上海交通大学学报（医学版）

›› 2010, Vol. 30 ›› Issue (2): 135-.

• 专题报道（儿科学研究） • 上一篇    下一篇

癫癎儿童拉莫三嗪群体药代动力学模型的研究

何大可1, 王 丽2, 秦 炯2, 胡鸿文3, 叶秀云3, 刘海涛4   

  1. 1. 上海交通大学 医学院新华医院儿内科, 上海 200092；2. 北京大学 第一医院儿内科, 北京 100034；3. 温州医学院 育英儿童医院神经内科, 温州 325027；4. 上海交通大学 医学院新华医院药剂科, 上海 200092
  • 出版日期:2010-02-25 发布日期:2010-02-25
  • 作者简介:何大可（1974—）, 男, 主治医师, 博士；电子信箱: hedake@139.com。

Research on population pharmacokinetics of Lamotrigine in children with epilepsy

HE Da-ke1, WANG Li2, QIN Jiong2, HU Hong-wen3, YE Xiu-yun3, LIU Hai-tao4   

  1. 1. Department of Pediatrics, Xinhua Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200092, China；2. Department of Pediatrics, Peking University First Hospital, Beijing100034, China；3. Department of Neurology, Yuying Children Hospital, Wenzhou Medical College, Wenzhou 325027, China；4. Department of Pharmacy, Xinhua Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200092, China
  • Online:2010-02-25 Published:2010-02-25

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摘要：

目的 采用USC*PACK软件建立中国癫癎儿童拉莫三嗪的群体药代动力学（PPK）模型，促进个体化用药。方法 回顾性收集60例癫癎患儿应用拉莫三嗪（LTG）的临床数据，并根据联合用药情况，将114个血药浓度点分成LTG+丙戊酸（VPA）组（n=56）、LTG+肝药酶诱导剂（EI）组（n=26）、LTG+EI+VPA组（n=16）及单用LTG 组（n=16）。血药浓度均为临床常规监测的稳态浓度。应用USC*PACK软件中的非参数最大期望程序（NPEM Program），推算最优的PPK参数值，并建立模型。应用此模型和USC*PACK软件中的贝叶斯拟合程序（Bayesian fitting program），对患儿的血药浓度进行预测；求算平均预测误差（MPE），预测误差均方（MSPE）判断预测的准确度和精密度，验证PPK模型。结果 最大似然值为-192.87，LTG的最佳PPK参数值为：Ka＝（1.97±1.66）h-1；Vs＝（1.07±0.89）L/kg；Kel＝（0.05±0.05）h-1。血药浓度拟合值与观测值的相关系数r=0.99，回归方程为YOBS=-0.09+1.05×YPRED（R2=0.98，P<0.001）。MPE为-0.16 μg/mL，MSPE为0.28（μg/mL）2。结论 在USC*PACK软件中，应用自行建立的PPK模型和Bayes法，估算个体PK参数，再进一步算出半衰期、峰谷浓度以及调药后的峰谷浓度，甚至可以模拟出调药前后的药时曲线，满足临床上的多种需求，使得临床用药从传统的经验用药模式提高到科学的个体化用药模式。

关键词: 拉莫三嗪, 群体药代动力学, USC*PACK软件, 癫癎, 儿童

Abstract:

Objective To establish the population pharmacokinetics（PPK）model of Lamotrigine (LTG) in children with epilepsy in China for promoting individualized dosage regimen. Methods The sparse data of LTG serum concentrations from 60 pediatric patients with epilepsy were collected. One hundred and fourteen serum concentration points were divided into LTG+valproic acid (VPA) group (n=56), LTG+ enzymatic inducer (EI) group (n=26), LTG+EI+VPA group (n=16) and single LTG group (n=16). The serum drug concentrations were the clinical routinely tested steady state concentrations. The LTG PPK parameters were calculated using the non-parametric expectation maximization (NPEM) Program of USC*PACK software, and then a PPK model was established. Based on this model, LTG serum concentrations were predicted with Bayesian fitting program of USC*PACK software. Mean prediction error (MPE) and mean squared prediction error (MSPE) were calculated to evaluate the accuracy and precision of the concentration prediction and to valid the PPK model. Results The greatest likelihood was -192.87. Optimum PPK parameters were: Ka=(1.97 1.66) h-1; Vs=(1.07±0.89) L/kg; Kel=(0.05±0.05) h-1. The linear regression function YOBS=-0.09+1.05 YPRED (R2=0.98, P<0.001), and determination of coefficient was 0.98. MPE was -0.16  g/mL, and MSPE was 0.28 (μg/mL)2. Conclusion A PPK model of LTG in children with epilepsy in China can be successfully established using the USC*PACK software, based on which LTG serum concentrations can be predicted accurately with a Bayesian approach.

Key words: Lamotrigine, population pharmacokinetics, USC*PACK software, epilepsy, children