[Image courtesy of Pixabay]

The lack of appropriate representation in clinical trials, particularly in terms of ethnicity and race, has been a long-standing issue that directly impacts health equity and treatment efficacy. In a 2020 analysis of the global participation in clinical trials, the Food and Drug Administration (FDA) highlighted the vast difference between enrolled participants and the global population. Of the more than 297,000 participants in clinical trials globally, 76% were white, 11% were Asian, and only 7% were Black. By comparison, 60% of the global population hails from Asia, 16% from Africa, 10% from Europe, 8% from Latin America, and just over 4% from the United States.¹

The FDA has focused on addressing this issue, drafting new guidance in April 2022 aimed at increasing clinical trial enrollment from underrepresented racial and ethnic populations. This draft guidance, “Diversity Plans to Improve Enrollment of Participants from Underrepresented Racial and Ethnic Subgroups in Clinical Trials,” recommends that sponsors of medical products develop and submit a Race and Ethnicity Diversity Plan to the agency early in clinical development, based on a framework outlined in the guidance.²

Reasons for the lack of diversity in clinical trials are wide-ranging. They include a perceived mistrust of the clinical research system due to historical abuses, aspects of the trial design such as inadequate recruitment and retention efforts, frequency of study visits, time and resource constraints for participants, transportation, and participation conflicting with caregiver or family responsibilities. In addition, language and cultural differences, health literacy, religion, limited access within the health care system and a lack of awareness and knowledge about what a clinical trial is and what it means to participate may impact clinical trial participation among racial and ethnic minority populations.²

Despite a commitment to expand diversity in enrollment, there remains room for improvement to address the representativeness of clinical trial populations.

Heavy reliance on academic medical centers can impede diversity

Historically, life science and pharmaceutical companies have worked directly with large academic medical centers (AMCs) to execute clinical trials. This process has been the de facto standard for more than 20 years. This approach has demonstrated advantages, including the established infrastructure to run trials and experienced research teams found at AMCs, both of which can help expedite the clinical trial life cycle. However, there can also be inherent challenges with this methodology when it comes to improving diversity. For example, more than 70% of the U.S. population lives more than two hours from an AMC, making localized participation challenging for many.³ Getting time off from work, childcare, and transportation costs are also barriers to getting diverse populations to participate in site-based clinical trials.⁴

Expanding the availability of clinical trials to practices and providers outside of AMCs — and potentially closer to diverse populations — is one approach to bringing more equity in enrollment. In addition, enrolling patients more representative of the population with the specific illness may require pharmaceutical companies to look beyond conventional methods to identify new participants with more diverse racial, ethnic, and socioeconomic backgrounds.

Decentralized clinical trials broaden outreach but can lack provider support

Decentralized clinical trials are one way to expand patient outreach and recruitment outside traditional medical center settings. Generally conducted remotely with patients remaining at home, these trials have been extensively adopted in the wake of the COVID-19 pandemic when patient access to trial sites became limited.³

Decentralized clinical trials help support diversity objectives in that they consult patients directly rather than through a medical institution. Using marketing outreach, pharmaceutical companies can monitor enrollment to ensure diversity among specific minority groups. However, these outreach methods may not capture the entire picture. For example, social media recruitment advertising written in English excludes more than 25 million Americans who have limited English proficiency, according to Census Bureau data.⁵ Furthermore, these efforts do not necessarily translate to patient recruitment because the healthcare provider’s role may be diminished in these scenarios. Physicians are a vital constituent in the clinical trial process – trusted influencers who answer questions, alleviate concerns, and ultimately care for patients, translating into helping many qualifying patients enroll in a clinical trial. Overall recruitment efforts could fall short without a close partnership with these providers.

A data-centric approach to patient centricity and provider partnership

One way to improve the diversity of clinical trials is to find patients where they are located while retaining close partnerships with trusted providers. A strategy for accomplishing this objective is to tap into the patient pools of specialty clinics and community-based medical practices within desired geographic regions.

By analyzing real-world data (RWD) from a robust community-practice network – such as qualified clinical data registries to which tens of thousands of community practices contribute their electronic health record (EHR) data – pharmaceutical companies can pre-determine where under-recruited or under-enrolled populations present and plan their trial sites accordingly. Moreover, they can continue working directly with the identified providers, enlisting them as trusted caregivers to bolster patient recruitment and facilitate trial execution.

When identified providers are not interested in or equipped to be a clinical trial site, referring qualifying patients to a trial may be attractive, particularly for patients with a condition for which there is no standard of care.

Referencing EHR data provides a holistic view of a patient’s medical history, race, ethnicity, socioeconomic status, and more. Artificial intelligence (AI) methodologies, such as machine learning (ML) and natural language processing (NLP), can also be applied to this data to gain deeper insights that aid in clinical trial inclusion and exclusion criteria. For example, much of the valuable clinical data on patients seeing medical specialists, such as neurologists and urologists, live in the unstructured clinical notes. This can include cognitive assessment scores, motor scores, ambulatory status, radiology, and pathology reports. Clinician-guided NLP can mine usable insights from this free-form text to identify key characteristics determining patient suitability for a specific trial. Subsequently, these insights can help improve recruitment efforts across different patient populations, saving time and resources over traditional manual methods.

Finally, continued use of AI-driven approaches and RWD analysis in Phase IV and beyond can provide pharmaceutical companies valuable information on drug efficacy and safety, including more specific data on different races and ethnicities. These insights can aid in drug development and ensure reported findings are representative of real-world, diverse patient populations.

Sujay Jadhav

Establishing diversity in clinical trials is essential to achieving health equity by ensuring historically underrepresented patient populations have equal access to and efficacy from new and investigative therapies that can help improve outcomes. Taking a real-world data-based approach can help unlock the ability to find new sites and diverse patient populations while keeping the focus on the trusted patient-provider connection often found in community practices. This can help bridge the current diversity gaps in traditional academic medical institution partnerships and emerging decentralized clinical trials.

Sujay Jadhav is the CEO of Verana Health