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Utility of Sparse Concentration Sampling for Citalopram in Elderly Clinical Trial Subjects
Author(s) -
Bies Robert R.,
Feng Yan,
Lotrich Francis E.,
Kirshner Margaret A.,
Roose Steven,
Kupfer David J.,
Pollock Bruce G.
Publication year - 2004
Publication title -
the journal of clinical pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 116
eISSN - 1552-4604
pISSN - 0091-2700
DOI - 10.1177/0091270004269647
Subject(s) - pharmacokinetics , citalopram , covariate , volume of distribution , disposition , medicine , population , serotonin reuptake inhibitor , pharmacology , psychology , statistics , mathematics , serotonin , social psychology , receptor , environmental health
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.