Drug-Drug-Gene Interactions in Cardiovascular Medicine

Innocent G Asiimwe1, Munir Pirmohamed1

  • 1The Wolfson Centre for Personalized Medicine, MRC Centre for Drug Safety Science, Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.

Insights

Drug-drug-gene interactions (DDGIs) are understudied but crucial for cardiovascular medicine. Addressing these complex interactions is key to improving drug efficacy and patient safety in cardiovascular care.

Area of Science:

  • Pharmacogenomics
  • Cardiovascular Medicine
  • Drug Interaction Studies

Background:

  • Cardiovascular disease is a major global health burden, often requiring multiple medications.
  • Drug-drug interactions (DDIs) and drug-gene interactions (DGIs) impact cardiovascular drug outcomes.
  • Research on drug-drug-gene interactions (DDGIs) is limited, despite their potential clinical significance.

Purpose of the Study:

  • To review the current evidence on how DDGIs and other complex interactions affect cardiovascular drug efficacy and safety.
  • To highlight the prevalence and clinical relevance of these interactions in cardiovascular medicine.
  • To identify challenges and propose recommendations for managing these interactions.

Main Methods:

  • Literature review of existing studies on DDIs, DGIs, and DDGIs in cardiovascular medicine.
  • Categorization and illustration of how DDIs and DGIs combine to form DDGIs.
  • Analysis of reported prevalence, implicated drugs, and clinical challenges.

Main Results:

  • DDGIs and complex interactions are prevalent and can lead to reduced drug efficacy and increased harm.
  • Specific cardiovascular medications are frequently implicated in these interactions.
  • Clinical practice faces challenges in identifying and managing these multifaceted interactions.

Conclusions:

  • Managing DDGIs requires expanding drug information resources and clinical guidelines.
  • Enhanced use of decision support tools, big data, and computational techniques is recommended.
  • Preemptive genotyping, ethnic diversity in research, and clinician education are vital for personalized cardiovascular medicine.

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