# Development of Integrated Precision Medicine Models in Adults with Cardiovascular Disease

> **NIH NIH R03** · UNIVERSITY OF FLORIDA · 2024 · $114,375

## Abstract

PROJECT SUMMARY
This application aims to use existing data within the All of Us Researcher Workbench to improve our ability to
identify cardiovascular disease (CVD) patients treated with statins or antiplatelet therapy (i.e. P2Y12 inhibitors)
at increased risk for adverse drug responses and adverse outcomes. In order to manage CVD and prevent
adverse outcomes, CVD patients can be treated with multiple medications including lipid-lowering agents or
statins and antiplatelet agents such as clopidogrel. There are well known clinical and genetic factors that
impact the risk of statin-associated musculoskeletal symptoms (SAMS) with numerous statins and the risk of
adverse cardiovascular outcomes with the P2Y12 inhibitor clopidogrel. Despite guidance from expert consensus
groups, and regulatory agencies, the implementation of pharmacogenetic testing for statins, and P2Y12
inhibitors has been limited, occurring mostly at large, academic medical centers. Additionally, almost all of the
studies conducted to date have been in populations of largely European and Asian ancestry. In order to
provide equitable care and fulfill precision medicine for the over 53 million Americans estimated to be treated
with statins or P2Y12 inhibitors annually, we need to better understand their usage and associated outcomes in
diverse, real-world populations. Our central hypothesis is that precision medicine models derived from diverse,
real-world data for SAMS, and adverse outcomes after treatment with an antiplatelet agent, will be more
precise and accurate than existing models To test our central hypothesis we will complete the following
Specific Aims: 1) Evaluate statin prescribing patterns, adverse drug responses, and adverse outcomes in
patients with CVD by SLCO1B1, ABCG2, and CYP2C9 genotypes using electronic-health record (EHR)-based
data, genomic data, and data from surveys and wearables, and 2) Characterize antiplatelet prescribing
patterns, adverse drug responses, and adverse outcomes in patients with CVD by CYP2C19 genotype using
EHR-based data, genomic data, and data from surveys and wearables. To achieve these aims, we will utilize
existing data from the All of Us Researcher Workbench. The All of Us Research Program is enrolling a diverse
group of persons in the United States, and including multiple types of real-world data (e.g. EHR, demographic,
wearables, patient surveys, genomic). We will deploy validated CVD algorithms and determine observed rates
of CVD, statin prescribing, and antiplatelet prescribing. We will identify characteristics of SAMS in patients with
CVD treated with statins and characteristics of adverse outcomes in patients with CVD treated with a P2Y12
inhibitor. We will also use multivariable regression analyses and machine-learning methods to model adverse
drug responses and adverse cardiovascular outcomes. We will examine characteristics and models of CVD
patients treated with statins by SLCO1B1, ABCG2, and CYP2C9 genotypes, and of CVD patie...

## Key facts

- **NIH application ID:** 10864524
- **Project number:** 1R03HL172987-01
- **Recipient organization:** UNIVERSITY OF FLORIDA
- **Principal Investigator:** Caitrin W McDonough
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $114,375
- **Award type:** 1
- **Project period:** 2024-07-15 → 2026-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10864524

## Citation

> US National Institutes of Health, RePORTER application 10864524, Development of Integrated Precision Medicine Models in Adults with Cardiovascular Disease (1R03HL172987-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10864524. Licensed CC0.

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