Effects of <Emphasis Type="Italic">CYP2C19</Emphasis> and <Emphasis Type="Italic">CYP2C9</Emphasis> 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?×?(1?+?e^{0.0267?×?(3???genotype)})?+?0.0071?×?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.