Engineered proteins for biologic medicines often fail during expensive, multi-year development cycles. New AI tools now predict protein structures and interactions to reduce these failure rates. MIT Tech Review highlights how these models streamline candidate selection. This shift allows researchers to bypass traditional trial-and-error, speeding the delivery of targeted therapies to patients.