Summary
A new nonparametric expectation maximisation (NPEM) algorithm for the estimation of population pharmacokinetic parameter values was evaluated. The algorithm, in the form of a personal computer program, was used to compute population pharmacokinetic parameter densities of gentamicin in a group of 9 patients with indicators of malnutrition. The 1-compartment parameter values for clearance (CL), volume of distribution (Vd) and elimination rate constant (k) were compared with values generated using a standard 2-stage (STS) approach. NPEM was used with a full data set (72 gentamicin concentrations) and a sparse data set (only peak and trough concentrations for each patient; 18 in total). There were no differences in parameter value estimations between the STS and NPEM with all the data (p > 0.05) or with the sparse data (p > 0.05).
Mean parameter value estimates from the STS and NPEM (with sparse data) were used as a priori data sets in the USC*PACK gentamicin Bayesian program to predict concentrations in 8 subsequent patients with similar indicators of malnutrition. There were no differences in predicted gentamicin concentrations between STS (3.75 ± 2.06 mg/L) and NPEM (3.75 ± 2.17 mg/L). NPEM was able to generate population pharmacokinetic parameter values for gentamicin in a defined population of patients using sparse routine clinical data. It was also shown to function with only a single data point per patient.
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Kisor, D.F., Watling, S.M., Zarowitz, B.J. et al. Population Pharmacokinetics of Gentamicin. Clin. Pharmacokinet. 23, 62–68 (1992). https://doi.org/10.2165/00003088-199223010-00005
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DOI: https://doi.org/10.2165/00003088-199223010-00005