Chris Miller, PhD, is the founder and principal consultant of Verida Sciences LLC, a consulting practice providing biostatistics, clinical trial methodology, and regulatory strategy support to life sciences organizations. He holds a PhD in Epidemiology from the University of Pennsylvania and an MS in Biostatistics from the University of Minnesota. He also currently serves as an Associate Scholar at Penn’s Center for Clinical Epidemiology and Biostatistics (CCEB).

Over more than 15 years, including senior roles at Pacira BioSciences, 3D Communications, and NAMSA, he has supported development programs across a wide range of therapeutic areas, from anesthesia and analgesia to gastroenterology, cardiology, infectious disease, psychiatry, and vaccines. His experience also extends to global public health, having served as a biostatistics subject matter expert for the Gates Foundation, where he reviewed the design and analytical rigor of more than 50 international trials in resource-constrained settings. He has led scientific and regulatory preparations for more than 30 FDA Advisory Committee meetings and is known for translating complex statistical strategy into clear, defensible regulatory communications for briefing packages, submissions, and label negotiations.

Chris's methodological expertise centers on the design and analysis challenges posed by intercurrent events and missing data, particularly the handling of rescue medication and treatment discontinuation in clinical trials. Under grant support from the FDA’s Division of Anesthesiology, Addiction Medicine, and Pain Medicine (DAAP), he leveraged more than 20 years of data from RCTs previously submitted to the Agency to develop novel statistical approaches to reduce bias from confounding by rescue medication and collaborated on a new patient-centered endpoint to improve the interpretability of pain trial results. This methodological work, together with his breadth across therapeutic areas and regulatory settings, has shaped a consulting practice built on communicating rigorous statistics in terms that clinical, regulatory, and executive audiences can act on.