Advancing Diversity in Clinical Trials

The benefits of research belong to all.

Or so our ideals tell us. Reality tells a different story. Systemic imbalances exclude too many people from trial opportunities on the basis of race, ethnicity, economic status, geography, or other social determinant. The exclusion may not be deliberate, but its effects are dire.

What’s the solution? More complex than any single changemaker can achieve. Drug developers, researchers, clinicians, policymakers, educators, and patient advocates all share the responsibility to achieve our ideals. TriNetX has a role to play. As a research leader, so do you.

Connect with one of our real-world data experts to discuss how TriNetX can guide your DEI efforts into ground-breaking territories.

Asian-Americans represent 5.9% of the U.S. population and a mean of 1.6% of all participants in pivotal trials between 2015 and 2019.

Lolic M, Araojo R, Okeke M, Woodcock J. Racial and Ethnic Representation in US Clinical Trials of New Drugs and Biologics, 2015-2019. JAMA. 2021;326(21):2201–2203.

Black Americans make up roughly 12% of the U.S. population and a disproportionate number of new cancer cases. Yet none of the 11 novel drug approvals for cancer in 2022 were based on study cohorts that enrolled more than 8% Black participants.

Center for Drug Evaluation and Research. Drug Trials Snapshots Summary Report 2022.

The barriers to diversity, equity, and inclusion (DEI) in clinical trials are multifaceted. At TriNetX, we are focused on breaking down barriers across all our solutions.

Sound experimental design requires that our samples represent the populations we want to understand. Meanwhile, a commitment to patients demands that we extend benefits, if they are discovered, as widely as possible.

Meeting both mandates starts with the right protocol. Study eligibility attuned to the health and experience of today’s patients, representing all backgrounds, let us design trials with more generalizable results. This RWD-informed approach also extends the benefits of participation to those disproportionately excluded by criteria that paint too broad a brush.

TriNetX Solutions

• TriNetX LIVE™ Networks
• Diversity Lens

In clinical trials, achieving diverse and representative patient populations remains a significant challenge, particularly in rare disease protocols and among populations prone to care transitions. Despite the advancements AI offers, such as improving patient recruitment and site identification, enrollment shortfalls continue to plague the industry, with nearly 80% of studies falling short of their recruitment goals.

Could AI be the key to solving this problem?

Watch our webinar to explore how AI is transforming clinical trial diversity. Delve into the potential of AI to tackle these issues and drive success in patient recruitment and site selection.

TriNetX Webinar: Optimize AI’s Role in Supporting Clinical Research

Natural course of disease. Disease burden. Standard of care. The forms these take are as various as patients themselves. Trends at the population level can quickly fall apart under analysis by cohort, whether defined clinically or demographically. Our rich de-identified data—inclusive of race, ethnicity, and (for millions of US patients) types of insurance coverage—enable researchers to pierce the surface of the “patient profile” to reveal the critical differences in access, treatment, and outcome.

We don’t stop at gathering the data. We interrogate it, with best-in-class analytic tools and the brightest minds in epidemiology and evidence generation.

TriNetX Solutions

• TriNetX LIVE™ Networks
• De-identified patient-level EHR data
• De-identified patient-level linked data (EHR and closed claims)
• Advanced Analytics
• LUCID Trusted Research Enviroment