Programmable Biology: Generative AI for Molecular Design

Biology may be becoming programmable. Drug discovery has long meant searching what already exists. Generative AI is beginning to change that logic: designing molecules de novo, from intent rather than finding them by chance.

I will present work from Latent Labs on this transition. Latent-X1 introduced all-atom generative models for macrocyclic peptides and protein mini-binders, replacing millions of random screening attempts with tens of precision designs. Latent-X2 extended this to antibodies, producing drug-like candidates confirmed not to trigger an immune response in human blood donor assays, the first such demonstration for any AI-generated antibody. Latent-Y takes a further step towards an AI scientist for biology: an agent that puts expert-level structure-based design within reach of any researcher, executing complete campaigns from a text prompt, autonomously or as a collaborative co-pilot, at previously intractable scale.

The underlying advances in all-atom generative modelling, multi-modal conditioning, and agentic reasoning, share deep structure with problems the CVPR community knows well. This talk will explore those connections, and what it means for science when the starting point is no longer a library, but a prompt.