Establishing a Verified Principal Investigator Pipeline for Middle Eastern, North African, and South Asian Physicians

A Scientific Strategy to Improve Clinical Trial Validity, Safety Inference, and Population Representativeness

5 minutes read

By Professor Hadi Danawi is a global public health leader, clinical research strategist, and founder of the MENASA Group, a U.S.-based nonprofit advancing the representation and participation of Middle Eastern, North African, and South Asian (MENASA) populations in clinical research and healthcare innovation

The scientific limitations created by non-representative clinical trial samples are well described: biased estimates of benefit–risk profiles, reduced external validity, and constrained subgroup inference. These limitations are amplified when population categories are imprecise or misclassified. Historically, Middle Eastern and North African populations were often tabulated within the “White” category in federal standards, reducing the capacity to monitor representation and outcomes with adequate granularity. The 2024 revision to Statistical Policy Directive No. 15 adds “Middle Eastern or North African” as a minimum reporting category and updates federal standards for collecting and presenting race and ethnicity data (Office of Management and Budget, 2024b). (Federal Register)

In parallel, regulators have signaled increasing expectations for prospective diversity planning. The Food and Drug Administration’s draft guidance on Diversity Action Plans and “Enhancing Participation in Clinical Trials-Guidance for Industry” describes the structure, timing, and submission expectations for plans designed to improve enrollment of underrepresented populations in clinical studies (U.S. Food and Drug Administration, 2024; U.S. Food and Drug Administration, 2025). (U.S. Food and Drug Administration) While Diversity Action Plans are commonly framed as an enrollment strategy, enrollment is downstream of investigator readiness and site capability. Therefore, improving representation for MENASA populations requires a workforce and infrastructure approach that makes community-embedded, quality-ready investigators available to sponsors and health systems.

This paper proposes a scientific framework for onboarding MENASA physicians into regulated research as verified Principal Investigators, where verification is defined not as branding but as competency-based readiness with measurable performance indicators.

Policy and Data Standards Context: Why Classification Quality Changes Science

– Statistical Policy Directive No. 15 revision (2024)

The revision introduces a distinct minimum reporting category for “Middle Eastern or North African,” addressing measurement limitations created by prior categorization (Office of Management and Budget, 2024b). (Federal Register) From a methodological perspective, improved classification reduces misclassification bias in demographic variables used for:

representation monitoring and enrollment benchmarking,
pre-specified subgroup analyses and stratification plans, and
post-market safety surveillance and stratification of real-world evidence.

– Food and Drug Administration Diversity Action Plans

The draft guidance and its associated Federal Register notice describe the form and content of Diversity Action Plans, the process and timing for submission, and the criteria and processes for evaluating waiver requests (U.S. Food and Drug Administration, 2024; U.S. Food and Drug Administration, 2025). (U.S. Food and Drug Administration) Regardless of final guidance details, the direction is clear: diversity is shifting from a retrospective discussion to a prospective, documented operational deliverable.

The Scientific Rationale for a Verified Principal Investigator Pipeline

Principal Investigators are central to protocol execution, participant protection, and data integrity. A verified MENASA Principal Investigator pipeline is justified because it can plausibly improve:

– External validity (generalizability)

When MENASA populations are missing, misclassified, or under-sampled, the transportability of treatment effects and safety signals to real-world clinical settings serving these communities is weakened.

– Subgroup inference and safety signal detection

Adequate sample sizes and accurate classification are prerequisites for meaningful subgroup analyses. Improved representation increases statistical power to detect heterogeneity and clinically relevant differences in adverse events.

– Recruitment feasibility and retention

Community-embedded physicians may reduce language, cultural, and trust barriers that drive low enrollment and early discontinuation, improving completeness of longitudinal endpoints.

– Data integrity and audit readiness

A structured pipeline that trains and assesses investigators against Good Clinical Practice expectations can improve protocol compliance, documentation quality, and deviation management.

Defining “Verified Principal Investigator” Scientifically

To remain scientifically defensible, verification should be competency-based, auditable, and tied to measurable indicators.

– Core competency domains

Good Clinical Practice competence (delegation, documentation, safety reporting, protocol adherence)
Human subject protections and ethics (informed consent quality, privacy, Institutional Review Board compliance)
Operational readiness (feasibility assessment, staffing, workflow design, budgeting literacy)
Quality management systems (deviation management, corrective and preventive action processes, monitoring readiness)
Diversity execution capability (evidence-based recruitment and retention plans for underrepresented communities)

– Example verification metrics (illustrative, non-exhaustive)

Screening-to-enrollment conversion and time-to-enrollment
Visit adherence and retention rates
Protocol deviation counts and severity distribution
Query rates, time-to-query resolution, and source data completeness
Participant experience or satisfaction indicators (where ethically and methodologically appropriate)
Monitoring/audit outcomes (when available)

Verification should be periodic and responsive to protocol complexity and therapeutic area.

