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

与吸收、分布、代谢和排泄相关的不同毒代动力学过程的体外数据可以非常快速和大量地生成（即高通量）。目前有很多人热衷于使用这些数据来定量预测外源药物的体内毒性动力学。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，特别是在从体外数据预测肝脏清除方面，已经取得了一些科学进展/突破。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物质？这些新开发的清除模型是否也足以在代谢和蛋白质结合位移水平上进行化学-化学相互作用的体外-体内外推（IVIVE） ？它们可以用来预测人群清除率的变异性吗？此外，目前定量预测外源体内毒性动力学的最大困难之一是具有低膜渗透性的化合物的分布，即扩散限制了组织分布。当组织内渗透性是组织摄取速率的限制因素时，根本没有办法预测组织内的渗透性。因此，拟议的研究计划旨在提高我们利用PBPK模型从体外数据预测体内组织剂量学和毒性动力学的能力。该项目将分为两个具体目标：1)开发一种基于生理学的方法，使膜通透性的IVIVE能够更好地预测扩散限制的组织摄取；2)完善单独化合物和混合物的IVIVE清除模型，以改善体内预测和估计群体中的变异性。从长远来看，我们的目标是建立一个经过验证的PBPK模型框架，该框架将允许IVIVE不同的毒代动力学决定因素，并增加使用体外数据预测体内毒代动力学的信心。通过获取体外和体内实验系统的清除率和渗透性数据，我们将推导出机制关系，以增强和/或增强IVIVE方法在毒性动力学中的应用，从而完善PBPK模型，用于预测毒理学。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求，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中产生。这将促进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.