Key result
Integrating AI and multi-omics enables early cardiotoxic risk detection and optimizes personalized cardiovascular therapies.
Why the study?
This review explores the potential of precision medicine, multi-omics, and artificial intelligence to overcome cardiotoxicity and adverse drug reactions associated with conventional cardiovascular disease treatments.
Design
Review
May minimize cardiotoxicity in personalized CV therapies; extends AI-multi-omics precision medicine but requires prospective validation.
Precision medicine refers to tailoring therapeutic interventions to an individual’s genetic, molecular and phenotypic characteristics, while multi-omics integrates genomics, proteomics and metabolomics data to provide a systems-level view of disease. Together with artificial intelligence (AI) driven predictive modeling, these approaches enable early identification of cardiotoxic risk and optimization of drug therapy in cardiovascular diseases. The present review explores the possibility of precision medicine to overcome cardiotoxicity associated with conventional cardiovascular disease (CVD) treatments. It highlights the integration of biomarker-driven therapies, pharmacogenomics, and multi-omics technologies to improve therapeutic efficacy and minimize the risk of adverse drug reactions. Additionally, the review assesses the emerging contributions of artificial intelligence (AI) and network medicine in improving cardiovascular diagnostics and developing personalized treatment regimens. The discovery of genomics, proteomics, metabolomics into cardiovascular research has significantly increased our understanding in disease etiology and variability in response of drug. Furthermore, AI-driven predictive models and machine learning algorithms play key role in minimizing clinical risk and support precision-guided decision, ultimately enhance patient outcomes. The advancement in omics technology, AI and customized therapy is expected to revolutionize cardiovascular care, despite current challenges in clinical implementation. The integration of cutting-edge approaches into standard clinical practice would maximize treatment effectiveness and guarantee patient safety.
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Pathak et al. (2026) studied this question. Integrating artificial intelligence and multi-omics enables early identification of cardiotoxic risk and optimizes personalized cardiovascular drug therapies to improve patient safety.
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