of disulfide-trapping makes it very useful for exploring allosteric sites that may not be found by typical screening approaches. The presentation will include examples of finding both inhibitory and activating allosteric sites, even from the same site in PDK-1, an important protein kinase.

    Lastly, the presentation will cover some other compounds discovered by HTS that activate caspases using a very novel mechanism. These technologies and the intrinsic adaptability and flexibility of proteins dramatically expand the opportunities for drug discovery at protein-protein interfaces and allosteric sites.

    James A. Wells

    Chair and Professor

    James A. Wells is a leader in therapeutic sciences and technology development for protein engineering and small molecule drug discovery. He is a professor and chair of the Department of Pharmaceutical Chemistry at UCSF.

  • Modern Phenotypic Drug Discovery is a Viable Pharma Strategy

    Contains 1 Component(s) Recorded On: 12/05/2013

    The majority of current drug discovery strategies are directed towards specific, molecular targets. However, analysis of FDA approved drugs indicates that the majority of first in class new molecular entities (NMEs) originated from phenotypic and not target-directed screening. Phenotypic drug discovery (PDD) approaches are not commonly used by Pharma due to concerns about assay performance, difficulties with compound structure-activity relationships (SAR), uncertain applicability of chemo-informatics, and the difficulty/requirement for elucidating a molecular target.

    The majority of current drug discovery strategies are directed towards specific, molecular targets. However, analysis of FDA approved drugs indicates that the majority of first in class new molecular entities (NMEs) originated from phenotypic and not target-directed screening. Phenotypic drug discovery (PDD) approaches are not commonly used by Pharma due to concerns about assay performance, difficulties with compound structure-activity relationships (SAR), uncertain applicability of chemo-informatics, and the difficulty/requirement for elucidating a molecular target. We address these perceived issues with PDD by conducting a medium through-put screen using a co-culture angiogenesis assay. Results indicate that modern phenotypic assays can reliably provide information on compound SAR. Identification of compounds which modulate targets not previously associated with angiogenesis demonstrates that PDD directly interrogates relevant biology without preconceptions of target validation state. These attributes of PDD enabled the identification of compounds which are structurally and mechanistically distinct from current standard of care (SOC) and are active in vivo.

    The potential synergism between novel chemical diversity and the target agnostic PDD approach was investigated by comparing the phenotypic assay profiles of compounds derived from Pharma verses structurally distinct molecules from academia/biotech. Taken together our results indicate that modern PDD combines advantages of pharmacology based drug discovery with the high through-put compound testing capacity and operational robustness of targeted approaches. Novel chemical diversity coupled with phenotypic lead generation strategies will facilitate the identification of novel therapeutic mechanisms and the validation of new molecular targets.

    Jonathan Lee

    Senior Research Advisor

    Jonathan has worked in the pharmaceutical industry since 1989. He is currently a Senior Research Advisor at Eli Lilly involved in assay technologies, cellular imaging and phenotypic drug discovery.

  • Phenotypic Drug Discovery Using Primary Human Cells and Co-Cultures: Lessons Learned

    Contains 1 Component(s) Recorded On: 11/12/2013

    We have spent over a decade developing an extensive panel of primary human cell based assays and co-culture models, BioMAP® systems, for use in phenotypic screening. These systems, applied together with our large drug activity database, have been used by industrial, academic and government collaborators for drug discovery, compound characterization and mechanism of action studies. Here we will describe the features and performance of these assays and summarize lessons learned for phenotypic drug discovery applications. We will also describe how data generated from this platform has been used to build predictive models for mechanism classes using a support vector machine approach.

    We have spent over a decade developing an extensive panel of primary human cell based assays and co-culture models, BioMAP® systems, for use in phenotypic screening. These systems, applied together with our large drug activity database, have been used by industrial, academic and government collaborators for drug discovery, compound characterization and mechanism of action studies. Here we will describe the features and performance of these assays and summarize lessons learned for phenotypic drug discovery applications. We will also describe how data generated from this platform has been used to build predictive models for mechanism classes using a support vector machine approach.

