We develop cutting-edge machine learning and AI methods to accelerate drug discovery, decode cancer multi-omics, and advance precision immunotherapy— bridging computational innovation with clinical translation.
We combine AI, computational chemistry, and biomedical science to advance drug discovery, from molecular property prediction to lead optimization. With tools such as MolMap and Leadmaster, we develop AI agents and foundation models that connect molecular design, synthesis planning, and experimental feedback.
For precision oncology, we integrate multi-omics data to understand tumor heterogeneity and identify therapeutic targets, using approaches such as AggMap. Our COMPASS model predicts immunotherapy response across cancer types, with multi-center validation supporting its clinical translation.


