Pediatric drug therapy remains fundamentally challenged by profound interindividual variability driven by dynamic development, genetic, and environmental factors. Although dosing strategies based on age, body weight, or body surface area remain important starting points in pediatric pharmacotherapy, they may not fully capture ontogeny-dependent variability in drug disposition and response. Consequently, clinically relevant differences in efficacy and toxicity may still occur among children receiving similar weight-adjusted doses. Pharmacogenomics offers a promising framework for individualized therapy; however, its clinical translation in pediatrics is limited by developmental variability in gene expression and enzyme activity. Emerging evidence highlights the pivotal role of epigenetic regulation, including DNA methylation, histone modifications, and microRNAs, in modulating pharmacogenetic expression across developmental stages, thereby reshaping drug response trajectories. Concurrently, advances in artificial intelligence and next-generation sequencing enable integration of multidimensional datasets, facilitating predictive modeling of drug efficacy and toxicity. This narrative review provides a comprehensive synthesis of developmental pharmacology, pharmacogenomics, and epigenetic mechanisms, while critically evaluating current translational gaps and implementation challenges. Importantly, it proposes an integrative precision framework that incorporates genetic, epigenetic, and computational insights to optimize pediatric pharmacotherapy. By bridging mechanistic biology with emerging digital health technologies, this work advances a paradigm shift from empirical prescribing toward predictive, adaptive, and individualized therapeutic strategies. The proposed approach holds significant potential to enhance clinical outcomes, minimize adverse effects, and accelerate the realization of precision medicine in pediatric populations.
Satyam et al. (Fri,) studied this question.