Beyond Outreach: Structural Drivers of Representation in Clinical Trials

This is the second of a two-part series. Click here for part one.

Escalating Effort Without Structural Change

Participant burden and access issues are believed to be the biggest challenges in advancing representation in clinical trials.^1,2 It does not seem to be for a lack of trying.

Industry has made visible investments to reduce participant burden and improve access. Decentralized approaches, flexible visits, language translations, and reimbursement support are all common.^1,3

Industry has also invested in community partnerships and community-based approaches to bring research to the community, including efforts to educate, raise awareness, and discuss clinical research with community members.^4-7 Yet, 80% of sponsors say they are not meeting their representation goals.⁸

The efforts that are driving these investments are evident. But, similar to recruitment being treated as an operational challenge, we are not yet systematically addressing the structural design decisions that shape representation.

Inclusion efforts often act as an overlay to operationally compensate for upstream decisions. What is needed is a systemic shift: sponsors must consider representation in the design of the trial itself, not address it primarily through downstream efforts to compensate for structural barriers.

Access Mismatch

One consideration is access. A recent study found that using decentralized local labs may improve representation of racially and ethnically diverse participants, although home visits may decrease representation across many population groups, particularly Black participants.⁹

Approaches must be customizable. To advance equitable representation, we need to understand who we are trying to reach and recognize that preferences, burden, and access differ across populations. Access interventions must be population-specific and evidence-based.

The physical location of the research study center is an important factor in the decision to participate in a research study.¹⁰ Although a large proportion of the United States population lives within 50 miles of a clinical research site for common advanced cancers, research sites are not evenly distributed around the country and are not accessible to all individuals.¹¹

American Indian and Alaska Native patients, in particular, have reduced access to clinical trials based on distance to a research facility.¹²

Travel burden can also be substantial. One study found that patients with income below the federal poverty level traveled a median of 92 miles to reach a trial center conducting cancer clinical research.¹³

Patients living in rural areas sometimes travel five times farther to attend their visits than those living in urban areas.¹⁴ Across trial types, the average distance participants travel to a clinical trial site is ~67 miles one way.¹⁴

A search for ongoing interventional clinical trials actively recruiting for Alzheimer disease research left many states across the US with no available options.¹⁵ And yet, the average distance to a McDonald’s in the contiguous 48 states is 3.07 miles.¹⁶

How can clinical research professionals learn from McDonald’s, Starbucks, and other fast-food chains that use data and sociodemographic insights to understand where their customers are and make strategic decisions about site locations and marketing? Clinical research also uses data to understand where patients are and to inform site selection and patient outreach. Sound familiar?

The difference is that clinical research often uses this intelligence within the boundaries of an existing site network. What if we used that intelligence earlier to inform where research sites should be located in the first place?

How can we apply this thinking to clinical research? Would selecting research sites in previously uncovered territory across the Midwest improve access? Would advertising that normalizes clinical research increase participation?

Increasing access is a structural decision. In many communities, fast-food outlets are more geographically accessible than research sites. This is not by accident.

Starbucks and McDonald’s do not wait for customers to travel 67 miles. They proactively determine where the next best market is rather than reactively repeating legacy decisions.

We need to structurally change where we are placing our research sites and how we approach outreach. Geography alone reveals structural inequities.

Inclusion as an Overlay

Industry often treats inclusion as an overlay, layered on to counteract systemic realities and design decisions that restrict the representativeness of research programs, resulting in:

• Repeated historical decisions
• Repeated eligibility criteria
• Repeated sites
• Repeated geographies
• Repeated trial populations

Benchmarking disease demographics against enrolled populations is not yet mainstream across industry sponsors.² In a recent Applied Clinical Trials survey, only 24% of respondents reported systematically benchmarking target-disease demographics against their enrolled clinical trial population, suggesting that disease-specific assessment of enrollment representativeness is not yet a routine practice across organizations.^1,2

Eligibility criteria are another design decision that can negatively affect access. Efforts to broaden eligibility criteria, where scientifically and clinically appropriate, are not regularly implemented across sponsor organizations.³

More restrictive eligibility criteria from Phase II studies often carry over to Phase III protocols, unnecessarily restricting access to real-world patients.¹⁷ For example, static laboratory ranges may eliminate otherwise eligible participants.

