Lin Wei-wei, Jiao Zheng, Wang Chang-lian, Wang Hua-yan, Ma Chun-lai, Huang Ping-fang, Guo Xian-zhong, Liu Yi-wei
*Department of Pharmacy, The First Affiliated Hospital, Fujian Medical University, Fuzhou; †Department of Pharmacy, Huashan Hospital, Fudan University, Shanghai; and ‡Department of Neurology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
Ther Drug Monit. 2015 Feb;37(1):76-83. doi: 10.1097/FTD.0000000000000100.
There are several reports describing population pharmacokinetic (PPK) models of valproic acid (VPA). However, little was known in Chinese adult patients with epilepsy. The present study aimed to establish a PPK model for VPA in Chinese adult epileptic patients and to demonstrate its use for dose individualization.
Data were obtained from a prospective study of 199 adult epileptic patients at 5 hospitals. The trough concentrations at steady state were measured by fluorescence polarization immunoassay. Data were analyzed using the Nonlinear Mixed Effects Model software. The serum trough concentrations at steady state were also measured using samples (n = 20) collected prospectively from a different hospital from those providing the data for deriving the original model. These independent samples served as an evaluation group.
The important determinants of apparent VPA clearance were daily dose, body weight, and combination with carbamazepine, phenytoin, or phenobarbital. The final model predicted the individualized doses accurately. A total of 85% of the trough concentrations in the evaluation group were accurately predicted by the final model, whereas the prediction errors of the other patients were all < ± 31%.
A PPK model was developed to estimate the individual clearance for patients taking VPA and could be applied for individualizing doses in the target population.
有几篇报道描述了丙戊酸(VPA)的群体药代动力学(PPK)模型。然而,在中国成年癫痫患者中对此了解甚少。本研究旨在建立中国成年癫痫患者VPA的PPK模型,并证明其在剂量个体化中的应用。
数据来自对5家医院199例成年癫痫患者的前瞻性研究。稳态时的谷浓度通过荧光偏振免疫测定法测量。使用非线性混合效应模型软件分析数据。还使用从与提供推导原始模型数据的医院不同的另一家医院前瞻性收集的样本(n = 20)测量稳态时的血清谷浓度。这些独立样本用作评估组。
VPA表观清除率的重要决定因素是每日剂量、体重以及与卡马西平、苯妥英或苯巴比妥的联合使用。最终模型准确预测了个体化剂量。最终模型准确预测了评估组中85%的谷浓度,而其他患者的预测误差均<±31%。
建立了一个PPK模型来估计服用VPA患者的个体清除率,并可应用于目标人群的剂量个体化。