Using PKPD Modeling to Optimize Gentamicin Dosing in Saudi Neonates

Abstract

The intricate interplay between pharmacokinetics and pharmacodynamics is pivotal in optimizing gentamicin therapy for neonates, a population characterized by unique physiological developmental considerations and pathophysiological changes in critically ill neonates. Rapid growth, Altered body composition, the immature renal function and premature immune system, significantly influence pharmacokinetic parameters Cl and Vd which aggravate complexities to achieve targets attainment and therapeutic drug monitoring  compared to adults, necessitating individualized dosing strategies. The primary aim of this review, highlights the importance of PKPD modeling to optimizing gentamicin dosing in neonates Emerging trends in pediatric pharmacotherapy underscore the urgency for advancing pharmacokinetic-pharmacodynamic (PKPD) modeling to enhance therapeutic efficacy. Future research should focus on integrating real-world data from diverse neonatal populations. Genetic variations may influence the outcomes of PKPD studies, and subsequent dosing recommendations. Conducting PKPD studies in diverse populations is crucial for obtaining more robust and reliable results, which would allow for more representative models that account for physiological variations. Incorporating advanced computational techniques such as machine learning may further refine predictive accuracy, enabling personalized dosing strategies that minimize toxicity while maximizing therapeutic benefits As research evolves, the role of pediatric-specific biomarkers in PKPD modeling warrants closer investigation, potentially leading to breakthroughs that redefine dosing paradigms. By addressing these critical areas, the field can advance toward more effective and individualized pharmacotherapy, reducing adverse outcomes and improving clinical care for vulnerable neonates.