# Real-World Data Estimates of Racial Fairness with Pharmacogenomics-Guided Drug Policy

> **NIH NIH R21** · JOHNS HOPKINS UNIVERSITY · 2024 · $204,688

## Abstract

Project Summary
A pharmacogenomics-guided drug policy includes the genomic profile of an individual’s drug response with other
clinical characteristics (age, body weight, etc.) and may improve the safety and effectiveness of drug therapy.
Thus, in recent years several medical centers in the United States have implemented clinical pharmacogenomics
services to support such policies. Among the services that can be supported, preemptive clinical genotyping
services produce pharmacogenomic data before it is known that a particular drug may be needed by a patient.
Preemptive clinical genotyping services that cover genetic markers primarily based on populations of European
ancestry, however, can have reduced performance of a policy to identify well-tolerated medications in
understudied groups. Worse performance in the understudied groups is, in part, due to being more likely to have
an indeterminate drug response phenotype when compared to a European ancestry group. Having more
indeterminate drug response statuses in some racial subgroups translates in to more occurrences of “missing
data” in assessments of an individuals’ drug response, thus resulting in lower racial fairness. One possible
solution to this challenge of knowing if low racial fairness is a problem, is to estimate the pharmacogenomic-
guided drug policy performance and fairness for different racial subgroups a priori. The specific objective of
this project is to use All of Us research program (AoU) data to derive evidence of the potential unintended
consequence of low racial fairness that can exist with a new pharmacogenomic-guided drug policy. The
AoU data is uniquely suited to generate such evidence given that it includes a diversity of racial subgroups and
a variety of data types, including from electronic health records and clinical whole genome sequencing data. We
will conduct an observational cohort study using the AoU data to assess the performance of pharmacogenomics-
guided drug policies to identify well-tolerated medications (Aim 1), and quantify the potential impact of differential
data access among patients on performance (Aim 2). We will also study the impact of differential data access
on the racial fairness of pharmacogenomics-guided drug policy (Aim 3). Outcomes of this work will demonstrate
one strategy to produce evidence from real-world data that can be expanded upon and studied further in future
research. Presenting this type of evidence prior to approving pharmacogenomics-guided drug policy holds
promise to inform Pharmacy & Therapeutics committee decision-making.

## Key facts

- **NIH application ID:** 10934571
- **Project number:** 5R21MD019100-02
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** CASEY OVERBY TAYLOR
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $204,688
- **Award type:** 5
- **Project period:** 2023-09-25 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10934571

## Citation

> US National Institutes of Health, RePORTER application 10934571, Real-World Data Estimates of Racial Fairness with Pharmacogenomics-Guided Drug Policy (5R21MD019100-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10934571. Licensed CC0.

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