Pharmacokinetic analysis of meropenem therapeutic drug monitoring data (TDM) in critically ill adult patients

Abstract

Meropenem is a carbapenem antibiotic widely used in treatment of severe infections in ICU. Critically ill patients’ pathophysiological features may cause changes in the pharmacokinetics of meropenem, such as augmented/impaired renal clearance, as well as an increase in the volume of distribution of the drug. Considerable variability in meropenem concentration for the same dosage regimen, severity of the diseases and the escalating antibiotic resistance support the need for an individualization of the dosing in critically ill patients. Estimation of meropenem pharmacokinetic (PK) parameters was performed using the NPAG (non-parametric adaptive grid) program from the Pmetrics package based on peak-trough TDM data. A one-compartment linear PK model with zero-order input and first-order elimination was used to analyze data of the 36 critically ill patients (66 measured meropenem concentrations totally) and to predict pharmacodynamic (PD) parameter values (%T>MIC) based on the time course of free meropenem concentration for empirically prescribed dosage regimens by MIC level. The estimated PK parameters of the meropenem model were in good agreement with those published in the literature earlier. A great interindividual variability for PK parameters from 44.5% up to 167% was revealed. Different regression lines between meropenem clearance and clearance creatinine (CLCr) were registered in patients with CLCr [1] 7 L/h versus > 7 L/h: statistically significant regression (n=30, p=0.015) versus no correlation (n=6, р=0.85), respectively. Bayesian feedback TDM-based meropenem dose personalization is the most practical approach to ensure adequate drug exposure in critically ill patients, especially in patients with augmented renal clearance.

Keywords

• meropenem
• pharmacokinetic/pharmacodynamic modeling
• therapeutic drug monitoring