Population Pharmacokinetics and AUC‐Based Dose Optimization of Vancomycin in Chinese Neonates

Objective: The primary objective of this study revolves around the development of a population pharmacokinetic (PPK) model for vancomycin in neonatal subjects, with the objective of providing a theoretical basis for judicious therapeutic interventions. Methods: In this study, a retrospective collection encompassed 75 neonatal patients, contributing to a total of 89 vancomycin blood concentration monitoring datasets. The establishment of the PPK model is carried out utilizing the nonlinear mixed effects model methodology. The PPK model was constructed employing a one‐compartment model with proportional residual error, and the influence of covariates on pharmacokinetic parameters was systematically assessed through forward stepwise addition and backward elimination methods. The stability and predictive accuracy of the final model were assessed using goodness‐of‐fit plots, nonparametric bootstrap validation, visual predictive checks, and normalized prediction distribution errors. Furthermore, Monte Carlo simulations were employed to predict vancomycin concentrations in neonatal patients with typical characteristics. Results: The final PPK model yielded population‐typical values of 0.24 L/h for vancomycin clearance (CL). Noteworthy contributors to vancomycin CL were identified as body weight, gestational age, creatinine clearance rate (CLcr), and sex. Internal validation results of the model indicate that it possesses stability, efficacy, and demonstrates a favorable predictive capacity. Monte Carlo simulations indicate that for a male neonatal patient characterized by a gestational age of 37 weeks, a body weight of 2.5 kg, and a CLcr of 60 mL/min, the recommended dosing regimen is 25.5 to 41.5 mg every 8 h. Conclusion: This investigation has successfully formulated a PPK model for vancomycin in neonatal patients, offering the capacity to estimate individual CL. The dosing regimen for neonates should take into account factors such as body weight, gestational age, CLcr, and sex.