RWD for Regulatory Decision-Making: Learnings from Use Cases and Demonstration Projects

Ulka Campbell, Aetion

Ulka Campbell is an epidemiologist and the Head of Scientific Strategy at Aetion (a healthcare technology and research services company), which provides methods and regulatory support to biopharma and device sponsors across therapeutic areas and leading research to inform regulatory RWE best practices. Previously, Ulka was at Pfizer for 14 years, where she led regulatory studies and served as the Head of Safety Surveillance Research, overseeing a team responsible for post-approval safety studies obligated to the FDA and the EMA. She has co-authored several publications and taught courses on pharmacoepidemiology, standards for decision-grade real-world studies, causal inference, and epidemiologic methods. Ulka is an Adjunct Assistant Professor of Epidemiology at Columbia University and has an MPH from the University of Michigan and a PhD from Columbia University.

Ben Ackerman, Johnson & Johnson

Ben Ackerman is a Principal Biostatistician at Johnson & Johnson Innovative Medicine, where he provides support across therapeutic areas to design and analyse randomised trials, namely those that combine trial data with real world data. He has expertise in causal inference methods to address biases in both randomised trials and non-experimental studies. He is also a lead researcher on a recently awarded FDA U01 grant to develop novel statistical methods for mitigating endpoint measurement error bias between trial and real world settings when conducting externally controlled trials. Previously, Ben worked as a Quantitative Scientist at Flatiron Health, an oncology real world data vendor, where he oversaw the design of studies leveraging EHR data to improve cancer care in the United States. Ben holds a PhD in Biostatistics from the Johns Hopkins Bloomberg School of Public Health.