Shen Xianhuan, Chen Xinyi, Lu Jieluan, Chen Qing, Li Wenzhou, Zhu Jiahao, He Yaodong, Guo Huijuan, Xu Chenshu, Fan Xiaomei
Shenzhen Baoan Women's and Children's Hospital, Jinan University, Shenzhen, China.
College of Pharmacy, Jinan University, Guangzhou, China.
Front Pharmacol. 2022 Nov 25;13:1037239. doi: 10.3389/fphar.2022.1037239. eCollection 2022.
The aim of this study was to establish a population pharmacokinetic (PPK) model of valproic acid (VPA) in pediatric patients with epilepsy in southern China, and provide guidance for individualized medication of VPA therapy. A total of 376 VPA steady-state trough concentrations were collected from 103 epileptic pediatric patients. The PPK parameter values for VPA were calculated by using the nonlinear mixed-effects modeling (NONMEM) method, and a one-compartment model with first-order absorption and elimination processes was applied. Covariates included demographic information, concomitant medications and selected gene polymorphisms. Goodness-of-fit (GOF), bootstrap analysis, and visual predictive check (VPC) were used for model evaluation. In addition, we used Monte Carlo simulations to propose dose recommendations for different subgroup patients. A significant effect of the patient age and genotypes was observed on the VPA oral clearance (CL/F) in the final PPK model. Compared with patients with the rs3789243 AA genotype, CL/F in patients with GG and AG genotypes was increased by 8% and reduced by 4.7%, respectively. The GOF plots indicated the satisfactory predictive performance of the final model, and the evaluation by bootstrap and VPC showed that a stable model had been developed. A table of individualized dosing regimens involving age and genotype was constructed based on the final PPK model. This study quantitatively investigated the effects of patient age and rs3789243 variants on the pharmacokinetic variability of VPA. The PPK models could be beneficial to individual dose optimization in epileptic children on VPA therapy.
本研究旨在建立中国南方癫痫患儿丙戊酸(VPA)的群体药代动力学(PPK)模型,并为VPA治疗的个体化用药提供指导。共收集了103例癫痫患儿的376个VPA稳态谷浓度。采用非线性混合效应建模(NONMEM)方法计算VPA的PPK参数值,并应用具有一级吸收和消除过程的单室模型。协变量包括人口统计学信息、合并用药和选定的基因多态性。采用拟合优度(GOF)、自抽样分析和视觉预测检查(VPC)进行模型评估。此外,我们使用蒙特卡洛模拟为不同亚组患者提出剂量建议。在最终的PPK模型中,观察到患者年龄和基因型对VPA口服清除率(CL/F)有显著影响。与rs3789243 AA基因型患者相比,GG和AG基因型患者的CL/F分别增加了8%和降低了4.7%。GOF图表明最终模型具有令人满意的预测性能,自抽样和VPC评估表明已建立了一个稳定的模型。基于最终的PPK模型构建了涉及年龄和基因型的个体化给药方案表。本研究定量研究了患者年龄和rs3789243变异对VPA药代动力学变异性的影响。PPK模型可能有助于癫痫患儿VPA治疗的个体剂量优化。