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Physiologically based pharmacokinetic models: Integration of in silico approaches with micro cell culture analogues

机译:基于生理学的药代动力学模型:计算机方法与微细胞培养类似物的整合

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There is a large emphasis within the pharmaceutical industry to provide tools that will allow early research and development groups to better predict dose ranges for and metabolic responses of candidate molecules in a high throughput manner, prior to entering clinical trials. These tools incorporate approaches ranging from PBPK, QSAR, and molecular dynamics simulations in the in silico realm, to micro cell culture analogue (CCAs)s in the in vitro realm. This paper will serve to review these areas of high throughput predictive research, and highlight hurdles and potential solutions. In particular we will focus on CCAs, as their incorporation with PBPK modeling has the potential to replace animal testing, with a more predictive assay that can combine multiple organ analogs on one microfluidic platform in physiologically correct volume ratios. While several advantages arise from the current embodiments of CCAS in a microfluidic format that can be exploited for realistic simulations of drug absorption, metabolism and action, we explore some of the concerns with these systems, and provide a potential path forward to realizing animal-free solutions. Furthermore we envision that, together with theoretical modeling, CCAs may produce reliable predictions of the efficacy of newly developed drugs.
机译:制药行业非常重视提供工具,这些工具将允许早期的研究和开发小组在进入临床试验之前,以高通量的方式更好地预测候选分子的剂量范围和代谢反应。这些工具结合了从计算机领域的PBPK,QSAR和分子动力学模拟到体外领域的微细胞培养类似物(CCA)的方法。本文将用于回顾高吞吐量预测研究的这些领域,并重点介绍障碍和潜在解决方案。我们将特别关注CCA,因为它们结合PBPK模型有潜力取代动物试验,并且具有更具预测性的测定方法,该方法可以在生理上正确的体积比下在一个微流体平台上结合多种器官类似物。虽然CCAS的当前实施例具有微流格式的优点,可用于药物吸收,代谢和作用的现实模拟,但我们探索了这些系统的一些问题,并为实现无动物性提供了潜在途径解决方案。此外,我们设想,与理论模型一起,CCA可以对新开发药物的疗效做出可靠的预测。

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