Nonparametric Approach to Population Pharmacokinetics in Oncology Patients Receiving Aminoglycoside Therapy

A nonparametric expectation maximization approach to the study of population pharmacokinetics is described for an aminoglycoside antibiotic. The method is used to explore population estimates for gentamicin clearance (liters per hour per creatinine clearance) and volume of distribution (liters per kilogram) in tumor patients. Joint and marginal probability distributions are plotted and further characterized by using standard descriptors such as mean, median, mode, standard deviation, skewness, and kurtosis. Results of additional analyses using hematologic or solid tumor subpopulations agree with those of a recent larger study which found no significant pharmacokinetic differences between these groups. Nonparametric maximum-expectation analyses are conve-nient and allow exploratory analysis of population estimates directly from routine laboratory information. Bayesian feedback methods bring population (a priori) information into pharmacokinetic decisions with a demon-strable advantage (9, 10). However, for economic and ethical reasons, these estimates did not become easily uncovered until the introduction of techniques capable of analyzing routine patient data (3). A nonparametric expectation max-imization (NPEM) algorithm is one method capable of pop