Université Paris Descartes, Paris, France.
J Pharmacokinet Pharmacodyn. 2011 Feb;38(1):25-40. doi: 10.1007/s10928-010-9173-1. Epub 2010 Nov 4.
The aim of this work was to determine whether optimizing the study design in terms of ages and sampling times for a drug eliminated solely via cytochrome P450 3A4 (CYP3A4) would allow us to accurately estimate the pharmacokinetic parameters throughout the entire childhood timespan, while taking into account age- and weight-related changes. A linear monocompartmental model with first-order absorption was used successively with three different residual error models and previously published pharmacokinetic parameters ("true values"). The optimal ages were established by D-optimization using the CYP3A4 maturation function to create "optimized demographic databases." The post-dose times for each previously selected age were determined by D-optimization using the pharmacokinetic model to create "optimized sparse sampling databases." We simulated concentrations by applying the population pharmacokinetic model to the optimized sparse sampling databases to create optimized concentration databases. The latter were modeled to estimate population pharmacokinetic parameters. We then compared true and estimated parameter values. The established optimal design comprised four age ranges: 0.008 years old (i.e., around 3 days), 0.192 years old (i.e., around 2 months), 1.325 years old, and adults, with the same number of subjects per group and three or four samples per subject, in accordance with the error model. The population pharmacokinetic parameters that we estimated with this design were precise and unbiased (root mean square error [RMSE] and mean prediction error [MPE] less than 11% for clearance and distribution volume and less than 18% for k(a)), whereas the maturation parameters were unbiased but less precise (MPE < 6% and RMSE < 37%). Based on our results, taking growth and maturation into account a priori in a pediatric pharmacokinetic study is theoretically feasible. However, it requires that very early ages be included in studies, which may present an obstacle to the use of this approach. First-pass effects, alternative elimination routes, and combined elimination pathways should also be investigated.
本研究旨在探讨是否可以通过优化年龄和采样时间等研究设计，来准确估算仅通过细胞色素 P450 3A4（CYP3A4）代谢的药物在整个儿童期的药代动力学参数，同时考虑到年龄和体重相关的变化。我们采用具有一阶吸收的线性单室模型，结合三种不同的残差模型和先前发表的药代动力学参数（“真实值”）进行分析。通过 CYP3A4 成熟函数的 D-最优设计确定最佳年龄，以创建“优化的人口统计学数据库”。通过药代动力学模型的 D-最优设计确定每个先前选择的年龄的给药后时间，以创建“优化的稀疏采样数据库”。我们通过将群体药代动力学模型应用于优化的稀疏采样数据库来模拟浓度，以创建优化的浓度数据库。然后对后者进行建模，以估算群体药代动力学参数。最后，我们比较了真实值和估计值。本研究建立的最佳设计包括四个年龄范围：0.008 岁（即大约 3 天）、0.192 岁（即大约 2 个月）、1.325 岁和成人，每个组的样本量相同，每个受试者有三到四个样本，符合误差模型。我们通过这种设计估算的群体药代动力学参数准确且无偏（清除率和分布容积的均方根误差[RMSE]和平均预测误差[MPE]小于 11%，k(a)的 MPE 小于 18%），而成熟度参数无偏但不够精确（MPE < 6%，RMSE < 37%）。基于我们的研究结果，在儿科药代动力学研究中，先验考虑生长和成熟在理论上是可行的。然而，这需要在研究中纳入非常早的年龄，这可能会对该方法的应用构成障碍。还需要研究首过效应、替代消除途径和联合消除途径。
