Population pharmacokinetics and dose optimization of vancomycin in neonates

Author:

Lee Soon Min,Yang Seungwon,Kang Soyoung,Chang Min Jung

Abstract

AbstractThe pharmacokinetics of vancomycin vary among neonates, and we aimed to conduct population pharmacokinetic analysis to determine the optimal dosage of vancomycin in Korean neonates. From a retrospective chart review, neonates treated with vancomycin from 2008 to 2017 in a neonatal intensive care unit (NICU) were included. Vancomycin concentrations were collected based on therapeutic drug monitoring, and other patient characteristics were gathered through electronic medical records. We applied nonlinear mixed-effect modeling to build the population pharmacokinetic model. One- and two-compartment models with first-order elimination were evaluated as potential structural pharmacokinetic models. Allometric and isometric scaling was applied to standardize pharmacokinetic parameters for clearance and volume of distribution, respectively, using fixed powers (0.75 and 1, respectively, for clearance and volume). The predictive performance of the final model was developed, and dosing strategies were explored using Monte Carlo simulations with AUC0–24 targets 400–600. The patient cohort included 207 neonates, and 900 vancomycin concentrations were analyzed. Only 37.4% of the analyzed concentrations were within trough concentrations 5–15 µg/mL. A one-compartment model with first-order elimination best described the vancomycin pharmacokinetics in neonates. Postmenstrual age (PMA) and creatinine clearance (CLcr) affected the clearance of vancomycin, and model evaluation confirmed the robustness of the final model. Population pharmacokinetic modeling and dose optimization of vancomycin in Korean neonates showed that vancomycin clearance was related to PMA and CLcr, as well as body weight. A higher dosage regimen than the typical recommendation is suggested.

Funder

A faculty research grant of Yonsei University College of Medicine

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

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