June 6, 11;00am
Location: Santa Clara I

Accelerating Drug Discovery with AI/ML

Artificial intelligence and machine learning approaches are increasingly utilized to accelerate the discovery of small molecule drug candidates. Combined with other computational approaches, AI/ML is greatly expanding our capability and capacity in designing novel molecules, in suggesting how to synthesize the molecules, and in improving operational efficiency to test the molecules. The accelerated learning cycles enable the exploration of broader chemical space as well as the pursuit of bolder ideas.

Jiye Shi is an Associate Vice President and Global Head of Computational Design and Automation Platforms at Eli Lilly and Company. Prior to that, he was a NewMedicines Fellow and Global Head of CADD (Computer-Aided Drug Design) at UCB Pharma. During the past decades, Jiye and his teams utilized physics, statistics and machine learning/AI based methods to accelerate the discovery of small molecule and antibody therapeutics. He is a co-inventor on 11 patents which led to 2 approved drugs on the market. Jiye received his PhD in Computational Structural Biology with Prof. Sir Tom Blundell at the University of Cambridge and completed his executive MBA training at the University of Rochester. He is an external advisor to the Department of Statistics, University of Oxford. He is passionate about graduate training, and helped establish and manage doctoral training centers in the UK. He holds visiting academic appointments in several countries and has co-authored over 200 scientific publications.