World models for biomedicine.

Abstract

Biological systems respond dynamically to changes in their environment, and predicting these responses before complex interventions are applied could change how computational models are used in biology and medicine. In artificial intelligence, world models represent the state of a system and simulate how it evolves under alternative actions. We envision extending this paradigm to biomedicine, with world models that span molecular, cellular, tissue, and clinical scales and simulate biological trajectories under alternative interventions. Building such models will require methods that combine observational data with interventional and longitudinal measurements across modalities. Biomedical world models could open new modes of inquiry by predicting how biological systems respond to novel perturbations, searching for interventions that drive them toward desired states, and planning experimental campaigns over extended time horizons.