Engineered proteins for biologic medicines often fail during expensive, multi-year development cycles. New AI tools now predict protein structures to reduce these failure rates. MIT Tech Review highlights how these models optimize candidate selection before lab testing. This shift cuts R&D costs and speeds delivery of complex therapies to patients.