Population-Aware Medicine: Mitigating Racial Disparities In Efficacy And Accuracy

By Bill Hanlon, Ph.D., executive advisor

The concept of "population-aware medicine" underscores the imperative of designing therapeutics and diagnostics with ancestral diversity at the forefront. Mitigating racial disparities requires acknowledging that one-size-fits-all approaches can inadvertently harm underrepresented groups and undermine clinical validity. By integrating population‑specific genetic insights and accounting for systemic biases, healthcare stakeholders can ensure more equitable efficacy and accuracy.

Racial and ethnic diversity shapes molecular drug interactions and the safety and efficacy of medications across ancestrally diverse populations. It is critical to distinguish between self‑identified race, a social construct reflecting cultural, historical, and socioeconomic contexts, and genetic ancestry, which refers to the proportionate heritage from ancestral populations inferred through genomic markers. Both self‑identified race and genetic ancestry are important in understanding health outcomes. Self‑identified race reflects structural and environmental influences that shape access and risk. Genetic ancestry provides a biologically-grounded view of allele frequencies and pharmacogenomic variation that can guide precision prescribing. Integrating both perspectives enables a nuanced understanding of disparities, ensuring that interventions address both biological and social determinants of health.

Prior publications have explored pharmacogenomic variation by race and ethnicity, ¹ racial bias in diagnostic technologies, ² and algorithmic inequity in care allocation.³ These challenges, however, have often been addressed in isolation. This article integrates therapeutic, diagnostic, systemic, and regulatory insights into a unified framework for population‑aware medicine. The following case studies illustrate why anchoring research and development, validation, and reimbursement to population diversity has become an imperative.

Genetic Drivers Of Drug Response

Subtle genetic differences can determine whether a medicine is effective or harmful. Many of these variations cluster along ancestral lines, creating distinct benefit–risk profiles that remain invisible when trials enroll mostly white participants.

Clopidogrel and CYP2C19. Among 17,000 coronary stent recipients, carriers of CYP2C19 *2/*3 alleles, which are more common in some Asian and African populations, experienced 1.5 times more stent thromboses. Other analyses limited to Black patients reported a twofold disparity. ^4–6 Hospitals that now genotype before prescribing report fewer adverse cardiac events and shorter inpatient stays.

CYP2D6 polymorphisms. Roughly 20% of individuals with African ancestry carry loss‑of‑function CYP2D6 variants. Observational studies link these genotypes to 30% higher rates of risperidone‑related side effects and to unpredictable codeine metabolism, ranging from therapeutic failure to life‑threatening respiratory depression.^7, 8

HLA‑B15:02.* A single allele prevalent in Southeast Asia raises the risk of carbamazepine‑induced Stevens‑Johnson syndrome twelve‑fold.⁹ Singapore and Taiwan have adopted mandatory screening, and several U.S. health systems are moving in the same direction.

G6PD deficiency. In parts of sub‑Saharan Africa and the Eastern Mediterranean, up to one in five males lack functional glucose‑6‑phosphate dehydrogenase. Standard‑dose rasburicase can precipitate hemolysis and severe anemia in more than 25% of affected individuals.¹⁰

SLCO1B15.* Present in about 15% of Europeans, this variant reduces hepatic uptake of simvastatin, quadrupling plasma levels and quintupling myopathy risk.¹¹ A prospective genotyping study showed that dose adjustment or drug substitution nearly eliminated creatine‑kinase elevations.

The above examples underscore the necessity of integrating pharmacogenomic screening into both clinical trials and routine care, particularly for ancestrally diverse populations historically underrepresented in biomedical research. By aligning drug development and prescribing practices with genetic insights, healthcare systems can reduce ineffective treatments and adverse events, improve therapeutic efficacy, and advance equitable treatment outcomes across racial and ethnic groups.

Diagnostic Accuracy And Bias

Diagnostic tools and laboratory reference thresholds are often calibrated using homogenous populations, at times leading to inaccuracies and misclassifications when applied across diverse racial and ethnic groups. When laboratory values or algorithms perform unevenly across populations, the resulting misdiagnoses ripple through the entire care pathway.

Hemoglobin reference ranges. The conventional European-derived lower limit of 12 g/dL designates 12% to 15% of African‑American women as anemic, even when iron stores and erythropoietic indices are normal. ¹² Establishing ancestry‑specific reference intervals reduces unnecessary iron panels, colonoscopies, and bone marrow biopsies.

