Leveraging RWD With AI To Enable Diverse Recruitment In Clinical Trials

By Lakshmi Sankar and Isabelle Cheung, PA Consulting

Clinical trials today face a significant hurdle: a lack of patient diversity. Disparities underscore the urgent need for clinical trials to better reflect the populations they aim to serve.

A recent survey of 2,000 U.S. respondents revealed strong public support for increased diversity in trials. Three-quarters of those surveyed believe that greater diversity in clinical trial recruitment will lead to more effective and suitable drugs for a broader population.

Addressing patient diversity is not just a moral imperative; it's a public health necessity. The FDA is actively pushing for mandated trial diversity through its updated draft guidance on Diversity Action Plans. By assisting clinical trial sponsors in submitting these plans, the FDA aims to ensure adequate participation from underrepresented groups and facilitate data analysis from clinically relevant populations.

Ultimately, a diverse cohort of research participants is crucial for developing inclusive studies that accurately represent the target population. This is especially important for understanding the unique healthcare needs and challenges within underrepresented communities. To overcome this challenge, pharmaceutical companies must enhance diversity, equity, and inclusion (DEI) in clinical trial research. This can be achieved by utilizing real-world data and evidence and by leveraging AI to more efficiently and intelligently source data to improve DEI design.