Randomized clinical trials have long been held as the evidentiary standard for determining safety and efficacy for medical products. But clinical trials alone may not be sufficient to address the information needs of patients, clinicians, regulators, and payers. There is strong support for using real-world data and real-world evidence to assess new therapies, especially in the context of smaller and/or more diverse populations. Further, model-informed drug development, which involves the use of mathematical models to inform drug development, is seen as a promising approach to accelerating development timelines and, ultimately, delivering treatments to patients faster. While regulators have expressed an openness to these approaches in certain scenarios, what do we know of their acceptability to patients, clinicians, and payers? In this session, we will discuss the outlook of these approaches in medical product development, examine the willingness of patients, clinicians, and payers to adopt products that have been developed using information generated outside the traditional clinical trial paradigm, and outline next steps for increasing public awareness and understanding of how these approaches are informing regulatory decisions.

Moderator

Susan Winckler

CEO, Reagan-Udall Foundation for the Food and Drug Administration

Speakers

Jacqueline Corrigan-Curay

Principal Deputy Center Director, Center for Drug Evaluation and Research, Food and Drug Administration

Mat Davis

Vice President, Data Science, Jazz Pharmaceuticals

Adrian Hernandez

Executive Director and Vice Dean, Duke Clinical Research Institute

Carolyn Magill

CEO and Board Director, Aetion