Impact of gender, albumin, and CYP2C19 polymorphisms on valproic acid in Chinese patients: a population pharmacokinetic model

OBJECTIVE: This prospective study aimed to establish the valproic acid (VPA) population pharmacokinetic model in Chinese patients and realise personalised medication on the basis of population pharmacokinetics. METHODS: The patients’ clinical information and VPA plasma concentrations were collected from The General Hospital of Taiyuan Iron & Steel (Group) Corporation (TISCO). Nonlinear mixed-effect modelling was used to build the population pharmacokinetic model. To characterise the pharmacokinetic data, a one-compartment pharmacokinetic model with first-order absorption and elimination was used. The first-order conditional estimation with η-ε interaction was applied throughout the model-developing procedure. The absorption rate constant (Ka) was fixed at 2.38 hour(−1), and the impact of covariates on clearance and apparent volume of distribution were also explored. Medical records of 60 inpatients were reviewed prospectively and the objective function value (OFV) of the base model and final model were 851.813 and 817.622, respectively. RESULTS: Gender was identified as the covariate that had a significant impact on the volume of distribution, and albumin and CYP2C19 genotypes influenced clearance. CONCLUSION: Bootstrap and VPC indicated that a reliable model had been developed that was based on the simulation results, and a simple-to-use dosage regimen table was created to guide clinicians for VPA drug dosing.