    Ellen Berg

    Scientific Director

    Dr. Berg is Scientific Director at BioSeek, a division of DiscoveRx, where she leads the scientific team developing the company's BioMAP® platform of primary human cell based assays and predictive analysis tools.

  • The Value of Phenotypic-Based Drug Discovery

    Contains 1 Component(s) Recorded On: 09/26/2013

    Drug discovery strategies include target-based molecular approaches and phenotypic-based empirical approaches. Our recent analysis revealed the phenotypic approach as the more successful strategy for first-in-class medicines. We rationalized that this success was influenced by the unbiased identification of a molecular mechanism of action (MMOA) that contributed to a useful therapeutic index. The value and success of phenotypic approaches will be further increased through efforts to bridge the gap between molecular and phenotypic approaches. In this webinar I will discuss challenges and solutions to assimilating molecular and phenotypic approaches to increase drug discovery success.

    Drug discovery strategies include target-based molecular approaches and phenotypic-based empirical approaches. Our recent analysis revealed the phenotypic approach as the more successful strategy for first-in-class medicines. We rationalized that this success was influenced by the unbiased identification of a molecular mechanism of action (MMOA) that contributed to a useful therapeutic index. The value and success of phenotypic approaches will be further increased through efforts to bridge the gap between molecular and phenotypic approaches. In this webinar I will discuss challenges and solutions to assimilating molecular and phenotypic approaches to increase drug discovery success.

    David C. Swinney

    Ph.D.

    David Swinney, with over 25 years preclinical drug discovery experience, is currently at the Institute for Rare and Neglected Diseases Drug Discovery working to identify new drug discovery starting points to address unmet medical needs.

  • Effectively Managing Collaborative Science: 3 Modules

    Contains 3 Component(s) Recorded On: 05/15/2013

    3 Modules

    Module 1: R&D Partnership in Asia and Emerging Markets

    Module 2: Lessons Learned in Pharma: CRO Collaboration in Discovery Research

    Module 3: Challenges and Strategies for Successful Transfer of Cell-Based Potency Assays

    Ajay Gautam

    Executive Director, Head of Emerging Markets

    Dr. Ajay Gautam is Executive Director and Head of Emerging Markets Collaborations for AstraZeneca based in Shanghai, China. In this role, he leads the development and implementation of AstraZeneca R&D's strategy and collaborations in the Emerging Markets.



    Prior to joining AstraZeneca, Ajay was the Co-founder and Managing Director of Bio-nAbler, a healthcare investment firm focused on India, the Middle East and North Africa region. Together with his co-founder, he conceptualised the firm, raised equity capital, and led transactions and advisory projects across countries such as India, Egypt, Algeria, Saudi, Jordan, and UAE.



    Previously, Ajay was Vice President, Corporate and Business Development at moksha8, a TPG backed Latin America-focused specialty pharma company, where he spent time in Latin America leading deals with Pfizer and Roche in Brazil and Mexico, and was part of management team that raised significant equity capital from US and Latin America investors.



    Prior to moksha8, Ajay was with the worldwide business development group at Pfizer Inc., based in New York, working on various business development initiatives across commercial, manufacturing and R&D. He also managed the company's R&D equity investment portfolio.



    Ajay holds a PhD in Biomedical Sciences and an MBA in Finance from the US and a Bachelor of Technology in Biotechnology and Biochemical Engineering from India.

    Jonathan H Connick

    Executive Director and Chair in vitro

    Dr Jonathan Connick is executive director and chair of the in vitro pharmacology council at Merck where he is responsible for developing the external in vitro biology strategy. Dr Connick recently relocated to Shanghai from New Jersey and previously headed Molecular Pharmacology at Organon in the UK.

