The FDA Group’s Nick Capman sits down with Dr. Manfred Stapff—physician, author, and founder of Candid Advisory Inc., a consultancy specializing in real-world evidence and clinical development—for a wide-ranging conversation about how real-world data is reshaping drug development, regulatory decisions, and public understanding of evidence. Dr. Stapff draws on decades of experience across medical affairs, clinical trials, and RWE analytics to explain why real-world evidence isn’t a replacement for randomized controlled trials—but a necessary complement. He outlines how to transform raw data into credible evidence, how the FDA is using RWE today, and why quality, transparency, and context are essential in data-driven science. He also offers cautionary insight on common pitfalls—from bias in training data and misinterpreted statistics to the challenges of AI integration in healthcare research.
What they cover:
- What real-world evidence is (and isn’t)—and how it differs from clinical trial data
- How RWE is being used by the FDA to support label expansions and safety monitoring
- Key risks around self-reported data, upcoding, and poor data quality
- Why statistical significance isn’t enough—and how to evaluate clinical relevance
- How AI can accelerate pattern recognition and predictive diagnostics
- Why training data matters—and how bias can infiltrate large-scale AI tools
- The role of educated skepticism in interpreting data-driven claims in both science and society
Dr. Manfred Stapff is the founder and principal consultant at a boutique advisory firm focused on real-world evidence strategy, clinical development, and medical data intelligence. He is the author of Real World Evidence Unveiled and a frequent speaker on the role of data integrity, statistical literacy, and AI in advancing medical research. His current work supports life science companies and investors in evaluating drug development strategies, acquisition opportunities, and data-driven innovations.