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 systems identify viable drug candidates faster. This shift cuts R&D costs for researchers targeting complex diseases with protein-based therapies.