    Liming Shi

    Senior Research Scientist

    Liming has been working in biotech industry for more than 15 years. He specializes in biological assays development, transfer and validation. With thorough statistical expertise, intensive GMP experience and bioanalytical knowledge, he has successfully managed numerous bioanalytical projects to support studies in different phases. He has also deeply involved in PK, immunogenicity and CMC activities to support IND and BLA filings.

    Asia and Emerging Markets present growth opportunities and potential sources of innovation and resource for the pharmaceutical industry. Identifying, establishing, and managing R&D partnership in Asia and Emerging markets offer unique opportunities and challenges. This presentation focus on examples of R&D partnerships between major pharmaceutical companies with local academia, biotech, and CRO companies in Asia and Emerging Markets. The presenter will try to share his perspectives on effective approaches towards productive R&D partnerships in Asia and Emerging Markets.

    Working in collaboration with Contract Research Organizations has become an essential component of the modern pharma industry. Establishing intensive, long-term collaborations can provide much needed flexibility and provides access to skills, expertise and talent which can be complementary to internal labs. Many challenges exist to realizing such effective partnerships. Effective logistics and communication as well as concerns around compliance, intellectual property and quality can present a considerable barrier to success. This presentation will provide examples of lessons learned in developing successful partnerships involving in vitro pharmacology. The importance of developing a strategic approach, effective risk management and governance as well as building trust and respect between scientists are pivotal to success. Whilst there may be differences in emphasis between small biotech and large pharma, these same characteristics apply in increasing the probability of success to the mutual benefit of both sides of the partnership.

    The most common practice in technology transfer to third parties is analytical methods. Due to its unique complexity and variability by biological systems, cell-based potency assays are considered to be one of the most challenging parts during technology transfer. Selection of appropriate CRO, application of effective transfer strategy, design appropriate experiments with pre-determined acceptance criteria, close monitoring and timely communication, consideration of IP issues and supply chain, meeting regulatory requirements and utilization of statistical tools are critical for successful transfer of cell-based potency assays.
  • Extracting Meaning From Your Data: 3 Modules

    Contains 3 Component(s) Recorded On: 12/11/2012

    3 Modules

    Module 1: Data Management, Analysis and Visualization Tools for Understanding Multidimensional Screening Results

    Module 2: TripleMap: Next Generation Semantic Search and Analytics for Life Sciences

    Module 3: Application of Design of Experiments (DOE) in Protein Purification, Assay Development and Ligand Interaction Studies

    Donald G. Jackson

    Sr. Research Investigator II

    Donald G. Jackson, PhD
    Sr. Research Investigator II,
    Applied Genomics Department,
    Bristol-Myers Squibb Research & Development

    Dr. Jackson has used high-content screening (HCS) extensively to support target discovery, target validation, compound mechanism-of-action studies, and toxicology projects at BMS. He also led the development of HCS Road, an innovative management and analysis solution for HCS data. Previously he was a member of the bioinformatics group at BMS where he helped identify novel oncology targets using model organism genetic screens. He received his doctorate in Biochemistry, Cellular and Molecular Biology from The Johns Hopkins University and was a post-doctoral felow at the Massachusetts General Hospital where he worked on bioinformatics for the Zebrafish Genome Project.

    Dr. Bouton

    CEO

    Dr. Bouton received his BA in Neuroscience (Magna Cum Laude) from Amherst College in 1996 and his Ph.D in Molecular Neurobiology from Johns Hopkins University in 2001. Between 2001 and 2004 Dr. Bouton worked as a computational biologist at LION Bioscience Research Inc. and Aveo Pharmaceuticals, leading the microarray data analysis functions at both companies. In 2004 he accepted the position of Head of Integrative Data Mining for Pfizer and led a group of Ph.D. level scientists conducting research in the areas of computational biology, systems biology, knowledge engineering, software development, machine learning and large-scale 'omics data analysis. While at Pfizer, Dr. Bouton conceived of and implemented an organization-wide wiki called Pfizerpedia for which he won the prestigious 2007 William E. Upjohn Award in Innovation. In 2008 Dr. Bouton assumed the position of CEO at Entagen (http://www.entagen.com), a biotechnology company that provides computational research, analysis and custom software development services for biomedical organizations. Dr. Bouton is an author on over a dozen scientific papers and book chapters and his work has been covered in a number of industry news articles.

