Invited speaker: Martin Renqiang Min (Agentic Generative Biomedicine)

Title: Agentic Generative Biomedicine

Abstract: Owing to the availability of large-scale multimodal biomedical data and advancement of AI technologies, generative biomedicine for simulating digital cells and patients becomes feasible, which will potentially disrupt drug discovery. In this talk, first I will introduce the concept of generative biomedicine. Then I will present a privacy-preserving framework that combines large language models with autonomous agents (generative models) to drive biomedical discovery. Finally, I will discuss some of our recent generative AI models for 3D molecule optimization, T-Cell Receptor design, and protein-protein complex sequence-structure co-design.