"Biomarkers in Personalized Drug Therapy: Current Advances, Clinical Translation, Research Gaps, and Future Perspectives"

Personalized drug therapy aims to improve treatment efficacy and safety by considering individual genetic, molecular, physiological, and clinical characteristics. Biomarkers support patient stratification, treatment selection, dose optimization, response monitoring, and prediction of adverse drug reactions. This critical narrative review evaluates current advances, clinical applications, translational challenges, research gaps, and future perspectives related to biomarkers in personalized drug therapy. Pharmacogenomic biomarkers help explain interindividual differences in drug pharmacokinetics, pharmacodynamics, efficacy, and toxicity. In addition, multi-omics, immune, imaging, liquid-biopsy, and digital biomarkers are expanding the scope of individualized pharmacotherapy. These approaches have shown important clinical utility in oncology and are increasingly being explored across cardiovascular, neurological, immunemediated, metabolic, and other therapeutic areas. However, clinical translation remains constrained by inadequate analytical and clinical validation, assay variability, limited representation of diverse populations, difficulties in interpreting rare genetic variants, uncertain clinical utility, high testing costs, ethical concerns, and limited integration into routine healthcare. Biomarkers can support a shift from empirical prescribing toward more precise and individualized drug therapy. Their successful implementation will require prospective clinical validation, standardized testing, diverse population datasets, regulatory harmonization, integration of multiomics and clinical information, and evidence of real-world clinical and economic benefit. A combined approach incorporating pharmacogenomics, therapeutic drug monitoring, modelinformed precision dosing, and artificial intelligence may provide a more comprehensive foundation for individualized drug therapy.