    Paul Taylor

    Lead

    Paul Taylor, Boehringer Ingelheim Pharmaceuticals, Inc.

    Paul's focus in drug discovery has been on facilitating new ways to automate and miniaturize assays for HTS, specifying and building robotic systems, applying continuous process improvements in compound management and finding novelty at the interface of specialized disciplines.

    New technologies and approaches in drug discovery require new approaches to data management and analysis. High-content screening (HCS) generates much richer data than conventional biochemical assays with multiple measurements and endpoints at the whole-well and single-cell level. This multidimensional data requires different tools, such as those commonly used for microarray gene expression and flow cytometry analyses. New approaches to drug discovery such as RNA interference and phenotypic or 'black-box' screening also require different approaches to hit selection and data visualization from conventional high-throughput screening. This talk will describe novel data management and analysis tools that adress these needs using a combination of internally developed solutions, commercial and open source software. These tools enable researchers to analyze new types of experiments and to extract new information from existing data sets.

    TripleMap is an enterprise knowledge discovery & collaboration platform which can be securely deployed within an organization's firewall or hosted in the cloud. TripleMap allows users such as biologists, chemists, patent attorneys, market analysts, and clinical trial specialists to search through and analyze the entities and associations between entities in the secure, massive interconnected GEM Semantic Data Core which is continuously aggregated from internal and external sources. TripleMap represents everything in its semantic data core as "master entities" that integrate all information for any given entity (e.g. protein, gene, compound, clinical trial, disease) including names, synonyms, symbols, meta-data properties, and associations to other entities. By searching for, and saving sets of entities, users build, share and, analyze "dynamic knowledge maps" of entities and their associations. These knowledge maps give users a "bird's eye view" of patterns of interconnection between entities of interest, are used to continuously scan for novel information as it becomes available and allow users to find other users creating similar maps, thereby enabling collaborative knowledge exchange.

    Pharmaceutical researchers today face the challenge of developing pre-clinical methodologies with the highest probability of identifying candidates for testing in the clinic. Automation and miniaturization have enabled high-throughput screening (HTS) labs to screen hundreds of thousands of compounds against a biological target in a short space of time, and, accordingly, a need has arisen to reduce the costs and time frames associated with protein supply and development of robust, physiologically relevant assays. For protein purification, conditions were sought which would improve the effectiveness of achieving maximum purity and yield. For assay development, conditions were optimized for miniaturized formats, stability, signal-separation, and variability - objective functions associated with transfer onto automated platforms.

    The application of Design of Experiments (DOE) and robotics to protein purification and assay optimization allowed elucidation of conditions which were often a composite of variables which could not have been arrived at by examining each individually. The availability of robotics capable of performing rapid random access tasks has made it possible to design optimization experiments which would be either very difficult or impossible to carry out manually. Standard designs now incorporate up to seven factors with five logarithmically-spaced levels. In this fashion, experiments are designed so that response surfaces can be easily viewed as a representation of biological data which is frequently non-linear.

    More recently, robotic capability has been extended to allow optimization in 1,536-well format and has also expanded to 3-way ligand mixture studies as a tool for pathway interrogation. Over time, a practical tool has emerged from the combination of biological expertise, high throughput robotics and integrated statistical design. Examples will be described where following each experiment, improved conditions or scientific insights were rapidly achieved.

