In vitro-in vivo extrapolations and physiologically-based pharmacokinetic modeling: Predicting permeability, clearance, metabolic interactions and interindivual variability from in vitro data

在体外，与吸收、分布、代谢和排泄相关的不同毒物动力学过程的数据可以非常快速和大量地产生(即高通量)。目前，人们对利用这些数据定量预测外来物的体内毒代动力学有很大的热情。尽管仍然存在一些障碍，但在将体外数据外推到体内情况方面已经取得了一些科学进展/突破，特别是在从体外数据预测肝脏清除量方面。但仍有相当大的改进和验证空间。我们仍然不知道如何充分处理与包括白蛋白在内的多种血浆蛋白结合的化学物质？我们应该如何处理这些化学品？这些新开发的清除模型是否也适用于代谢和蛋白质结合位移水平上的化学-化学相互作用的体外-体内外推(IVE)？它们是否可以用来预测人口清除的变异性。此外，目前定量预测异源生物体内毒代动力学的最大困难之一是具有低膜通透性的化合物的分布，即扩散受限的组织分布。当它是组织摄取的速率限制因素时，根本没有方法来预测组织中的活体渗透性。因此，拟议的研究计划旨在提高我们使用PBPK建模从体外数据预测体内组织剂量学和毒代动力学的能力。该计划将分为两个具体目标：1)开发一种基于生理学的方法，以实现膜通透性的IVIVE，以更好地预测扩散限制的组织摄取；以及2)完善单独化合物和混合物的IVIVE清除模型，以改善体内预测并估计人群中的变异性。从长远来看，我们的目标是拥有一个有效的PBPK模型框架，允许对不同的毒代动力学决定因素进行IVIVE，并增加使用体外数据预测体内毒代动力学的信心。通过从体外和体内实验系统获得清除量和渗透性数据，我们将推导出机理关系，以增强和/或增强毒物动力学中的IVIVE方法，从而改进用于预测毒理学的PBPK模型。这项研究计划的成功将不可避免地减少我们在毒代动力学数据中使用活体动物的需要，并提高我们从简单的体外实验中预测体内毒代动力学的能力，这些实验可以在高通量下产生。这将便利和加速环境污染物风险评估以及药物开发方面的决策。

In vitro data of different processes of toxicokinetics related to absorption, distribution metabolism and excretion can be generated very rapidly and in large quantity (i.e., high throughput). Currently there is a lot of enthusiasm towards the use of such data towards quantitative predictions of the in vivo toxicokinetics of xenobiotics. Although there are still some hurdles, there have been some scientific advancements/breakthroughs related to extrapolating in vitro data to the in vivo situation especially related to the prediction of hepatic clearance from in vitro data. But there is still quite some room for improvement and validation. We still do not know how to adequately deal with chemicals binding to multiple plasma proteins that include albumin? How should we deal with these chemicals? Are these newly developed clearance models also adequate for in vitro-in vivo extrapolation (IVIVE) of chemical-chemical interactions at the level of metabolism and protein binding displacements? Can they be used to predict variability in clearance in the population. Also, one of the current greatest difficulties in qunatitatively predicting xenobiotic in vivo toxicokinetics is the distribution of compounds that have low membrane permeability, i.e., diffusion limited tissue distribution. There is simply no approach existing to predict the in vivo permeability in tissues when it is the rate limiting factor of tissue uptake. The proposed research program therefore to to increase our ability to predict in vivo tissue dosimetry and toxicokinetics from in vitro data using PBPK modeling. The program will be divided in 2 specific objectives: 1) to develop a physiologically based approach to enable IVIVE of membrane permeability for a better predictability of diffusion limited tissue uptake; and 2) to refine IVIVE clearance models for compounds alone and for mixtures to ameliorate in vivo predictions and estimate variability in a population. On the long-term, our goal is to have a validated PBPK model framework that will allow IVIVE of different toxicokinetic determinants and to increase confidence in the use of in vitro data for the prediction of in vivo toxicokinetics. By acquiring clearance and permeability data from in vitro and in vivo experimental systems, we will derive mechanistic relationship to enhance and/or enhance IVIVE approaches in toxicokinetics and hence refine PBPK modeling for predictive toxicology. The success of this research program will inevitably decrease our need to use live animals in toxicokinetic data and increase our ability to predict  in vivo toxicokinetics from simple in vitro experiments that can be generated in highthrouput. This will facilitate and accelerate decision making in risk assessment of environmental contaminants as well as in drug development.