Engineered proteins form the basis of biologic medicines, yet most candidates fail during development. New AI tools now predict protein structures and interactions with higher precision. MIT researchers are leveraging these models to slash expensive trial-and-error cycles. This shift reduces the time and capital required to move candidates from the lab to patients.