    Acknowledgements in presentation:

    Laura Amodeo, Debra Brennan, Mohammed Kashem, Jim King, Zofia Paw, Gregory Peet, George Rogers, Cynthia Sledziona, Joshuaine Toth, John Wan and Zane Wenzel.

  • Interrogating Chemical Space - Rules, Filters, Fragment-Based Screening and Beyond: 4 Modules

    Contains 4 Component(s) Recorded On: 11/15/2011

    4 Modules

    Module 1: Rules and Filters and their Impact on Success in Chemical Biology and Drug Discovery

    Module 2: From Molecular Complexity to Molecular Obesity: Lessons from Hindsight

    Module 3: Practical Approaches to Fragment-Based Lead Discovery

    Module 4: Combining NMR and X-Ray Crystallography in Fragment-Based Drug Discovery: From NMR-Detected Fragment Hits to clinical Candidate for BACE-1

    Chris Lipinski

    Scientific Advisor


    Dr. Christopher Lipinski learned his medicinal chemistry skills in a 32 year career at Pfizer in Groton, CT where he retired at the most senior scientific position. He is currently a Scientific Advisor to Melior Discovery a drug repurposing startup located in Exton, PA and carries out his medicinal chemistry consulting through Christopher A. Lipinski, Ph.D., LLC located in Waterford CT. Chris serves on the scientific advisory boards for academic drug discovery efforts in Leuven, Belgium, Dundee Scotland and London UK. He is a conference committee member for the annual MIPTEC meeting in Basel Switzerland which is now the largest early drug discovery meeting in Europe. He is a member of the American Chemical Society (ACS), the American Association of Pharmaceutical Sciences (AAPS) and the Society for Laboratory Automation Screening (SLAS). He is the author of the "rule of five" a widely used filter to select for acceptable drug oral absorption which is now the most highly cited paper in medicinal chemistry drug discovery.

    Career history:
    1968 PhD Physical Organic Chemistry - University of California, Berkeley
    1969-1970 - NIH NIGMS Postdoctoral Trainee California Institute of Technology
    1970-2002 - Research Scientist to Senior Research Fellow, Pfizer, Groton, CT USA
    2002 - present - Independent medicinal chemistry consultant - Scientific Advisor, Melior Discovery (a drug repurposing biotech) & Adjunct Professor Biochemistry, University of Massachusetts, Amherst

    Special interests: Medicinal chemistry, Drug Discovery, Bioisosteres and the relationship of in-vitro to in-vivo drug activity, physicochemical properties and biological activity

    Mike Hann

    Director

    Mike Hann, Ph.D., GlaxoSmithKline Medicines Research Centre

    Career History:
    1980 PhD Synthetic Organic Chemistry - City University; Isosteric replacement studies in Enkephalins.
    1980-1981 - Medicinal Chemist, Wyeth UK
    1981-1986 - Medicinal Chemist and Computational Chemist, GD Searle, UK
    1986 - present - GlaxoSmithKline, UK - Current position: Director of Bio-Molecular Structure, previously Director of Computational Chemistry

    Special interests: Computational chemistry, Structural Biology, Lead generation and optimisation, Fragment screening, Medicinal chemistry.

    Daniel A. Erlanson

    Researcher

    Daniel A. Erlanson, Ph.D., Carmot Therapeutics, Inc.

    Dr. Daniel Erlanson has practiced fragment-based drug discovery since 1998, previously developing Tethering at Sunesis Pharmaceuticals and currently Chemotype Evolution at Carmot Therapeutics, which he co-founded. He earned his PhD in chemistry from Harvard University.

    Daniel F. Wyss

    BioNMR Lead

    Daniel F. Wyss, Ph.D., BioNMR Lead, Merck Research Laboratories

    Dr. Wyss joined Schering-Plough (now Merck) as a Section Leader in 1997. His team has implemented fragment-based approaches to assist lead discovery on a global level in the organization. He holds a PhD in Chemistry (Univ Basel, Switzerland) and carried out post-doctoral studies in structural biology at Harvard Medical School (Prof Gerhard Wagner).