South Asian Over-Aggregation: A Methodological Concern

South Asian populations are frequently grouped within broad “Asian” categories, obscuring heterogeneity in baseline risk, exposures, genetics, and social determinants. The scientific issue is inferential fidelity: over-aggregation can mask clinically meaningful differences and weaken the interpretability of benefit–risk profiles for specific populations.

Implementation Framework: A Systems Approach

A verified MENASA Principal Investigator pipeline can be operationalized as a four-stage systems model:

Identification and onboarding: mapping clinicians serving MENASA communities; baseline readiness assessment.
Competency development: standardized training in trial operations, ethics, and quality management.
Verification: competency assessment, simulated monitoring/audit exercises, and performance thresholds.
Sustainment: continuous quality improvement, retraining triggers, and performance monitoring.

This approach explicitly connects policy and guidance (classification standards and Diversity Action Plans) to measurable scientific outputs: improved representation, stronger evidence, and higher quality execution.

Limitations and Risks

Verification heterogeneity: without common standards, verification may vary in meaning and become non-comparable across institutions.
Data access constraints: Some performance indicators (e.g., audit findings) may not be available or may not be shareable.
Workforce burden: training and quality systems require time and resources; programs must avoid shifting cost burdens onto clinicians without institutional support.
Equity risks: verification must be accessible and not create structural exclusion for resource-limited settings; tiered supports may be needed.

Conclusion

Revisions to federal race and ethnicity standards and evolving expectations for prospective diversity planning create a timely opportunity to improve the scientific quality of clinical research for Middle Eastern, North African, and South Asian populations (Office of Management and Budget, 2024b; U.S. Food and Drug Administration, 2025; U.S. Food and Drug Administration, 2024). (Federal Register) A competency-based, auditable pipeline that onboards MENASA physicians as verified Principal Investigators offers a systems-level approach to strengthen external validity, subgroup safety inference, and operational execution—producing evidence that better reflects the populations affected by disease and treated in practice.

References (APA 7th; alphabetical)
Office of Management and Budget. (2024, March 28). OMB publishes revisions to Statistical Policy Directive No. 15: Standards for maintaining, collecting, and presenting Federal data on race and ethnicity. The White House (Archived). https://bidenwhitehouse.archives.gov/omb/briefing-room/2024/03/28/omb-publishes-revisions-to-statistical-policy-directive-no-15-standards-for-maintaining-collecting-and-presenting-federal-data-on-race-and-ethnicity/

Office of Management and Budget. (2024, March 29). Revisions to OMB’s Statistical Policy Directive No. 15: Standards for maintaining, collecting, and presenting Federal data on race and ethnicity. Federal Register, 89, 22182–22196. https://www.federalregister.gov/documents/2024/03/29/2024-06469/revisions-to-ombs-statistical-policy-directive-no-15-standards-for-maintaining-collecting-and

U.S. Food and Drug Administration. (2024, June 28). Diversity action plans to improve enrollment of participants from underrepresented populations in clinical studies; draft guidance for industry; availability. Federal Register, 89, 54010–54012. https://www.federalregister.gov/documents/2024/06/28/2024-14284/diversity-action-plans-to-improve-enrollment-of-participants-from-underrepresented-populations-in

U.S. Food and Drug Administration. (2025, July 25). Diversity action plans to improve enrollment of participants from underrepresented populations in clinical studies (Draft guidance). https://www.fda.gov/regulatory-information/search-fda-guidance-documents/diversity-action-plans-improve-enrollment-participants-underrepresented-populations-clinical-studies

U.S. Food and Drug Administration. (2025, December). Enhancing participation in clinical trials—Eligibility criteria, enrollment practices, and trial designs: Guidance for industry. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/enhancing-participation-clinical-trials-eligibility-criteria-enrollment-practices-and-trial-designs

Professor Hadi Danawi

Professor Hadi Danawi is a global public health leader, clinical research strategist, and founder of the MENASA Group, a U.S.-based nonprofit advancing the representation and participation of Middle Eastern, North African, and South Asian (MENASA) populations in clinical research and healthcare innovation. With more than two decades of experience spanning academia, clinical trials, and health systems strategy, his work focuses on strengthening research infrastructure, advancing inclusive trial design, and translating evidence into equitable health outcomes.

Professor Danawi collaborates closely with hospitals, regulators, industry leaders, and physician networks across the United States and the MENASA region to elevate underrepresented voices, build sustainable clinical trial capacity, and support the development of population-relevant drug safety and efficacy data. Through global summits, education programs, and strategic partnerships with U.S. and global Health Authorities, he continues to champion a future in which MENASA nations and communities are active contributors to clinical research, health policy, and innovation worldwide.