Department of Bioengineering & Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California San Francisco, 533 Parnassus Avenue, Room U-68, San Francisco, CA 94143-0912, USA.
AAPS J. 2013 Apr;15(2):483-97. doi: 10.1208/s12248-013-9456-8. Epub 2013 Jan 24.
There is a growing need for highly accurate in silico and in vitro predictive models to facilitate drug discovery and development. Results from in vitro permeation studies across the Caco-2 cell monolayer are commonly used for drug permeability screening in industry and are also accepted as a surrogate for human intestinal permeability measurements by the US FDA to support new drug applications. Countless studies carried out in this cell line with published permeability measurements have enabled the development of many in silico prediction models. We identify several common cases that illustrate how using Caco-2 permeability measurements in these in silico and in vitro predictive models will not correlate with human intestinal permeability and will further lead to inaccuracies in these models. We provide guidelines and recommendations for improving these models to more accurately predict clinically relevant information, thereby enhancing the drug discovery, development, and regulatory approval processes.
人们越来越需要高度准确的计算机模拟和体外预测模型，以促进药物发现和开发。体外透过 Caco-2 细胞单层的渗透研究结果通常用于行业中的药物渗透性筛选，并且也被美国 FDA 接受为人类肠道渗透性测量的替代方法，以支持新药申请。通过对该细胞系进行的无数项具有已发表渗透性测量值的研究，开发出了许多计算机模拟预测模型。我们确定了几种常见情况，说明了在这些计算机模拟和体外预测模型中使用 Caco-2 渗透性测量值将如何与人类肠道渗透性不相关，并进一步导致这些模型的不准确。我们提供了改进这些模型的指南和建议，以更准确地预测临床相关信息，从而增强药物发现、开发和监管审批过程。
