Vancomycin population pharmacokinetic modeling in children using Bayesian estimation and a Non Parametric Approach

Anna Luísa Silveira; Geisa Cristina Silva Alves; Jiao Xie; Jason Roberts; Cristina Sanches

doi:10.1590/s2175-97902020000X2e19313

Authors

Anna Luísa Silveira Federal University of São João del-Rei, Minas Gerais, Brazil https://orcid.org/0000-0002-2061-2405
Geisa Cristina Silva Alves Federal University of São João del-Rei, Minas Gerais, Brazil
Jiao Xie The University of Queensland Centre for Clinical Research, The University of Queensland, Brisbane, Australia
Jason Roberts The University of Queensland Centre for Clinical Research, The University of Queensland, Brisbane, Australia; Department of Intensive Care Medicine, Royal Brisbane and Women’s Hospital, Brisbane, Australia; Pharmacy Department, Royal Brisbane and Women’s Hospital, Brisbane, Australia; Centre for Translational Anti-infective Pharmacodynamics, School of Pharmacy, The University of Queensland, Brisbane, Queensland, Australia
Cristina Sanches Federal University of São João del-Rei, Minas Gerais, Brazil

DOI:

https://doi.org/10.1590/s2175-97902020000X2e19313

Keywords:

Glycopeptide, Vancomycin, Pharmacokinetics, Pharmacokinetic Modelling, Pediatric

Abstract

To analyze microbiological effectiveness of vancomycin in children from a pediatric hospital through population pharmacokinetic modelling, as well as to propose dose adjustment, a cross- sectional study was performed in children under vancomycin treatment from the John Paul II Children’s Hospital, MG. In order to establish a model, concentrations versus time curves were analyzed using a population pharmacokinetic approach with Pmetrics®. Seventeen blood samples of 10 patients were collected. The best model to describe vancomycin population pharmacokinetic (PK) consisted of a two-compartment linear intravenous absorption model. The R² value and bias for population and individuals in observed versus predicted plot was 0.642 vs. 0.992 and the bias of 0.41 mg/L and 0.0778 mg/L, respectively. The covariables creatinine clearance, age, and body mass index were related to vancomycin PK. A relevant PK variability for vancomycin in pediatric patients was verified, which was significantly influenced by creatinine clearance, age, and body mass index. This result justifies the formulation of dosing recommendations for vancomycin in pediatric patients to achieve adequate pharmacodynamics targets.

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References

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Vancomycin population pharmacokinetic modeling in children using Bayesian estimation and a Non Parametric Approach

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