Disposition, Safety and Animal Research, Drug Disposition, Modeling and Simulations Entity, Sanofi-aventis Recherche & Développement, 371, rue du Professeur Joseph Blayac, 34184, Montpellier Cedex 04, France,
J Pharmacokinet Pharmacodyn. 2014 Apr;41(2):187-95. doi: 10.1007/s10928-014-9356-2. Epub 2014 Mar 16.
A population pharmacokinetic analysis was conducted to characterize the pharmacokinetics of fexofenadine in Japanese pediatric patients (6 months through 16 years) with perennial allergic rhinitis or atopic dermatitis. The dataset was composed of 515 patients (including 109 adults), for a total of 1,080 concentration-time points. The analysis was performed with NONMEM using the SAEM method. Several structural models and residual error models were evaluated. The relationship between the individual estimates and the potential covariates was then investigated: demographic and pathophysiologic characteristics were tested as potential model covariates (forward selection method). The qualification of the model was performed using visual predictive check and bootstrap. A two-compartment disposition model with first-order absorption best fitted the data. The inter-individual variability was modeled through an exponential error model for all parameters (except for ka for which no inter-individual term could be estimated), while a proportional error model was used to model the residual variability. The final model included two covariates on elimination clearance and one on the intercompartmental clearance. CL/F was related to BSA and patient's age (expressed in months) Q/F was also related to BSA. Once the model was correctly qualified, exposure parameters such as Cmax and AUCτ were computed and compared between each age sub-group and between Japanese and Caucasians patients. These comparisons did not reveal any major difference (less than 50 %) between subgroups.
进行了群体药代动力学分析,以描述患有常年性变应性鼻炎或特应性皮炎的日本儿科患者(6 个月至 16 岁)中非索非那定的药代动力学特征。该数据集由 515 名患者(包括 109 名成年人)组成,共 1080 个浓度-时间点。使用 NONMEM 通过 SAEM 方法进行分析。评估了几种结构模型和残留误差模型。然后研究了个体估计值与潜在协变量之间的关系:测试了人口统计学和病理生理学特征作为潜在的模型协变量(前向选择方法)。使用可视化预测检查和自举法对模型进行了资格验证。具有一级吸收的两室处置模型最适合数据。通过指数误差模型对所有参数(ka 除外,因为无法估计个体间项)进行个体间变异性建模,而使用比例误差模型对残留变异性进行建模。最终模型包括两个消除清除率的协变量和一个隔室间清除率的协变量。CL/F 与 BSA 和患者年龄(以月表示)相关,Q/F 也与 BSA 相关。一旦模型得到正确验证,就计算了 Cmax 和 AUCτ 等暴露参数,并在每个年龄亚组之间以及日本和白种人患者之间进行了比较。这些比较并未显示亚组之间存在任何重大差异(小于 50%)。