Associate Professor, College of Pharmacy
The University of Arizona, USA
Dr. Li is currently associate professor of medicinal chemistry in College of Pharmacy, University of Arizona. Dr. Li received his Ph.D. degree from the University of Tokyo. He did the postdoctoral training at Columbia University and Harvard University. Dr. Li has extensive experience in drug discovery and development, with a particular focus on Oncology. He has led medicinal chemistry teams with about twenty chemists, and collaborated with leaders in pharmacology, toxicology, pharmacokinetics, pharmacy, and intellectual property for the discovery of new experimental drugs (IND). He and his team have successfully discovered three small molecule kinase inhibitors with acceptable toxicology profile, that were tested in clinical trials. Dr. Li was the kinase platform-rational drug design leader at Eli Lilly and was responsible for the generation of kinase inhibitors. His broad expertise in the study of kinases and cancer will allow him to discover the next generation kinase inhibitors for use in cancer and Alzheimer’s disease.
Dr. Li’s research interest is drug discovery and development of kinase inhibitors for rare and/or neglected cancer diseases in a High-Throughput manner. To discover active hits, a novel type of kinase fragment library will be generated in a High-Throughput manner. This kinase fragment library will be designed to overcome most of issues concerning kinase fragment libraries. Compounds identified from the library as an active will be further optimized for better activity and toxicity profiles. The optimization will be done through the library synthesis approach, rather than the industry standard approach of solving SAR (structure-activity relationship) problems one molecule at a time. The one-by-one approach may work well in the beginning of the sequence of the drug discovery value chain, but you may run the risk of encountering the initial problems when trying to solve the next problem. One-cycle library iteration will produce a wide range of SAR information including toxicity for the next library design and production. Three to five cycle iterations of libraries will generate advanced compounds with properties to produce the desired in vivo efficacy with acceptable toxicity profile. The library design approach aided by the computer modeling and calculation will focus on solving any unforeseen SAR problems for each cycle.