Bose et al¹⁸ evaluated recruitment and retention patterns of clinical studies conducted at their center in India. Nearly 60% of screen failures across their studies over a five-year period were due to abnormal laboratory values.

They observed that this could have resulted from the normal ranges that the protocol stipulated on the basis of central laboratory reference ranges. The ranges were not modified to reflect normal values across the population recruited in India.¹⁸

How do you know how to create an inclusive protocol, site selection, and engagement strategy without first knowing who to recruit? Sponsors cannot retrofit inclusion onto a design that was never structured for broad access.

These are overlays, not structural redesigns. Consider the structural realities:

• Patients routinely travel more than 50 miles to participate, even farther for some populations, such as those living in rural areas.
• Just under a quarter of organizations report systematically benchmarking disease demographics against enrolled populations.
• Eligibility criteria are often unnecessarily narrow.
• Sites are unevenly geographically distributed, clustering in urban areas.
• Sponsors do not always consider disease demographics, eligibility criteria, and access together when defining the intended trial population.

Representation gaps are not surprising under these conditions. They are predictable.

We are attempting to diversify enrollment within designs that may systematically limit eligibility, increase burden, and concentrate access in select geographies. In other words, we are treating inclusion as an operational overlay while filtering potential participants out by design.

An Inclusion-by-Design Framework

An inclusion-by-design approach shifts the focus from how we recruit participants to how we design clinical research to make broader participation possible from the outset. Increasing representation must be designed intentionally. An inclusion-by-design framework should involve:

• Demographic benchmarking: Systematically comparing eligibility criteria and enrollment projections against the demographic profile of the real-world disease population to inform upstream trial design decisions.
• Eligibility equity review: Critically evaluating inclusion and exclusion criteria for scientific and clinical necessity rather than historical convention, requiring justification for restrictions.
• Burden and accessibility protocol review: Incorporating participant burden and access considerations during protocol design and concept review, and intentionally identifying measures that make the study operationally feasible and less burdensome for the intended trial population.
• Site selection redesign: Assessing site placement relative to disease prevalence and patient distribution while ensuring more equitable geographic access.
• Community-informed development: Engaging intended populations before key study design decisions are made.
• Representation accountability: Establishing key performance indicators tied to equitable enrollment performance, not just overall enrollment speed.

Inclusion challenges are not primarily failures of community engagement or recruitment efforts. They are consequences of structural design decisions.

When access is misaligned, when burden is unevenly distributed, and when eligibility criteria filter out large segments of the intended population, inclusion becomes an operational aspiration constrained by a structurally exclusionary design. If we want equitable participation, we must build it into the foundation of the system, not attempt to later compensate for decisions that have already limited who can participate.

Inclusion, like recruitment performance, is systemically engineered upstream.

