Effects of CYP2C19 and CYP2C9 genotypes on pharmacokinetic variability of valproic acid in Chinese epileptic patients: nonlinear mixed-effect modeling.

Purpose: To evaluate the effects of CYP2C19 and CYP2C9 genotypes on the pharmacokinetic variability of valproic acid (VPA) in epileptic patients using a population pharmacokinetic (PPK) approach.

Methods: VPA concentrations were measured in 287 epileptic patients, who were genotyped for CYP2C19*2/*3 and CYP2C9*3. Patients who were on monotherapy with VPA were divided into two groups, a PPK-model group (n = 177) and a PPK-valid group (n = 110). The PPK parameter values for VPA were calculated in the PPK-model group by using the NONMEM software. Ultimately, a biological model and a final model were established. Each model was then used to independently predict the concentrations of the PPK-valid group to validate the two models.

Results: There was a significant effect of the CYP2C19 and CYP2C9 genotypes on the pharmacokinetic (PK) variability (P < 0.01) in the final PPK model of CL/F. The interindividual CL was calculated according to the final model: CL/F = 0.0951 x (1 + e(0.0267 x (3 - genotype))) + 0.0071 x age (L/h). The coefficient of variation (CV) (omega CL/F) of the final model was 29.3%, while that of the biological model was 31.7%. Based on the genotype, the individual PK parameters can be calculated more accurately than before.

Conclusion: The CYP2C19 and CYP2C9 genotypes significantly influenced the PK variability of VPA, as quantified by NONMEM software.