Robert Abel, Ph.D., Schrödinger

Robert Abel, Ph.D. Robert Abel, Senior Vice President, Science, is responsible for leading efforts to further improve induced-fit docking, free energy perturbation theory, physics-based affinity scoring, and protein structure prediction; as well as supervising the Schrödinger R&D portfolio. Robert obtained his PhD from Columbia University for his work with Professor Richard Friesner on methods to quantify the role of the solvent in protein-ligand binding. He has also been awarded NSF and DHS research fellowships; published on a variety of topics including protein-ligand binding, protein dynamics, protein structure prediction, energy function development, and fluid thermodynamics; served as a referee for several prestigious journals; and co-authored multiple patent applications. Since joining Schrödinger in 2009, Robert has advanced through a number of roles to his current position.

Session

10:40 AM - 11:35 AM

R&D Use Cases

Drug Discovery is a long process that AI technologies and tools are beginning to help shorten.  The speakers in this two-part R&D Use Case session will present information on current projects where they are applying AI.  They will cover the inputs and outcomes, as well as share insights from applying AI  to their discovery projects

Moderator

Speakers

  • Ron Alfa, MD, Ph.D

    Ron Alfa, MD, Ph.D Senior Vice President, Translational Discovery Recursion Pharmaceuticals

  • Martin Akerman

    Martin Akerman Co-founder and CTO Envisagenics

    • Envisagenics’ platform, SpliceCore, uses AI to discover druggable splicing errors: Use cases in identifying and validating novel targets for triple-negative breast cancer.
  • Kate Hilyard, Ph.D.

    Kate Hilyard, Ph.D. Chief Operating Officer Healx

    The use of AI in accelerating new rare disease drugs towards the clinic
    This use case will discuss how AI enabled us to get from disease selection to clinical candidate selection for fragile X syndrome in 24 months.

    • How AI and ML predict viable treatment options

    • The importance of partnership and patient insight – FRAXA Research Foundation example

    • Preclinical proof of concept for fragile X syndrome

    • Progression to clinical trials

  • Rishi R. Gupta, Ph.D.

    Rishi R. Gupta, Ph.D. Principal Research Scientist, Data Science & Informatics AbbVie

    Boosting Drug Discovery with Machine Learning

    Applying recent advances made in Artificial Intelligence (AI) and Machine Learning (ML) methods to advance decision making in many industries has become an extremely important area of applied research. Progress in this regard will come from combining an understanding of the current and potential decision making processes specific to the industry of interest along with new and careful approaches to data capture that support training of the data using an appropriate method of choice. How machine learning tools can increase the efficiency and expediency of this decision by helping various research groups within a Pharmaceutical organization will be presented along with case studies highlighting the application of ML methods in discovery and pharmacovigilance.


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