Carolina Llanos-Paez

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

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.

Comparison of methods to estimate glomerular filtration rate in paediatric oncology patients

Glomerular filtration rate (GFR) is estimated daily in paediatric oncology patients; however, few equations, particularly ones that do not include serum creatinine, have been evaluated in this population. We aimed to compare the predictive performance of different equations available to estimate GFR in paediatric oncology patients.

A Population Pharmacokinetic Model of Gentamicin in Pediatric Oncology Patients To Facilitate Personalized Dosing

ABSTRACT To ensure the safe and effective dosing of gentamicin in children, therapeutic drug monitoring (TDM) is recommended. TDM utilizing Bayesian forecasting software is recommended but is unavailable, as no population model that describes the pharmacokinetics of gentamicin in pediatric oncology patients exists. This study aimed to develop and externally evaluate a population pharmacokinetic model of gentamicin to support personalized dosing in pediatric oncology patients. A nonlinear mixed-effect population pharmacokinetic model was developed from retrospective data. Data were collected from 423 patients for model building and a further 52 patients for external evaluation. A two-compartment model with first-order elimination best described the gentamicin disposition. The final model included renal function (described by fat-free mass and postmenstrual age) and the serum creatinine concentration as covariates influencing gentamicin clearance (CL). Final parameter estimates were as follow CL, 5.77 liters/h/70 kg; central volume of distribution, 21.6 liters/70 kg; peripheral volume of distribution, 13.8 liters/70 kg; and intercompartmental clearance, 0.62 liter/h/70 kg. External evaluation suggested that current models developed in other pediatric cohorts may not be suitable for use in pediatric oncology patients, as they showed a tendency to overpredict the observations in this population. The final model developed in this study displayed good predictive performance during external evaluation (root mean square error, 46.0%; mean relative prediction error, −3.40%) and may therefore be useful for the personalization of gentamicin dosing in this cohort. Further investigations should focus on evaluating the clinical application of this model.