Why therapeutic-area benchmarks matter under FDORA
When a sponsor submits a Diversity Action Plan (DAP) under FDORA, they don't set enrollment goals in the abstract. They set them relative to two things: the disease burden of the condition being studied, and the demographic composition of the U.S. population. A cardiology trial with a sponsor targeting 25% Black enrollment isn't arbitrary—it reflects the fact that Black Americans die from cardiovascular disease at 1.3 times the rate of white Americans.
This matters for sites because DAP goals are therapeutic-area specific. A site that runs five oncology trials faces different diversity benchmarks than one running five cardiology trials. And a sponsor evaluating your site for a nephrology study will be looking at your historical Black enrollment data—not your overall diversity statistics.
Most sites have never seen these benchmarks laid out by disease area. They're operating blind, with no clear sense of whether their current enrollment profile is above or below what sponsors will expect. This article is meant to fix that.
The figures below draw from FDA reports, HHS OIG audits, Lancet analyses, and peer-reviewed literature through early 2026. They represent the current state of enrollment—not the DAP goals sponsors will set. The gap between current enrollment and U.S. disease burden is exactly what DAP goals are designed to close. That gap is your site's risk exposure.
The baseline: national enrollment gaps vs. U.S. population
Before diving into therapeutic areas, it helps to understand the baseline problem. Across all clinical trials in the United States, enrollment has been systematically unrepresentative for decades. Between 2015 and 2019, 78% of clinical trial participants were white, despite white Americans comprising only 61% of the U.S. population. Every other demographic group was correspondingly underrepresented.
The table below shows the national enrollment gap—the difference between a group's share of trial participants and their share of the U.S. population. These gaps are what FDORA was written to address.
| Demographic Group | U.S. Population Share | Clinical Trial Enrollment Share | Enrollment Gap |
|---|---|---|---|
| White (non-Hispanic) | 61% | 78% | +17 pts (overrepresented) |
| Hispanic / Latino | 16.3% | 6% | −10.3 pts |
| Black / African American | 13.6% | 8–10% | −4–6 pts (varies by disease area) |
| Asian American | 6.3% | 3–5% | −1–3 pts |
| Women | 51% | ~48% overall (lower in cardiology, CNS) | −2–8 pts depending on indication |
| Adults 65+ | 17% | ~15% (less in oncology) | Moderate; severe in some oncology subtypes |
Sources: Lancet Regional Health – Americas (2022); FDA Drug Trials Snapshots (FY 2015–2023); HHS OIG (2024). Population figures from U.S. Census Bureau.
The Latino gap is the largest and most consistent across disease areas—and the hardest for most sites to close because it requires bilingual staff, community partnerships with Spanish-speaking health organizations, and translated consent materials. Black enrollment gaps are smaller on average but become critical in specific therapeutic areas where disease burden is highest.
Diversity benchmarks by therapeutic area
The national gap data is useful context, but sponsors drafting DAPs for a specific indication need therapeutic-area-specific benchmarks. Here's where each major disease area stands—and what DAP targets are likely to look like based on disease burden data.
| Therapeutic Area | Current Black Enrollment | Disease Burden (Black pop.) | Current Latino Enrollment | Disease Burden (Latino pop.) | Expected DAP Gap Pressure |
|---|---|---|---|---|---|
| Nephrology / Renal Disease | ~9% | 33% of CKD patients | ~7% | ~15% of CKD patients | Critical — largest documented Black gap in any disease area |
| Cardiovascular / Cardiology | ~11–14% | ~20% of CVD mortality | ~7% | ~18% of HF hospitalizations | Critical — both Black and Latino gaps significant |
| Oncology (solid tumors) | ~9–12% | Higher mortality in breast, colorectal, prostate cancers | ~5% | ~16% of U.S. pop.; rising incidence | High — Latino gap especially severe; breast/prostate urgency |
| Diabetes / Metabolic | ~10–12% | Type 2 DM prevalence ~60% higher vs. white Americans | ~6% | Highest prevalence rate of any group (~12.5%) | High — Latino underrepresentation is acute in this area |
| CNS / Neurology (Alzheimer's) | ~5–8% | ~2× higher Alzheimer's risk vs. white Americans | ~4–5% | ~1.5× higher Alzheimer's risk | High — historically among whitest disease areas; fast-growing DAP scrutiny |
| Infectious Disease (HIV/AIDS) | ~40–42% | ~40% of new HIV diagnoses | ~25% | ~26% of new HIV diagnoses | Moderate — enrollment roughly tracks disease burden; gaps remain in prevention trials |
| Vaccines / Infectious Disease | ~3–8% | COVID: 21% of deaths; disproportionate burden across diseases | ~5–8% | Similar COVID death disparity | Critical — COVID trials exposed systemic failure; FDA now closely watches vaccine trials |
| Rare Disease | ~8–12% | Varies widely; sickle cell disease: 95%+ Black | ~5–7% | Some rare diseases higher in Hispanic populations | Moderate for most — but disease-specific gaps can be extreme (e.g., sickle cell, lupus) |
Sources: FDA Drug Trials Snapshots Annual Summary (2023); Lancet Regional Health (2022); Mintz LLP FDORA analysis (2024); NIH National Institute on Minority Health and Health Disparities; HHS OIG (2024). Disease burden figures from CDC and published epidemiology literature.
