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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.
Abstract:
Cardiovascular disease remains a leading cause of both morbidity and mortality worldwide. It is widely accepted that both concomitant medications (drug-drug interactions, DDIs) and genomic factors (drug-gene interactions, DGIs) can influence cardiovascular drug-related efficacy and safety outcomes. Although thousands of DDI and DGI (aka pharmacogenomic) studies have been published to date, the literature on drug-drug-gene interactions (DDGIs, cumulative effects of DDIs and DGIs) remains scarce. Moreover, multimorbidity is common in cardiovascular disease patients and is often associated with polypharmacy, which increases the likelihood of clinically relevant drug-related interactions. These, in turn, can lead to reduced drug efficacy, medication-related harm (adverse drug reactions, longer hospitalizations, mortality) and increased healthcare costs. To examine the extent to which DDGIs and other interactions influence efficacy and safety outcomes in the field of cardiovascular medicine, we review current evidence in the field. We describe the different categories of DDIs and DGIs before illustrating how these two interact to produce DDGIs and other complex interactions. We provide examples of studies that have reported the prevalence of clinically relevant interactions and the most implicated cardiovascular medicines before outlining the challenges associated with dealing with these interactions in clinical practice. Finally, we provide recommendations on how to manage the challenges including but not limited to expanding the scope of drug information compendia, interaction databases and clinical implementation guidelines (to include clinically relevant DDGIs and other complex interactions) and work towards their harmonization; better use of electronic decision support tools; using big data and novel computational techniques; using clinically relevant endpoints, preemptive genotyping; ensuring ethnic diversity; and upskilling of clinicians in pharmacogenomics and personalized medicine.
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