Woody Sherman – Entering the Era of Physical AI in Drug Discovery

QCMS Online Seminar Series brings together leading researchers working at the interface of QSAR, cheminformatics, molecular modeling, artificial intelligence, and drug discovery. In this talk, Woody Sherman presents “Entering the Era of Physical AI in Drug Discovery”, discussing how recent advances in physics-based modeling, artificial intelligence, and computational drug discovery are shaping a new generation of molecular design workflows. Talk title: Entering the Era of Physical AI in Drug Discovery Speaker: Woody Sherman Event: QCMS Online Seminar Series Date: May 28, 2026 Organizer: QSAR, Chemoinformatics and Modeling Society (QCMS) Talk Abstract: Artificial intelligence is changing how scientific work is performed, but the core challenges of drug discovery remain. Progress still depends on solving difficult predictive problems rooted in the physical world, including molecular interactions, conformational dynamics, binding energetics, chemical reactivity, and the multiparameter tradeoffs that determine whether a molecule can become a medicine. These grand challenges are unlikely to be solved by language-based AI alone. They will require advances in what may be called Physical AI: predictive systems that integrate machine learning with physics, simulation, experiment, and expert judgment. This talk will examine the emerging role of Physical AI in drug discovery and the conditions under which it can materially improve outcomes. It will outline a spectrum of problem types, ranging from those that may benefit primarily from large-scale data-driven learning to those that still require explicit physical modeling or tightly coupled hybrid approaches. It will also discuss the importance of closed-loop workflows that combine AI, simulation, and fit-for-purpose assays, as well as the implications for foundation models, open scientific infrastructure, and the measurable bottlenecks that must be addressed if AI is to improve candidate. Biography: Woody Sherman is the Founder and Chief Innovation Officer of PsiThera, where he leads the development of a computational-first drug discovery platform advancing oral small-molecule medicines for high-value immunology and inflammation targets traditionally addressed by biologics. He is also Chair of the OpenFold Consortium Executive Committee, guiding a global open science effort to build next-generation foundation models for biomolecular structure and drug design that are shaping the future of the field. Across industry and academia, Woody has been a pioneer in applying physics-based simulation, AI/ML, and integrated experimental-computational workflows to solve real-world drug discovery problems. His career spans leadership roles as Chief Computational Scientist at Roivant Sciences, Chief Scientific Officer at Silicon Therapeutics, and Global Head of Applications Science at Schrödinger, where he helped translate advanced modeling technologies into widely adopted discovery tools. Woody has authored over 100 peer-reviewed publications spanning molecular simulation, free energy methods, protein structure and dynamics, machine learning, and structure-based drug design, and is an Adjunct Professor at the University of Massachusetts Amherst. His work bridges deep technical innovation with strategic vision for how computational technologies can materially transform the speed, cost, and probability of success in drug discovery.