Reducing R&D Cycle Time in Pharma Without Increasing Regulatory Risk - with Vaithi Bharath of Bayer

Today's guest is Vaithi Bharath, Associate Director of Data Science & AI Solutions at Bayer. Bharath joins Emerj Editorial Director Matthew DeMello to break down why clinical R&D timelines often slip for reasons that have little to do with model performance. Rather, delays compound when data moves across fragmented systems, teams rely on slow handoffs, and validation requirements turn minor adjustments into major cycle-time hits. He walks through where decision-making slows from data capture through database lock, and what it takes to accelerate workflows without replacing a validated environment. Want to share your AI adoption story with executive peers? Click emerj.com/expert2 for more information and to be a potential future guest on the 'AI in Business' podcast! This episode is sponsored by AnswerRocket.