Population pharmacokinetic modelling, Monte Carlo simulation and semi-mechanistic pharmacodynamic modelling as tools to personalize gentamicin therapy.

Abstract

Population pharmacokinetic modelling, Monte Carlo simulation and semi-mechanistic pharmacodynamic modelling are all tools that can be applied to personalize gentamicin therapy. This review summarizes and evaluates literature knowledge on the population pharmacokinetics and pharmacodynamics of gentamicin and identifies areas where further research is required to successfully individualize gentamicin therapy using modelling and simulation techniques. Thirty-five studies have developed a population pharmacokinetic model of gentamicin and 15 studies have made dosing recommendations based on Monte Carlo simulation. Variability in gentamicin clearance was most commonly related to renal function in adults and body weight and age in paediatrics. Nine studies have related aminoglycoside exposure indices to clinical outcomes. Most commonly, efficacy has been linked to a Cmax/MIC ≥7-10 and a AUC24/MIC ≥70-100. No study to date has shown a relationship between predicted achievement of exposure targets and actual clinical success. Five studies have developed a semi-mechanistic pharmacokinetic/pharmacodynamic model to predict bacteria killing and regrowth following gentamicin exposure and one study has developed a deterministic model of aminoglycoside nephrotoxicity. More complex semi-mechanistic models are required that consider the immune response, use of multiple antibiotics, the severity of illness, and both efficacy and toxicity. As our understanding grows, dosing of gentamicin based on sound pharmacokinetic/pharmacodynamic principles should be applied more commonly in clinical practice.