PBPK prediction of ontogeny mediated alteration in hepatic drug elimination

 说明(申请人提供)：在药物处置方面，儿童(特别是新生儿和婴儿)不同于成人。因此，根据成人剂量的经验比例(例如，基于体重)为这一特殊人群选择给药方案是不合适的。这一问题变得更加重要，因为出于后勤、伦理、安全和医疗法律方面的考虑，并不总是可能在临床上确定药物在儿童中的安全性和有效性。例如，在1997-2010年间给新生儿/婴儿开的399种处方药中，只有28种药物的安全性和/或有效性进行了研究。因此，迫切需要开发新的替代方法来预测安全有效的儿童给药方案。一种这样的方法是将年龄相关的生理参数与药物特定的参数(例如，体外酶/转运动力学数据)相结合，以建立基于生理学的儿科药物动力学(PPBPK)模型。一旦得到验证，这种完全机械化的pPBPK模型可以推广到任何药物。然而，为儿童开发这类模型的最大障碍是缺乏与药物处置相关的蛋白质的绝对个体发育数据，即药物代谢酶(Dme)和转运蛋白。已知主要肝脏DMEs的表达存在发育模式，但大多数DMES/转运蛋白的现有数据要么是定性的/半定量的，要么完全缺失。因此，作为纠正这一知识鸿沟的第一步，我们建议量化DMES和转运蛋白在我们独特的儿童肝脏中的表达(n=220)，并将其与成人的表达进行比较。我们将使用选择性和稳健的多反应监测(MRM)蛋白质组学方法来量化这些蛋白质。一旦获得了与年龄相关的蛋白质丰度数据，这些数据就可以与体外动力学和其他发育(生理)信息相结合，构建pPBPK模型。这种合理设计的模型可以使用模型化合物的现有临床数据进行验证，然后推广到通过这些机制在肝脏中消除的药物。由于机械性pPBPK模型可以描述个体代谢/转运途径在药物处置中的部分作用，这种机械性工具也能够准确地预测药物-药物相互作用(DDiS)和由这些途径介导的药物遗传变异性。因此，这项建议解决了新生儿对青少年肝脏药物处置的机制。这项研究中产生的pPBPK模型对于儿童健康将具有巨大的价值，因为这些模型对于评估儿童(包括个体发育最重要的新生儿/婴儿)首次使用药物(或其他外源药物)相关的风险将是重要的。

 DESCRIPTION (provided by applicant): With respect to drug disposition, children (especially neonates and infants) are different than the adults. Therefore it is not appropriate to select dosing regimen for this special population based on empirical scaling (e.g., based on body weight) of the adult dose. This issue becomes more significant as it is not always possible to establish safety and efficacy of drugs in the children at clinic due to logistical, ethical, safetyand medico- legal concerns. For instance, out of 399 prescribed drugs to neonates/infants between 1997-2010, only 28 drugs were studied for the safety and/or efficacy. Thus, it is imperative that novel alternative approaches are developed to predict safe and efficacious dosing regimens for children. One such approach is to integrate age- dependent physiological parameters with drug specific parameters (e.g., in vitro enzyme/transport kinetic data) to develop a pediatric physiologically based pharmacokinetic (pPBPK) model. Once validated, such fully mechanistic pPBPK model can be generalized for any drug. However, the biggest hurdle in developing such models for children are the lack of absolute ontogeny data on the proteins that are related to drug disposition, i.e,, drug metabolizing enzymes (DMEs) and transporters. It is known that developmental pattern exists in the expression of major hepatic DMEs, but the available data are either qualitative/semi-quantitative or completely missing for most of the DMEs/transporters. Therefore, as a first step towards rectifying this gap in knowledge we propose to quantify the hepatic expression of DMEs and transporters in our unique pediatric livers (n=220) and compare this expression with that in adults. We will use selective and robust multiple reaction monitoring (MRM) proteomic approach to quantify these proteins. Once the age-dependent protein abundance data are available, these data can be integrated with in vitro kinetics and other developmental (physiological) information to construct a pPBPK models. Such rationally designed models can be validated using available clinical data on the model compounds, and then generalized to drugs that are eliminated by these mechanisms in the liver. Because mechanistic pPBPK models can delineate fractional role of individual metabolic/transport pathways in drug disposition, such mechanistic tools are also capable of accurately predicting drug-drug interactions (DDIs) and pharmacogenetic variability mediated by these pathways. Hence, this proposal addresses the mechanisms of hepatic drug disposition in neonates to adolescents. The pPBPK model generated in this study will be of enormous value with respect to child health as these will be important to assess the risk associated with the first use of drug (or other xenobiotics) in children (including neonates/infants, where the ontogeny matters most).