首页> 外文期刊>Therapeutic Drug Monitoring >Validation of population pharmacokinetic parameters of phenytoin using the parallel Michaelis-Menten and first-order elimination model.
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Validation of population pharmacokinetic parameters of phenytoin using the parallel Michaelis-Menten and first-order elimination model.

机译:使用并行Michaelis-Menten和一阶消除模型验证苯妥英的总体药代动力学参数。

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This study was conducted to assess whether the parallel Michaelis-Menten and first-order elimination (MM+FO) model fitted the data better than the Michaelis-Menten (MM) model, and to validate the MM+FO model and its parameter estimates. The models were fitted to 853 steady state dose: serum concentration pairs obtained in 332 adults with epilepsy using nonlinear mixed-effects modeling (NONMEM). The MM+FO model fitted the data better than the MM model. The validity of the pharmacokinetic models and the estimated population parameter values was tested using the naive prediction method. The estimation and validation of the pharmacokinetic parameters were undertaken in two separate patient groups (cross-validation) obtained by splitting the data set. Patients were randomly allocated to two equally matched groups (groups 1 and 2). The predictive performance was assessed using 770 paired predicted versus actual dose or measured serum concentrations. The population pharmacokinetic parameters estimated by NONMEM in group 1 were validated in group 2 and vice versa. When predicting steady state serum concentration, the MM+FO model was clearly superior to the MM model (mean bias of 0.91 and 8.13 mg/L, respectively).
机译:进行这项研究是为了评估并行的Michaelis-Menten模型和一阶消除(MM + FO)模型是否比Michaelis-Menten(MM)模型更适合数据,并验证MM + FO模型及其参数估计。使用非线性混合效应模型(NONMEM),将模型拟合为853稳态剂量:在332例癫痫成人中获得的血清浓度对。 MM + FO模型比MM模型更适合数据。使用天真的预测方法测试了药代动力学模型和估计的群体参数值的有效性。通过拆分数据集在两个独立的患者组中进行药代动力学参数的估计和验证(交叉验证)。将患者随机分配到两个相等匹配的组(第1组和第2组)。使用770对预测剂量与实际剂量或测量的血清浓度进行评估,评估预测性能。在第2组中验证了由NONMEM在第1组中估计的总体药代动力学参数,反之亦然。当预测稳态血清浓度时,MM + FO模型明显优于MM模型(平均偏差分别为0.91和8.13 mg / L)。

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