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Updated: May 21, 2026

Multiplex Therapeutic Drug Monitoring by Isotope-dilution HPLC-MS/MS of Antibiotics in Critical Illnesses
Published on: August 30, 2018
Population Pharmacokinetics and Clinical Application of Vancomycin in Critically Ill Adults: A NONMEM-Based Review
Huanran Husheng1,2,3, Ying Wang1,4, Yan He1,2,3
1Clinical Trials Center & Key Laboratory of Clinical Pharmacology and Translational Research, the Affiliated Hospital of Guizhou Medical University, Guiyang, 550000, People's Republic of China.
Abstract:
Vancomycin remains an important treatment for severe Gram-positive infections in the intensive care unit (ICU), but critically ill adults show highly variable pharmacokinetics, making conventional dosing unreliable. This review aimed to summarize Nonlinear Mixed-Effects Modeling (NONMEM)-based population pharmacokinetic studies of vancomycin in critically ill adults and identify clinically relevant covariates associated with exposure variability. PubMed, Embase, and Google Scholar were searched from inception to January 2026. Twelve original studies met the inclusion criteria. All focused on adult ICU populations and used nonlinear mixed-effects modeling with NONMEM. One-compartment models were most commonly used, although parameter estimates varied substantially across populations. Typical clearance ranged from 1.19 to 5.15 L/h. Excluding volume estimates that needed to be normalized to actual body weight, reported typical values ranged from 29.2 to 107 L. Covariate analyses consistently identified renal function and body weight as important determinants of clearance, whereas continuous renal replacement therapy (CRRT)/high-volume hemofiltration (HVHF) intensity and residual renal function were particularly relevant in patients receiving extracorporeal support. Mechanical ventilation was retained as a covariate on clearance in some models. Overall, these findings highlight the marked heterogeneity of vancomycin pharmacokinetics in critical illness and support more individualized dosing strategies, ideally combining early therapeutic drug monitoring with model-informed precision dosing.
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