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Supporting Diversity and Inclusion Goals for Clinical Trials with an Effective Analytics Strategy

Navigating Change: 10 Highlights from the FDA's Draft Guidance for Decentralized Trials

The top priority of life sciences organizations is ensuring the safety and efficacy of new clinical treatments in order to improve the health of the individuals and communities they serve. Naturally, the effectiveness of clinical trials hinges on compiling and analyzing data that accurately reflects the target population.

On average, the rate of clinical trial participation from racial and ethnic minorities in the U.S. ranges from 2%-16%, despite making up close to 40% of the population.

The under-representation of racial and ethnic minorities in clinical trial participation in the United States has become strategic imperative, in 2022, newly proposed legislation, the DEPICT ACT, was introduced in Congress as one way to address this problem. Enrolling participants from diverse backgrounds is no longer an aspiration for trial sponsors to work towards— it’s a requirement.

Lack of diversity in clinical trials isn’t just a recruiting problem—it’s a data problem.

The emergence of modern, digitized data infrastructure and analytics platforms presents a tremendous opportunity for life sciences organizations to accelerate progress on their diversity goals. These platforms provide real-time views of enrollment goals and demographics to support data driven trial operations with leading indicators demonstrating real-time results.

In this ebook, we will examine the role data and real-time analytics play in ensuring life sciences organizations are able to support participant diversity goals for improved trial outcomes along with:  

  • Important DEPICT clarifications and how to fulfill these goals.
  • The role of a modern data infrastructure in participant diversity and inclusion
  • Case study: How Cerevel Therapeutics operationalized diversity in clinical trials 

2024 Industry Outlook: Driving Tomorrow’s Breakthroughs with Clinical Data Transformation