Individualising gentamicin dosage regimens. A comparative review of selected models, data fitting methods and monitoring strategies

Abstract

The various components required for individualising clinical drug dosage regimens are reviewed, including a study of 3 types of fitting procedures, 2 types of gentamicin pharmacokinetic model and the utility of D-optimal times for obtaining serum gentamicin concentrations. The combination of the current Bayesian fitting procedure, the kslope pharmacokinetic model [in which the elimination rate constant (kel) can change from dose to dose with changing creatinine clearance] and the explicit measurement of the assay error pattern yielded predictions of future serum gentamicin concentrations which were (a) slightly better than those found using weighted nonlinear least squares; (b) somewhat better than those found with Bayesian fitting and a fixed-kel model; (c) better than those found using the traditional linear regression fitting procedure and a fixed kel model. D-Optimally timed pairs of concentrations also predicted future concentrations at least as well, and more cost effectively.