Pulse oximetry. Bench and clinical evaluations reveal a systematic 2.8‑point over‑read in individuals with darker skin pigmentation. ^13, 14 During the COVID‑19 pandemic, this bias delayed antiviral therapy and intensive care transfer for Black and Hispanic patients. Manufacturers now submit multi‑ethnic performance data with new sensor designs, and the FDA is reassessing clearance standards.

Spirometry. Shifting from white-derived to race‑neutral lung function equations reclassified 39% of Black children from “normal” to “impaired,” prompting earlier assessment for asthma and airway disease.^15, 16

Risk models and artificial intelligence. The original Gail model understates breast cancer risk by about one‑third in African‑American women, ¹⁷ while several commercial dermatology algorithms detect 20% to 30% fewer melanomas on Fitzpatrick skin types V and VI.¹⁸ Research groups increasingly publish subgroup‑specific metrics alongside overall accuracy.

These diagnostic disparities reflect systemic calibration gaps that can influence clinical decision-making from initial assessment to treatment selection, especially in underrepresented populations. Addressing them requires intentional recalibration of tools, reference standards, and algorithms to reflect the full spectrum of human biology.

Systems And Market Access

Clinical insight alone does not guarantee patient benefit. Coverage for CYP2C19 genotyping is available from only about 30%of U.S. private payers,¹⁹ and Medicare reimbursement remains inconsistent across regional contractors. Rural communities often have no local collection site, so prescriptions lapse even when physicians order the test. Meanwhile, an electronic health record algorithm used by more than 200 hospitals underestimated chronic kidney disease severity by 25% in Black patients, delaying nephrology referrals and transplant evaluations³; additional analyses found that the same tool overestimated glomerular filtration rate in many Hispanic patients, creating a parallel access gap.

Implementation studies suggest that combining mobile phlebotomy, sample‑pickup courier networks, telehealth genetic counseling, and community outreach can double biomarker testing in underserved ZIP codes within a year. Early adopters such as the Veterans Health Administration and several large integrated delivery networks have tied pharmacogenomic prompts to computerized order sets; within six months they recorded 40% higher test completion rates and a measurable drop in adverse drug reactions.^{20, 21} These examples illustrate that logistical innovation, clinician decision support, and payer alignment are just as crucial to equitable medicine as laboratory precision.

Regulatory Traction

In June 2024, building on industry feedback to an earlier version of the guidance, the FDA released an updated draft Diversity Action Plan that proposes requiring investigational new drug applications and biologics license applications to include race-based enrollment targets, predefined subgroup efficacy and safety analyses, and early consultation with the Office of Minority Health.²² While the finalized guidance was originally anticipated in late 2025, recent administrative changes have introduced additional review and commentary, leaving the final implementation timeline uncertain.

Statutory levers are tightening as well. Under the Food and Drug Omnibus Reform Act, the FDA can impose post‑approval commitments when subgroup evidence remains insufficient; a March 2025 Federal Register notice clarifies that accelerated approval applications must now provide a quantitative diversity gap analysis. Revised Office of Management and Budget Directive 15 categories will sharpen analytics by further disaggregating broad racial labels, enabling more precise pharmacovigilance.²³

However, the evolving regulatory environment is not without complexity. Recent federal actions have rolled back certain diversity, equity, and inclusion (DEI) initiatives, creating uncertainty for organizations navigating how best to comply while advancing equitable care. Stakeholders must remain agile, aligning with existing FDA and OMB directives while adapting to policy changes that may reshape the landscape of inclusive healthcare innovation.

Conclusion

Population-aware medicine demands a paradigm shift: recognizing ancestral diversity not as a compliance checkbox but as a foundational element of therapeutic design, diagnostic development, and healthcare delivery. The evidence presented herein, ranging from CYP2C19 and CYP2D6 polymorphisms to pulse oximetry calibration disparities, emphasizes that without deliberate inclusion of diverse populations, innovations risk serving only a subset of patients, perpetuating inequities and eroding clinical validity.

Embracing population-aware medicine means:

• Designing Inclusive Trials: Embedding genotype stratification and diversity targets ensures that trial outcomes accurately predict efficacy and safety across the U.S. demographic spectrum.
• Calibrating Diagnostics for All: Developing and validating lab assays and medical devices against multi-ethnic cohorts safeguards against misdiagnosis and guides equitable clinical decisions.
• Addressing Systemic Barriers: Expanding access to genetic testing, auditing algorithms for bias, and aligning reimbursement policies dismantles structural obstacles that disproportionately affect underrepresented groups.
• Aligning Regulatory and Payer Frameworks: Proactively engaging with FDA diversity mandates, OMB data standards, and payer coding reforms integrates equity into the commercial pathway from bench to bedside.

