Biological processes continuously adapt in response to intervention. Unlike static predictive models, biomedical world models support action-conditioned simulations for counterfactual reasoning, intervention design, and sequential planning. This perspective defines the key properties of biomedical world models and discusses the data, modeling, and evaluation challenges required to build them across biological and clinical scales.

Nature Biotechnology, Published online: 20 March 2026; doi:10.1038/s41587-026-03064-w

This Review discusses the promises and pitfalls of biological AI algorithms and presents a vision for generalist biological artificial intelligence, in which models can perform diverse tasks across biological domains.