Jiang De-Chun, Wang Li, Wang Yu-Qin, Li Lin, Lu Wei, Bai Xiang-Rong
Department of Pharmacy, Xuan-wu Hospital of Capital Medical University, Beijing 100053, China.
Acta Pharmacol Sin. 2007 Oct;28(10):1677-84. doi: 10.1111/j.1745-7254.2007.00704.x.
The aim of the present study is to establish a population pharmacokinetic (PPK) model of valproate (VPA) in Chinese epileptic children to promote the reasonable use of anti-epileptic drugs.
Sparse data of VPA serum concentrations from 417 epileptic children were collected. These patients were divided into 2 groups: the PPK model group (n=317) and the PPK valid group (n=100). The PPK parameter values of VPA were calculated by NONMEM software using the data of the PPK model group. A basic model and a final model were set up. To validate the 2 models, the concentrations of PPK valid group were predicted by each model, respectively. The mean prediction error (MPE), mean squared prediction error (MSPE), root mean squared prediction error (RMSPE), weight residues (WRES), and the 95% confidence intervals (95% CI) were also calculated. Then, the values between the 2 models were compared.
The PPK of VPA was determined by a 1-compartment model with a first-order absorption process. The basic model was: Ka=3.09 (h(-1)), V/F=20.4 (L), CL/F=0.296 (L/h). The final model was: Ka=0.251+2.24 x (1-HS) (h(-1)), V/F=2.88+0.157 x WT (L), CL/F=0.106(0.98 x CO)+ 0.0157 x AGE (L/h). For the basic model, the MPE, MSPE, RMSPE, WRES, and the 95% CI were -23.53 (-30.36, -16.70), 3728.96 (2872.72, 4585.20), 39.62 (34.34, 44.90), and -0.06 (-0.14, 0.02), respectively. For the final model, the MPE, MSPE, RMSPE, WRES, and the 95% CI were -1.16 (-4.85, 2.53), 1002.83 (1050.64, 1143.61), 23.04 (21.12, 24.96), and 0.08 (-0.04, 0.20), respectively. The final model was more optimal than the basic model.
The PPK model of VPA in Chinese epileptic children was successfully established. It will be valuable to facilitate individualized dosage regimens.
本研究旨在建立丙戊酸（VPA）在中国癫痫儿童中的群体药代动力学（PPK）模型，以促进抗癫痫药物的合理使用。
收集417例癫痫儿童的VPA血清浓度稀疏数据。这些患者被分为两组：PPK模型组（n = 317）和PPK验证组（n = 100）。使用PPK模型组的数据通过NONMEM软件计算VPA的PPK参数值。建立了一个基本模型和一个最终模型。为验证这两个模型，分别用每个模型预测PPK验证组的浓度。还计算了平均预测误差（MPE）、平均平方预测误差（MSPE）、均方根预测误差（RMSPE）、权重残差（WRES）以及95%置信区间（95%CI）。然后，比较两个模型之间的值。
VPA的PPK由具有一级吸收过程的单室模型确定。基本模型为：Ka = 3.09（h⁻¹），V/F = 20.4（L），CL/F = 0.296（L/h）。最终模型为：Ka = 0.251 + 2.24×(1 - HS)（h⁻¹），V/F = 2.88 + 0.157×WT（L），CL/F = 0.106(0.98×CO) + 0.0157×AGE（L/h）。对于基本模型，MPE、MSPE、RMSPE、WRES以及95%CI分别为 -23.53（-30.36，-16.70）、3728.96（2872.72，4585.20）、39.62（34.34，44.90）和 -0.06（-0.14，0.02）。对于最终模型，MPE、MSPE、RMSPE、WRES以及95%CI分别为 -1.16（-4.85，2.53）、1002.83（1050.64，1143.61）、23.04（21.12，24.96）和0.08（-0.04，0.20）。最终模型比基本模型更优。
成功建立了中国癫痫儿童中VPA的PPK模型。这对于促进个体化给药方案具有重要价值。
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