# Pharmacogenomics in the prediction of adverse effects of cardiovascular drugs: the PGx-CardioDrug project

## TL;DR

This paper introduces a project exploring how genetic factors influence adverse reactions to cardiovascular drugs, aiming to improve personalized treatment.

## Contribution

The PGx-CardioDrug project evaluates pharmacogenes and drug interactions to predict adverse drug reactions in real-life patient scenarios.

## Key findings

- The project focuses on three major classes of cardiovascular drugs and their associated adverse reactions.
- It uses a case-control design to assess genetic and drug interactions in a real-world patient population.
- The study aims to develop better methods for predicting drug-gene interactions in patients with comorbidities.

## Abstract

Although the role of pharmacogenomics (PGx) in personalized pharmacotherapy has been well established, its implementation in clinical practice lags behind. In this article, we present an overview of important achievements in the field of PGx of cardiovascular drugs (CVDs), and identify gaps in the existing research. We also present an outline of the PGx-CardioDrug project (ClinicalTrials.gov: NCT05307718) focused on PGx of three major classes of CVDs: P2Y12 antiplatelets, direct oral anticoagulants (DOACs), and statins. The project intends to evaluate pharmacogenes, concomitant treatments, and their combinations as determinants of adverse drug reactions (ADRs). It is based on a pool of around 1200 consecutive adults who were accrued on the case-control principle defined with respect to the CVDs and ADRs of interest (bleeding related to antiplatelets and DOACs, skeletal muscle or liver toxicity related to statins, inefficiency). Possible perpetrator or victim roles of concomitantly used drugs are assessed using the Lexicomp® Clinical Decision Support System. The assembled data provide a basis for a series of case-control type analyses. Considering the mode of data generation and the nature of the exposures of interest (ie, present before the occurrence of the outcome), potentially observed outcome-exposure associations are likely to be causal, provided that confounding is reasonably controlled. The project enables the development of methods and procedures that better reflect the real-life situation of patients with comorbidities and polytherapy, and might better predict the interactions of multiple drugs and genes that affect the frequency and severity of CVD ADRs.