Genetics of Drug-Drug Interactions (DDIs)

Published by Luke Morais on

Genetics of Drug-Drug Interactions (DDIs)

 

What are DDIs?

Drug-Drug Interactions (DDIs) occur when two or more drugs interact, altering how the body processes them or how they affect the body. These interactions can not only enhance or reduce the effects of the drugs but also lead to adverse effects. Additionally, DDIs can arise from interactions with food, drinks, and supplements. Symptoms of DDIs can range from mild to severe and may include:

  • Feeling more tired than usual
  • Memory loss or confusion
  • Fast heartbeat
  • Difficulty breathing
  • Changes in mood
  • Unusual bleeding or bruising

DDIs are more common among older adults and those on multiple medications, potentially leading to serious health issues like kidney damage, heart problems, and high blood pressure. Preventing drug interactions and their associated health problems is a significant focus for scientists.

 

How is the Research Done?

This study aims to explore the genetic underpinnings of adverse drug reactions (ADRs) of DDIs using BioVU resources. Researchers will compare patients who experienced adverse DDIs with those who did not, focusing on genetic differences that may predispose individuals to these interactions. The goal is to identify genetic variants linked to DDI-related health issues, such as cardiovascular and renal complications.

 

What is the Importance of this Study?

A significant number of patients possess actionable genotypes that can influence drug prescribing. Preemptive pharmacogenomic (PGx) testing can reduce clinically relevant interactions, especially in patients with polypharmacy. Using BioVU’s genetic data allows researchers to study these factors on a large scale, facilitating personalized medication management and minimizing adverse drug events. Understanding the genetic factors contributing to DDIs can help healthcare providers predict and prevent these interactions. This research underscores the importance of integrating genetic data into routine clinical practice, leading to more informed drug prescribing tailored to individual genetic profiles.

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