Rishi R. Gupta, Ph.D., AbbVie

Rishi R. Gupta, Ph.D. Rishi R. Gupta is currently a Principal Research Scientist at Abbvie, Inc. at Lake County, Chicago. He leads the Cheminformatics and Competitive Intelligence groups. At AbbVie, he has developed a web based infrastructure to expose suite of Cheminformatics tools called AIDEAS. He has developed and deployed machine learning models for a variety of bioassay data including ADMET endpoints. In his extended role within Competitive Intelligence (CI), Rishi is developing web based visual-analytic frameworks for exposing genomics data, clinical Trials data and a variety of other CI related landscapes e.g. KOLs. Prior to AbbVie, Rishi was at Pfizer Global Research and Development as a Computational Chemist where he had broad set of responsibilities ranging from developing ADMET in-silico models, novel scoring methods such as confidence metrics for in-silico models. He also supported the Anti-Bacterial research organization. Rishi earned his PhD. from University of Connecticut where he developed systems engineering approaches for genetic pathway analysis and also developed computational methods for application in drug discovery.


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



  • 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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