Hariprasad Vankayalapati
CSO Biolexis Therapeutics
Hari co-founded Biolexis Therapeutics, Inc., where he serves as Chief Scientific Officer, overseeing the company’s R&D strategy across metabolic, cardiometabolic, oncology, and CNS therapeutic domains. In partnership with Dr. David J. Bearss, he co-developed the proprietary MolecuLern technology platform, which underpins Biolexis’s mission to discover and develop next-generation oral small-molecule therapeutics. Before founding Biolexis, Hari co-founded and led scientific functions at multiple biopharmaceutical ventures, advancing nine drug candidates into Phase I/II clinical evaluation. With more than two decades of experience spanning academia and industry, his career is defined by translational innovation and collaborative discovery. Hari also serves as a scientific advisor and review board member for pharmaceutical organizations and academic institutions. He earned his M.Pharm in Pharmaceutical Chemistry from the University of Karnataka and his PhD in Medicinal Chemistry from the Institute of Chemical Technology (formerly UDCT), University of Bombay, followed by postdoctoral research at the University of Sunderland, UK, and the University of Arizona Cancer Center under Professor Laurence H. Hurley. He has authored over 100 scientific publications and presentations and is an inventor on numerous issued and pending U.S. and international patents.
Seminars
- Demonstrate how data-first AI frameworks in discovery reduce attrition by sharing practical, validated examples of how they are being used to design real, experimentally confirmed small-molecule degraders, showing what works (and what doesn’t) in moving from prediction to proof
- Gain insight into emerging strategies for precision molecular glue design and highlight novel approaches to rationally engineer glue degraders by integrating structural biology, cheminformatics, and predictive modeling offering valuable lessons for anyone working on targeted protein degradation, GLUES or PROTACs, or complex modality discovery
- Discover frameworks to de-risk R&D pipelines and learn how data-centric model validation and feedback loops can reduce late-stage attrition, accelerate candidate selection, and improve return on discovery investment. Ideas that can be applied across therapeutic areas to accelerate the path from concept to candidate