A Comprehensive Analysis of Teicoplanin Population Pharmacokinetic Models in Pediatric Populations: Age-Dependent Variability and Implications for Dose Optimization

Purpose: Teicoplanin (TEC) is widely used for treating invasive infections caused by Gram-positive bacteria. Due to its high pharmacokinetic variability, several population pharmacokinetic (PPK) studies have been performed to identify factors contributing to the variability. This review aims to provide a comprehensive overview of published PPK studies and explore potential covariates. Patients and Methods: We systematically searched the PubMed, Web of Science, and Embase databases and compared study characteristics, model parameters, and covariate effects. Visual predictive distributions were used to compare different models. Forest plots and Monte Carlo simulations were used to assess the influence of covariates and probability of target attainment (PTA) against methicillin-resistant Staphylococcus aureus (MRSA). Results: A total of eight PPK studies involving preterm infants, neonates, infants, children, and adolescents were finally included. The median weight-normalized clearance (CL) in adolescents was 0.0116 L/h/kg, 14.7% and 16.0% lower than that in infants and children, respectively, and significantly approximately 22.7% lower than that in neonates. Key covariates impacting TEC clearance included body weight, postmenstrual age (PMA), renal function parameters, albumin levels, and continuous kidney replacement therapy (CKRT) status. Monte Carlo simulations indicated that current dosing regimens may be inadequate, particularly when treating MRSA with minimum inhibitory concentration (MIC) = 2 mg/L, as the PTA for AUC 24 /MIC≥ 400 often fell below 90%. Conclusion: TEC dosing in pediatric patients should be individualized, taking into account factors like age, weight, and renal function. Moreover, further population studies are essential to be conducted to clarify the dose-exposure-response relationship of TEC. PROSPERO Registration: CRD420251012884 Keywords: teicoplanin, population pharmacokinetics, nonlinear mixed-effect model, dosage optimization, pediatric