Clinical trials often suffer from a lack of participant diversity, resulting in findings that may not fully represent the eventual treated patient population. This issue has improved only modestly in the last decades. Recognition of this limitation has coalesced recently with the Food and Drug Association’s recommendations for diversity action plans; however, sponsors and researchers are tasked with determining how to address prior limitations and recruit more diverse patient populations.
Clinical trials play an essential role in bringing forward safe and effective medical treatments and technology, but, of the less than 5 percent of the U.S. population participating in clinical research, 75 percent of these participants are of European descent. A recent analysis of U.S. cancer clinical trials found that 48 percent had no Hispanic or Latin American representation, and only 58 percent included participants who were Black. In addition, in their site selection and implementation, clinical trials may disregard other factors that can impact disease burden and prevalence, such as geographic location.
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Clinical trial sponsors should be empowered to include more diverse and representative patient populations and there is a path forward for better democratization of clinical trials and research.
To break down barriers to clinical trial access, accelerate diverse participation in clinical trials, and ensure more inclusive and representative trial results, researchers can implement the following five strategies:
#1: Improve inclusion by collecting and analyzing social determinants of health data
Many clinical trials do not focus on underserved populations, and very few individuals in these cohorts are recruited to participate in clinical trials. Factors, such as education level and urbanicity, affect the odds of a participant even receiving an invitation to participate in a clinical trial.
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Data from these underrepresented populations, including real-world data and SDoH data, exist and more can be collected. These data hold amazing potential to improve the lives of patients in the rare disease space, develop novel therapeutics, build care pathways, advance adherence, improve the safety and efficacy of healthcare, and develop medical devices, by surfacing insights and providing the foundation for more inclusive clinical trial design and recruitment. Ideally, every new treatment or therapy would be developed with the full inclusion of the populations impacted.
More clinical institutions are collecting SDoH data through interviews and surveys. This information, however, is typically captured in unstructured clinical notes or open-ended survey responses (which leads us to the need for a common healthcare data language – see #3). To fully understand how SDoH influences health and disease treatment response, such data must be collected and standardized in a way that is interpretable by health systems, public health agencies, and research organizations. Most importantly, these data should be analyzed in the broader context of clinical trial planning and implementation to ensure that the right populations are included in drug and medical device trials and the right factors are considered in determining trial outcomes.
#2: Combat data infrastructure challenges
We developed a healthcare ecosystem that connects providers and life science companies as a response to my frustrations as a physician-researcher. I routinely observed how difficult it was to ensure we included all patients, making sure the research truly represented all of our communities. In my mind, the key to resolving this lay in better data standardization and interoperability.
I still observe the healthcare industry struggling with the challenges of siloed data and impediments to data sharing. The broader life sciences community can benefit from access to provider data to identify study populations and determine burden and disease prevalence in different populations. EHRs used in routine care can be further leveraged to supplement clinical trial data and enable research at the point of care. Lowering the barrier to data collection could broaden study types, leading to greater patient diversity in trials. A robust healthcare data ecosystem can help maintain the data capture and flow necessary for democratization.
#3: Create a common data language across stakeholders
Another factor holding back clinical trial democratization and trial accessibility is the absence of a “common language” for data. There is not yet widespread adoption of data extraction from the medical record into one common language that’s accessible to diverse sectors. Various data standards are helping, such as HL7, LOINC, etc., but adoption is slow and inconsistent, and stringent implementation is lacking. Plus, these standards do not address the wealth of data captured in the unstructured sections of the EHR, including the above-mentioned SDoH surveys. Organizations such as the Clinical Data Interchange Standards Consortium are working globally to improve these standards and are worth following to keep up to date with their efforts. Right now, there is no standard by which valuable but disparate sources of healthcare data are automatically integrated in a way that a researcher can query patient demographics and history to support clinical trial engagement. Provider organizations who want to engage in trials do not have all the patient data accessible to easily match their patients to trials. This is a reason why we built a data platform that fuels partnerships that drive patient care.
#4: Leverage clinical data outside the EHR to break down barriers and facilitate access for underrepresented communities
Up to now, many clinical trials have relied on access to dense population centers that accompany large health systems, such as academic medical centers. Study design and participant outreach are limited to these centers’ patients and exclude the broader community and underrepresented patients. Inclusive clinical trials could be conducted outside of large medical centers to ensure that a participant’s genetics, background, and personal experiences are taken into consideration when studying a new treatment’s efficacy and safety. Casting a wider net for trial participant populations and ensuring they stay engaged and enrolled in the trial through completion requires specific personnel, capabilities, and resources for appropriate trial planning, analytic insights, representation, and participant engagement.
A good first step in engaging underrepresented populations is for study sponsors to analyze robust clinical data sets to inform the development of more accurate and broader recruitment, participation, and retention strategies. This can help ensure a more inclusive population is invited to participate in trials and to facilitate the appropriate physicians’ engagement in the trial.
#5: Involve community organizations and businesses in clinical trial support and ensure these locations have the resources and capabilities to successfully conduct clinical trials
Community researchers, specialty practice clinical sites, and local pharmacies can play a pivotal role in clinical trial education and access. With a broader range of recruitment locations comes a more diverse participant cohort, and the resulting treatment innovations are more inclusive. These organizations require assistance, however, to optimize data collection, normalization, and aggregation. This means building out data networks and infrastructure in underrepresented areas, such as rural geographies and community health centers. With this assistance, researchers and study sites are empowered to identify and connect with more participants and conduct more comprehensive analyses.
To increase trial participation, this outreach should extend to community members where they live and work and through smaller local health practices. Some pharmacies, such as Walgreens, are educating the populace about the importance of clinical trials and the opportunities they represent. With only 59 percent of the U.S. population indicating an awareness of clinical trials and how they work, community-based practices and pharmacies have a unique opportunity to drive inclusivity.
The current lack of representation in clinical trials remains distressing and impedes health equity. Without taking specific steps to improve trial diversity – such as promoting greater community involvement, developing the right data ecosystem, building robust inclusive data sets, and using a shared clinical data language – advances in inclusive treatments will continue at a snail’s pace.
Photo: Irina Devaeva, Getty Images
Mitesh B. Rao, MD, MHS is the Assistant Professor of Emergency Medicine at Stanford and the CEO and co-founder of OMNY Health, a venture-backed enterprise fostering real-world data collaboration between providers and Life Sciences companies to accelerate clinical research.
