Paroxetine: population pharmacokinetic analysis in late-life depression using sparse concentration sampling

Abstract

Aim: To develop a population pharmacokinetic (PK) model using sparse sampling of long-term treatment with paroxetine in elderly depressed subjects, incorporating CYP2D6 genotype as well as other covariates.

Methods: Elderly subjects (age>or=70 years) with nonpsychotic, nonbipolar major depressive disorder from the inpatient and outpatient clinic were treated with paroxetine in a 5-year clinical trial investigating 'Maintenance Therapies in Late-Life Depression' (MTLD-2). Plasma concentrations were collected during regular visits. CYP2D6 genotype was determined using polymerase chain reaction (PCR) for each individual. A nonlinear mixed-effects model was developed with NONMEM for these subjects who received 10-40 mg day-1 of paroxetine during treatment. One- and two-compartment models with linear and nonlinear elimination (Michaelis-Menten) were evaluated. PK parameters as well as interindividual and residual variability were estimated. The effects of age, weight, sex, race and CYP2D6 genotypes on the pharmacokinetics of paroxetine were evaluated.

Results: One hundred and seventy-one subjects with a mean age of 77 years (range 69-95) and a mean weight of 72.0 kg (range 32.9-137.0) were enrolled in the MTLD-2 clinical trial. A total of 1970 paroxetine concentrations were available for population PK analyses. Approximately 10 samples were taken per subject. A two-compartment nonlinear PK model with additive and proportional error provided the best base model for description of the data. Weight and CYP2D6 polymorphisms were found to have a significant effect on maximal velocity (Vm), whereas sex had an effect on volume of distribution of the central compartment. The Vm estimates in each of the CYP2D6 phenotypic groups were: 125 microg h-1 in poor metabolizer (n=1), 182 microg h-1 in intermediate metabolizers (n=28), 454 microg h-1 in extensive metabolizers (n=36) and 3670 microg h-1 in ultra-rapid metabolizers (n=5).

Conclusions: The population PK model adequately described paroxetine data in this elderly depressed population. The data indicate that female and male subjects with different CYP2D6 polymorphisms have different elimination rates and therefore may need to be dosed differently based on metabolizer genotype.

Figure 1

Frequency histogram showing the sampling distribution for paroxetine sampling measurements. The abscissa is broken into 1-h bins. The ordinate is the proportion of samples taken in each interval

Figure 2

Diagnostic plots of final pharmacokinetic model. (a) Plot of population predicted paroxetine concentrations vs. observed paroxetine concentrations. Individual data points are shown as dots and the unity line is shown as a solid line. (b) Plot of individual population predicted paroxetine concentrations vs. observed paroxetine concentrations. Individual data points are shown as dots and the unity line is shown as a solid line. (c) Plot of weighted residual error (WRES) vs. population predicted concentrations. (d) Plot of WRES vs. time

Figure 3

Box plot of V_m estimates for each CYP2D6 phenotype group. Dots in each group were median values. Notches show approximate 95% confidence limits for the median. CYP2D6 genotype was classified into one of the four CYP2D6 phenotype groups based on the phenotype–genotype relationship. In this plot, PMs = poor metabolizers, IMs = Intermediate metabolizers, EMs = extensive metabolizers, UMs = ultra-rapid metabolizers. Missing = Subject was missing CYP2D6 phenotype information