Research landscape of precision medicine in cardiology

Abstract

Precision medicine in cardiology integrates genomic, proteomic, and phenotypic data to tailor prevention, diagnosis, and treatment strategies for individual patients. Recent advances have identified genetic variants associated with arrhythmias, cardiomyopathies, and coronary artery disease, enabling risk stratification and targeted therapies. High-throughput "omics" technologies and machine-learning algorithms have facilitated the discovery of novel biomarkers and have refined phenotypic subgroups within heterogeneous cardiac disorders. Pharmacogenomic profiling has demonstrated potential to optimize drug selection and dosing, reducing adverse events and improving therapeutic efficacy. Despite these breakthroughs, challenges such as data integration, clinical implementation barriers, and ethical considerations remain. Ongoing efforts in large-scale consortia, real-world data registries, and adaptive clinical trial designs are expanding the evidence base. This review synthesizes the current research landscape, highlights emerging technologies, and discusses future directions for personalized cardiovascular care.

Keywords: Precision cardiology; biomarkers; cardiovascular phenotyping; genomic medicine; machine learning; personalized therapy; pharmacogenomics.