By operationalizing these principles, stakeholders can evolve from conventional and early-stage precision medicine toward population-aware medicine, enabling a healthcare system where treatments and diagnostics are effective and reliable for people of all backgrounds.

References:

1. Bonham VL, Green ED, Pérez‑Stable EJ. Examining How Race, Ethnicity, and Ancestry Data Are Used in Biomedical Research. JAMA 2018.
2. Sjoding MW et al. Origins of Racial and Ethnic Bias in Pulmonary Technologies. Annual Review of Medicine 2023.
3. Obermeyer Z et al. Dissecting Racial Bias in an Algorithm Used to Manage the Health of Populations. Science 2019.
4. Cavallari LH et al. CYP2C19 Genotype and Clopidogrel Response. JACC Advances 2023.
5. Scott SA et al. Clinical Pharmacogenetics Implementation Consortium Guideline for CYP2C19 and Clopidogrel Therapy. Clinical Pharmacology & Therapeutics 2022.
6. Tunehag KR et al. CYP2C19 Genotype and Outcomes in Black Patients Undergoing PCI. Journal of the American Heart Association 2024.
7. Oni‑Orisan A et al. CYP2D6 Polymorphisms and Risperidone Adverse Effects. UCSF Pharmacogenomics Program.
8. Crews KR et al. Clinical Pharmacogenetics Implementation Consortium Guideline for CYP2D6 and Codeine Therapy. Clinical Pharmacology & Therapeutics 2014.
9. Tangamornsuksan W et al. HLA‑B1502 and Carbamazepine‑Induced Stevens‑Johnson Syndrome.* JAMA Dermatology 2013.
10. Nkhoma ET et al. Global Prevalence of G6PD Deficiency. Blood Cells, Molecules, and Diseases 2009.
11. Link E et al. SLCO1B1 Variants and Statin‑Induced Myopathy. New England Journal of Medicine 2008.
12. Beutler E, West C. Hematologic Differences Between African‑Americans and Whites. Blood 2005.
13. Singh S et al. Skin Pigmentation and Pulse Oximetry Accuracy. Journal of Medical Internet Research 2024.
14. Fawzy A et al. Racial Differences in Oxygen Supplementation During COVID‑19. JAMA Internal Medicine 2022.
15. Adegunsoye A et al. Race‑Specific Equations in Lung‑Function Testing. American Journal of Respiratory and Critical Care Medicine 2024.
16. Chang WC et al. Race‑Neutral Spirometry in Black Children. JAMA Network Open 2025.
17. Gail MH et al. Breast‑Cancer Risk Prediction for African‑American Women. Journal of the National Cancer Institute 2007.
18. Daneshjou R et al. Dermatology AI Performance on Diverse Skin Types. JAMA Dermatology 2022.
19. Personalized Medicine Coalition. Genomic Testing Utilization and Coverage. Washington, DC; 2020.
20. Danilowicz S et al. Reimbursement Practices for Genetic Testing. NPJ Genomic Medicine 2023.
21. Shriver SP et al. Equitable Pharmacogenomic Testing in Oncology. Journal of Clinical Oncology 2024.
22. U.S. Food and Drug Administration. Diversity Action Plans to Improve Enrollment of Participants From Under‑represented Populations in Clinical Trials. Draft Guidance 2024.
23. Office of Management and Budget. Revisions to Statistical Policy Directive No. 15: Standards for Maintaining, Collecting, and Presenting Federal Data on Race and Ethnicity. 2024.
24. European Medicines Agency. Reflection Paper on the Use of Population Sensitivity Analyses in the Evaluation of Medicines. 2024.

Acknowledgements:

The author thanks Elizabeth George, head, patient diversity, Labcorp, for her critical review and constructive suggestions during the drafting of this article.

About The Author:

Bill Hanlon, Ph.D., is an executive advisor and former Labcorp SVP who has built data‑driven businesses where drug development and real‑world evidence converge. Over 30 years in pharma and clinical CRO leadership, he has unified global teams, steered $3 billion P&Ls, and launched a RWD strategy platform that enables clinical trials and access to de-identified lab data. Hanlon now guides investors and biopharma innovators on the utility of RWD in drug development and healthcare, M&A strategy, and regulatory engagement. He also served on advisory boards for Circuit Clinical, Prognos Health, and BioSpectal, and has been a member of the Board of Trustees of the Institute of Life Science Entrepreneurship of NJ (ILSE) for 10 years.