Utility of sparse concentration sampling for citalopram in elderly clinical trial subjects

Abstract

The objective of this study was to evaluate whether the disposition of the selective serotonin reuptake inhibitor, citalopram, could be robustly captured using 1 to 2 concentration samples per subject in 106 patients participating in 2 clinical trials. Nonlinear mixed-effects modeling was used to evaluate the pharmacokinetic parameters describing citalopram's disposition. Both a prior established 2-compartment model and a de novo 1-compartment pharmacokinetic model were used. Covariates assessed were concomitant medications, race, sex, age (22-93 years), and weight. Covariates affecting disposition were assessed separately and then combined in a stepwise manner. Pharmacokinetic characteristics of citalopram were well captured using this sparse sampling design. Two covariates (age and weight) had a significant effect on the clearance and volume of distribution in both the 1- and 2-compartment pharmacokinetic models. Clearance decreased 0.23 L/h for every year of age and increased 0.14 L/h per kilogram body weight. It was concluded that hyper-sparse sampling designs are adequate to support population pharmacokinetic analysis in clinically treated populations. This is particularly valuable for populations such as the elderly, who are not typically available for pharmacokinetic studies.