Introduction: This study aimed to investigate the relationship between gene polymorphisms and clinical factors with the concentrations of valproic acid (VPA) in adult patients who underwent neurosurgery in China.

Methods: A total of 531 serum concentration samples at steady state were collected from 313 patients to develop a population pharmacokinetic (PPK) model. Data analysis was performed using nonlinear mixed effects modeling. Covariates included demographic parameters, biological characteristics, and genetic polymorphism. Bootstrap evaluation showed that the final model was stable. Sensitive analysis was performed to verify the relationship between gene polymorphisms and concentrations of VPA. Linear regression was used to analyze the relationship between VPA concentration, ANKK1, and daily dosage.

Results: In the recruited patients, 17 of 25 single-nucleotide polymorphism distributions were consistent with the Hardy-Weinberg equilibrium. A one-compartment model with first-order absorption and elimination was developed for VPA injections. VPA clearance was significantly influenced by three variables: sex (17.41% higher in male than female patients), body weight, and the ANKK1 gene. Typical values for the elimination clearance and the volume of central compartment were 0.614 L/min and 23.5 L, respectively. The model evaluation indicated the stable and precise performance of the final model. After sensitive analysis using Kruskal-Wallis and Mann-Whitney U tests, we found that patients with AA alleles had higher VPA concentrations than those with GG and AG alleles. Linear regression models showed that gene polymorphisms of ANKK1 had little effects on VPA concentration.

Conclusion: A PPK model of VPA in Chinese Han patients was successfully established; this can be helpful for model-informed precision-dosing approaches in clinical patient care, and for exploring the mechanism of VPA-induced weight gain.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9837366PMC
http://dx.doi.org/10.1007/s40120-022-00419-8DOI Listing

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