Michael J. Keiser ^UDM

Michael J. Keiser, a National Science Foundation Fellow, earned his PhD in bioinformatics from UCSF in 2009, focusing on developing techniques like the Similarity Ensemble Approach (SEA) to establish relationships between drugs and proteins based on ligand similarity. Holding BSc, BA, and MA degrees from Stanford University, Dr. Keiser co-founded a startup to apply these methods in the pharmaceutical industry and the US FDA. Joining UCSF's faculty in 2014, he holds positions in the Department of Pharmaceutical Chemistry and the IND, with a joint appointment in the Department of Bioengineering and Therapeutic Sciences. Dr. Keiser's lab explores forward polypharmacology for complex diseases and predicts drug off-target activities using a combination of machine learning and chemical biology methods. The lab investigates how small molecules perturb entire protein networks, challenging the traditional pharmacological notion of "one drug hits one target." Their work aims to identify therapeutic chords for neurodegenerative diseases and uncover unintended side effects induced by drugs.