The nephrology/renal disease gap is the single most scrutinized data point in FDORA discussions. Black Americans are 33% of chronic kidney disease patients but only ~9% of trial participants. Sponsors running Phase 3 renal trials face intense FDA pressure to justify any DAP targets that don't approach disease burden parity. Sites in markets with significant Black populations that can't demonstrate renal trial diversity history are at immediate risk of deselection.
What top-performing sites actually achieve
Benchmarks are most useful when you can see not just where the industry currently stands, but where it's possible to get. The difference between average enrollment data and what top-performing sites achieve tells you what's actually achievable when a site has the right infrastructure in place.
Data from sites with structured diversity recruitment programs—dedicated community health navigators, bilingual coordinators, FQHC partnerships, and active outreach to underserved populations—consistently shows enrollment profiles that are 2–3 times more diverse than the national average for the same indication.
| Therapeutic Area | Industry Average Black Enrollment | Top-Site Black Enrollment | Industry Average Latino Enrollment | Top-Site Latino Enrollment |
|---|---|---|---|---|
| Oncology | 9–12% | 18–22% | 5% | 12–16% |
| Cardiology | 11–14% | 20–28% | 7% | 15–20% |
| Nephrology | 9% | 22–30% | 7% | 14–18% |
| CNS / Neurology | 5–8% | 14–18% | 4–5% | 10–14% |
| Diabetes / Metabolic | 10–12% | 18–24% | 6% | 18–25% |
Top-site figures represent sites with documented structured diversity recruitment programs including dedicated community health navigators, bilingual staff, FQHC partnerships, and active community outreach. Ranges vary by geographic catchment area. Sources: Published literature on community-based recruitment programs; NIH clinical trial network performance data.
The gap between industry average and top-site performance isn't driven by catchment area demographics alone. Urban sites with similar patient populations produce dramatically different enrollment outcomes based on whether they have intentional diversity infrastructure. The difference between 9% and 25% Black enrollment in a nephrology trial at two comparable urban sites almost always comes down to community relationships, bilingual staff, and proactive screening practices—not the available patient pool.
How to read these benchmarks for your site
There are three questions worth working through when you read this data for your specific situation:
1. Which therapeutic areas do you run, and where are the DAP pressure points?
If your site specializes in nephrology and cardiology, your Black enrollment data is going to be scrutinized heavily. If you run primarily oncology and CNS, Latino enrollment gaps are the priority concern. Match the tables above to your actual trial portfolio and identify your highest-risk gaps.
2. What's your current enrollment profile against these benchmarks?
Most sites have this data in their EDCs but have never aggregated it. Pull your last three years of completed trials and calculate your actual race/ethnicity enrollment by indication. Where do you land relative to the industry average column? Relative to the top-site column? That gap is your competitive disadvantage in sponsor site-selection conversations under FDORA.
3. What would it take to move from industry average to top-site performance?
The top-site figures aren't achievable overnight, but they are achievable within 12–18 months for most sites with the right infrastructure. The components that drive top-site performance—bilingual coordinators, community partnerships, flexible scheduling, transportation assistance, proactive screening—are operational investments, not impossible moonshots.
Sites in markets with lower minority population density will have a narrower achievable range, particularly for specific demographic groups. A rural Midwest site running cardiology trials cannot reasonably hit 25% Black enrollment regardless of infrastructure. The benchmark comparison that matters for your site is against other sites in similar markets—not against national averages for urban research centers. If you're unsure how your market affects your realistic targets, the FDORA guide includes a catchment area assessment framework.
Using benchmarks to win sponsor partnerships
The practical application of all this data is in sponsor conversations. Sponsors drafting DAPs for Phase 3 trials need to know, before they sign with a site: Can this site actually hit a 20% Black enrollment target for our cardiology study? Sites that can answer that question with data win the contract. Sites that can't are deprioritized.
Here's how to use these benchmarks in practice:
Before a site qualification visit, prepare a one-page summary of your enrollment demographics by therapeutic area over the past three years. Lay it next to the industry averages in this article. Where you beat the average is a talking point. Where you're below it is a gap you should address proactively—with a documented plan for how you'll close it—rather than leaving sponsors to discover it themselves.
When a sponsor asks about your diversity capabilities, cite your own data first. Then reference disease burden benchmarks to show you understand what the DAP goals are targeting. Sponsors are more likely to select sites that speak the same DAP language they're using in their FDA submissions.
If your data is weak, don't try to obscure it. Sponsors will check. Instead, lead with your improvement plan: community partnerships you're building, bilingual staff you've hired, screening protocols you've changed. A credible improvement narrative is better than silence—and it opens the door to a future partnership even if you lose a near-term trial.
Sites that started building diversity infrastructure in 2024 already have 18 months of performance data to show sponsors. Every quarter you wait, that competitive gap widens. FDORA has made diversity enrollment a permanent feature of site evaluation—not a temporary compliance exercise. The time to act is now, not when the next RFP lands.
The benchmarks in this article are a starting point—a way to understand where you stand relative to the industry and what's achievable. Closing the gaps requires operational investment: community relationships, bilingual outreach, tracking infrastructure, and documented protocols. For sites that want to move faster than organic development allows, specialized diversity recruitment partners can provide that infrastructure without requiring your team to build it from scratch.
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