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Eur J Clin Pharmacol ; 78(3): 405-418, 2022 Mar.
Article in English | MEDLINE | ID: mdl-34854947

ABSTRACT

PURPOSE: To develop and validate a population pharmacokinetic (PPK) model of valproic acid (VPA) in adult Chinese patients with bipolar disorder, and provide guidance for individualized therapy in this population. METHODS: A total of 1104 serum concentrations from 272 patients were collected in this study. The data analysis was performed using a nonlinear mixed-effects modeling approach. Covariates included demographic parameters, biological characteristics, and concomitant medications. Bootstrap validation (1000 runs), normalized prediction distribution error (NPDE), and external validation of 50 patients were employed to evaluate the final model. RESULTS: A one-compartment model with first-order absorption and elimination was developed for VPA extended-release tablets. VPA clearance was significantly influenced by three variables: sex (12% higher in male patients), daily dose (increasing with the 0.13 exponent), and body weight (increasing with the 0.56 exponent). Typical values for the absorption rate constant (Ka), apparent clearance (CL/F), and apparent distribution volume (V/F) for a female patient weighing 70 kg administered VPA 1000 mg/day were 0.18 h-1, 0.46 L/h, and 12.84 L, respectively. The results of model evaluation indicated a good stable and precise performance of the final model. CONCLUSIONS: A qualified PPK model of VPA was developed in Chinese patients with bipolar disorder. This model could be used as a suitable tool for the personalization of VPA dosing for bipolar patients.


Subject(s)
Antipsychotic Agents/pharmacokinetics , Bipolar Disorder/drug therapy , Valproic Acid/pharmacokinetics , Adolescent , Adult , Aged , Aged, 80 and over , Antipsychotic Agents/therapeutic use , Asian People , Body Weight , China , Delayed-Action Preparations , Dose-Response Relationship, Drug , Female , Humans , Male , Middle Aged , Models, Biological , Monte Carlo Method , Valproic Acid/therapeutic use , Young Adult
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