OBJECTIVE: To quantitatively model nortriptyline clearance as a function of the cytochrome P450 (CYP) 2D6 genotype and to estimate the contribution of genotype to the interindividual variability in steady-state plasma concentration and metabolic clearance. DESIGN: Modelling study using data from two previously published studies. PARTICIPANTS: 20 healthy volunteers receiving single oral doses of nortriptyline and 20 patients with depression on steady-state oral treatment. METHODS: A total of 275 nortriptyline plasma concentrations were analysed by standard nonlinear regression and nonlinear mixed effect models. The pharmacokinetic model was a 1-compartment model with first order absorption and elimination. All participants had previously been genotyped with respect to the CYP2D6 polymorphism. RESULTS: A model in which the intrinsic clearance is a linear function of the number of functional CYP2D6 genes and hepatic blood flow is fixed to 60 L/h gave the closest fit of the pharmacokinetic model to the data. Stable estimates were obtained for population pharmacokinetic parameters and interindividual variances. Assuming 100% absorption, the model allows systemic clearance and bioavailability to be estimated. Bioavailability was found to vary between 0.17 and 0.71, depending on the genotype. Using the frequency distribution of CYP2D6 genotype with the above results we estimate that, in compliant Swedish individuals on nortriptyline monotherapy, the number of functional CYP2D6 genes could explain 21% of the total interindividual variance in oral clearance of nortriptyline and 34% of that in steady-state plasma concentrations. CONCLUSION: Nonlinear mixed-effects modelling can be used to quantify the influence of the number of functional CYP2D6 genes on the metabolic clearance and plasma concentration of drugs metabolised by this enzyme. Gene dose has a significant impact on drug pharmacokinetics and prior knowledge of it may aid in predicting plasma concentration of the drug and thus tailoring patient-specific dosage regimens.
OBJECTIVE: To quantitatively model nortriptyline clearance as a function of the cytochrome P450 (CYP) 2D6 genotype and to estimate the contribution of genotype to the interindividual variability in steady-state plasma concentration and metabolic clearance. DESIGN: Modelling study using data from two previously published studies. PARTICIPANTS: 20 healthy volunteers receiving single oral doses of nortriptyline and 20 patients with depression on steady-state oral treatment. METHODS: A total of 275 nortriptyline plasma concentrations were analysed by standard nonlinear regression and nonlinear mixed effect models. The pharmacokinetic model was a 1-compartment model with first order absorption and elimination. All participants had previously been genotyped with respect to the CYP2D6 polymorphism. RESULTS: A model in which the intrinsic clearance is a linear function of the number of functional CYP2D6 genes and hepatic blood flow is fixed to 60 L/h gave the closest fit of the pharmacokinetic model to the data. Stable estimates were obtained for population pharmacokinetic parameters and interindividual variances. Assuming 100% absorption, the model allows systemic clearance and bioavailability to be estimated. Bioavailability was found to vary between 0.17 and 0.71, depending on the genotype. Using the frequency distribution of CYP2D6 genotype with the above results we estimate that, in compliant Swedish individuals on nortriptyline monotherapy, the number of functional CYP2D6 genes could explain 21% of the total interindividual variance in oral clearance of nortriptyline and 34% of that in steady-state plasma concentrations. CONCLUSION: Nonlinear mixed-effects modelling can be used to quantify the influence of the number of functional CYP2D6 genes on the metabolic clearance and plasma concentration of drugs metabolised by this enzyme. Gene dose has a significant impact on drug pharmacokinetics and prior knowledge of it may aid in predicting plasma concentration of the drug and thus tailoring patient-specific dosage regimens.
Authors: Lauren M Osborne; Catherine A Birndorf; Lauren E Szkodny; Katherine L Wisner Journal: Arch Womens Ment Health Date: 2014-03-26 Impact factor: 3.633
Authors: Jesse J Swen; Tom W Huizinga; Hans Gelderblom; Elisabeth G E de Vries; Willem J J Assendelft; Julia Kirchheiner; Henk-Jan Guchelaar Journal: PLoS Med Date: 2007-08 Impact factor: 11.069