Critical Roles for Modeling and Simulation and Real-World Evidence to Inform Challenges in Clinical Trial Diversity Planning

Abstract

Due to the highly controlled settings of clinical trials, enrolled subjects may not be fully representative in age, gender, ethnicity, medical status, or socioeconomic background of the variety of patients who will ultimately receive a medication. This disconnect can lead to post-approval challenges, the most substantial of which could include changes in drug label, dosing, or withdrawal due to severe safety risks that were only observed post-approval. To mitigate these risks and improve the likelihood of approval of safe and effective treatments for patients in the real-world setting from both a medical and socioeconomic perspective, recent regulatory guidance has highlighted a critical role for the inclusion of appropriately diverse populations in clinical trials. To achieve this, there is an increasing need for approaches to facilitate sponsors' ability to generate regulatory-acceptable diversity plans. While epidemiological data may serve as the foundation for diversity planning, researchers are increasingly turning toward modeling and simulation (M&S) approaches to optimize study planning and increase the knowledge gained from study data. Additionally, real-world evidence (RWE) generation is receiving increased attention in the regulatory setting, but prior research has only begun to scratch the surface of the value these approaches can bring to trial diversity planning. Herein, we summarize the strategic value of M&S and RWE-based approaches in the context of trial diversity planning, highlighting unmet needs, prior thought leadership, and recent case examples with the goal of providing readers insight into their diversity planning at different stages of the drug development lifecycle.