biostudies-literatureUnknown15(4)Aljutayli APfizerThe recently released revised vancomycin consensus guideline endorsed area under the concentration-time curve (AUC) guided monitoring. Means to AUC-guided monitoring include pharmacokinetic (PK) equations and Bayesian software programs, with the latter approach being preferable. We aimed to evaluate the predictive performance of these two methods when monitoring using troughs or peaks and troughs at varying single or mixed dosing intervals (DIs), and evaluate the significance of satisfying underlying assumptions of steady-state and model transferability. Methods included developing a vancomycin population PK model and conducting model-informed precision dosing clinical trial simulations. A one-compartment PK model with linear elimination, exponential between-subject variability, and mixed Clinical and translational science942-953https://www.ebi.ac.uk/biostudies/studies/S-EPMC9010252biostudies-literaturePharmacokinetic equations versus Bayesian guided vancomycin monitoring: Pharmacokinetic model and model-informed precision dosing trial simulations.PMC9010252Thirion DJGAljutayli ANekka FBonnefois GfalsePharmacokinetic equations versus Bayesian guided vancomycin monitoring: Pharmacokinetic model and model-informed precision dosing trial simulations.The recently released revised vancomycin consensus guideline endorsed area under the concentration-time curve (AUC) guided monitoring. Means to AUC-guided monitoring include pharmacokinetic (PK) equations and Bayesian software programs, with the latter approach being preferable. We aimed to evaluate the predictive performance of these two methods when monitoring using troughs or peaks and troughs at varying single or mixed dosing intervals (DIs), and evaluate the significance of satisfying underlying assumptions of steady-state and model transferability. Methods included developing a vancomycin population PK model and conducting model-informed precision dosing clinical trial simulations. A one-compartment PK model with linear elimination, exponential between-subject variability, and mixed 2022-01-01T00:00:00Z2022 Apr2025-04-18T22:59:01.07Z2025-02-19T03:41:55.179ZS-EPMC90102523517024310.1111/cts.13210