McKinsey released analysis arguing that biopharma firms need a structural redesign to turn AI-driven workflows into compounding learning rather than isolated efficiency gains. The report describes a shift away from linear stage gates toward a closed-loop R&D model anchored on five connected decision points—starting with understanding patient and disease biology and ending with maximizing impact of approved therapies through feedback that refines prior decisions.