    There are both similarities and differences in the biology world of drug targets and the chemistry world of the drugs that bind to the targets. Summarizing first some of the differences. The physicochemical properties consistent with useful drugs are of low dimensionality in that their properties can be described by a small number of independent variables. This is why the quite simple rule of five works. By contrast biological activity at a target is of high dimensionality. Something as simple as the rule of five would never work to describe a biological SAR. The biology world is incredibly complex and to be really certain about activity one has to run an experimental assay. The chemistry world is far simpler with rules and principles and decades of lore relating chemistry structure to chemical reactivity. Thus it is possible to classify which types of chemical functionality are more likely to lead to promiscuity in chemical biology or drug discovery assays. The similarities in the biology and chemistry worlds can be quite surprising. In both biology and chemistry the targets and their ligands occupy respectively an infinitesimally tiny portion of the possibly available target or chemistry space. Evolution prunes down the choices on the target side

    There are both similarities and differences in the biology world of drug targets and the chemistry world of the drugs that bind to the targets. Summarizing first some of the differences. The physicochemical properties consistent with useful drugs are of low dimensionality in that their properties can be described by a small number of independent variables. This is why the quite simple rule of five works. By contrast biological activity at a target is of high dimensionality. Something as simple as the rule of five would never work to describe a biological SAR.

    The biology world is incredibly complex and to be really certain about activity one has to run an experimental assay. The chemistry world is far simpler with rules and principles and decades of lore relating chemistry structure to chemical reactivity. Thus it is possible to classify which types of chemical functionality are more likely to lead to promiscuity in chemical biology or drug discovery assays. The similarities in the biology and chemistry worlds can be quite surprising. In both biology and chemistry the targets and their ligands occupy respectively an infinitesimally tiny portion of the possibly available target or chemistry space. Evolution prunes down the choices on the target side

    Since their introduction in the mid-1990s, fragment-based approaches have become increasingly successful in finding drug leads. More than a dozen drugs that have entered clinical development started as fragments, and in August this year vemurafenib became the first such drug approved. However, successful fragment-based lead discovery requires both different techniques and a different mindset than traditional approaches. This module will cover the basic ideas behind fragment discovery, outline the major tools used to discover fragments, and highlight case studies in the optimization of fragments to drug leads.

    After a brief introduction to the concepts, several of the pitfalls and challenges to finding fragments will be described. Next, the major techniques employed to identify fragments will be presented, followed by a discussion of how to evaluate fragments that are found through these methods. This discussion will cover common metrics used to prioritize fragment hits as well as general principles for deciding which fragments are most suitable for further advancement. Finally, examples of how fragments have been successfully advanced will be used to illuminate guidelines from earlier sections.

    Fragment-based drug discovery has become increasingly popular over the last decade. We will discuss how structure-driven fragment-based approaches have been used in the organization to complement more traditional lead discovery to tackle early & high priority targets, and those struggling for leads. Combining biomolecular NMR, X-ray crystallography, and computer modelling with structure-assisted chemistry & innovative biology as an integrated approach for FBDD can solve very difficult problems as illustrated in our work.

    A successful FBDD campaign will be described which allowed the development of a clinical candidate for BACE-1, a challenging CNS drug target. Critical to this achievement were the initial identification of a ligand-efficient isothiourea fragment through target-detected NMR screening & analoging, and the determination of its X-ray crystal structure in complex with BACE-1, which revealed an extensive H-bond network with the two active site aspartates. This detailed 3D structural information then enabled the design and validation of novel, chemically stable and accessible heterocyclic acylguanidines as aspartic acid protease inhibitor cores. Structure-assisted fragment hit to lead optimization yielded iminoheterocyclic BACE-1 inhibitors that possess desirable molecular properties as potential therapeutic agents to test the amyloid hypothesis in a clinical setting.