References

1. Studna A. Applied Clinical Trials’ 2025 state of the industry survey. Appl Clin Trials. 2025;34(4). Accessed October 9, 2026. https://www.appliedclinicaltrialsonline.com/view/applied-clinical-trials-2025-state-industry-survey
2. Johnson R. Designed for performance, part 1: recruitment is a design outcome, not an operational failure. Appl Clin Trials. 2026;35(2):8-9. Accessed October 9, 2026. https://www.appliedclinicaltrialsonline.com/view/designed-performance-recruitment-outcome-operational-failure
3. PhRMA. Industry efforts to enhance clinical trial diversity. July 2022. Accessed October 9, 2026. https://www.phrma.org/resources/a-look-at-company-efforts-to-enhance-clinical-trial-diversity
4. Sanofi. Sanofi commits $18 million to Howard University College of Medicine, Meharry Medical College, and Morehouse School of Medicine to increase diversity in clinical studies. News release. Sanofi US News. October 16, 2024. Accessed October 9, 2026. https://www.news.sanofi.us/2024-10-16-Sanofi-commits-18-million-to-Howard-University-College-of-Medicine,-Meharry-Medical-College,-and-Morehouse-School-of-Medicine-to-increase-diversity-in-clinical-studies
5. Equitable Breakthroughs in Medicine Development. Equitable Breakthroughs in Medicine Development (EQBMED) to work with inaugural sponsor companies to drive greater diversity in clinical trials. News release. PR Newswire. September 12, 2024. Accessed October 9, 2026. https://www.prnewswire.com/news-releases/equitable-breakthroughs-in-medicine-development-eqbmed-to-work-with-inaugural-sponsor-companies-to-drive-greater-diversity-in-clinical-trials-302246462.html
6. Merck. Let’s talk trials. Merck Clinical Trials. 2026. Accessed October 9, 2026. https://www.merckclinicaltrials.com/lets-talk-trials/
7. Center for Information & Study on Clinical Research Participation. AWARE for all. 2026. Accessed October 9, 2026. https://www.ciscrp.org/aware-for-all
8. Flanagan J, Evers J. How customer-first clinical trials cut complexity and delays. Bain & Company. April 2023. Accessed October 9, 2026. https://www.bain.com/insights/how-customer-first-clinical-trials-cut-complexity-and-delays/
9. Smith Z. Current industry trends, and new and emerging opportunities for optimization. Presented at: Evolution Summit; September 2025; Carlsbad, CA.
10. Center for Information & Study on Clinical Research Participation. 2025 perceptions and insights study: deciding to participate. 2025. Accessed October 9, 2026. https://www.ciscrp.org/wp-content/uploads/2025/11/2025-Perceptions-Insights-Deciding-to-Participate_FINAL.pdf
11. Swenson W, Westergard E, Schroeder Z, et al. Geographic distribution of clinical trials for common advanced-stage cancers in the United States. J Clin Oncol. 2024;42(16 suppl):e18503.
12. Swenson W, Swenson A, Westergard E, et al. Geographic distribution of clinical trials for advanced-stage cancer. JAMA Oncol. 2024;10(8):1132-1133. doi:10.1001/jamaoncol.2024.1690
13. Borno H, Zhang L, Siegel A, et al. At what cost to clinical trial enrollment? A retrospective study of patient travel burden in cancer clinical trials. Oncologist. 2018;23(10):1242-1249. doi:10.1634/theoncologist.2017-0628
14. TrialX. How far do patients travel to participate in clinical trials? TrialX. October 2025. Accessed October 9, 2026. https://trialx.com/how-far-do-patients-travel-to-participate-in-clinical-trials/#:~:text=Cardiovascular%20clinical%20trial%20sites%20are,only%2011.2%25%20of%20urban%20residents
15. ClinicalTrials.gov. Clinical trials map. Accessed October 9, 2026. https://www.clinicaltrialsmap.org/
16. Hadlock S. A happy meal is never far away: the average distance to a McDonald’s in the US. Best Neighborhood. Accessed October 9, 2026. https://bestneighborhood.org/a-happy-meal-is-never-far-away-the-average-distance-to-a-mcdonalds-in-the-us/
17. US Food and Drug Administration. Enhancing participation in clinical trials – eligibility criteria, enrollment practices, and trial designs: guidance for industry. December 2025. Accessed October 9, 2026. https://www.fda.gov/media/190162/download
18. Bose D, Saha S, Saxena U, et al. Factors influencing recruitment and retention of participants in clinical studies conducted at a tertiary referral center: a five-year audit. Perspect Clin Res. 2020;11(2):81-85. doi:10.4103/picr.PICR_198_18