Pat Walters is the Chief Scientist at OpenADMET, an open-science initiative integrating high-throughput experimentation, structural biology, and machine learning to advance ADMET prediction. Alongside his work at OpenADMET, he serves as an Adjunct Professor in the Department of Bioengineering & Therapeutic Sciences at UCSF.

Pat brings over thirty years of industry leadership to his roles, having previously held senior positions at Relay Therapeutics and Vertex Pharmaceuticals. A dedicated educator and communicator, he is the author of the widely read blog “Practical Cheminformatics,” where he shares technical insights on computational drug discovery.

His contributions to the field were recognized by the American Chemical Society with the 2023 Herman Skolnik Award for Chemical Information Science. Pat is a co-author of Deep Learning for the Life Sciences (O’Reilly, 2019) and serves on the editorial advisory boards for the Journal of Chemical Information and Modeling and Artificial Intelligence in the Life Sciences. He earned his Ph.D. in Organic Chemistry from the University of Arizona and his B.S. in Chemistry from UC Santa Barbara.