Paige Bowling is a computational chemist whose research explores how machine learning can accelerate drug discovery. Her current work focuses on enhancing Multisite Lambda Dynamics (MSLD), a computational method that allows scientists to simulate how well different drug-like molecules bind to a target protein. Traditionally, screening large libraries of potential drug molecules is both time-consuming and computationally expensive. Paige’s research addresses this challenge by developing new reinforcement learning approaches that help computers “learn” how to explore these molecular systems more efficiently.
By integrating reinforcement learning with adaptive biasing techniques, Paige’s work will allow simulations to adjust in real time, this prioritization furthers exploration of promising regions of chemical space and could drastically reduce the time spent on unlikely candidates. These advancements have the potential to accelerate the development of treatments for a wide range of diseases.