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Global Analysis of Models for Predicting Human Absorption: QSAR, In Vitro, and Preclinical Models

机译:预测人体吸收模型的全球分析:QSAR、体外和临床前模型

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摘要

Models intended to predict intestinal absorption are an essential part of the drug development process. Although many models exist for capturing intestinal absorption, many questions still exist around the applicability of these models to drug types like "beyond rule of 5" (bRo5) and low absorption compounds. This presents a challenge as current models have not been rigorously tested to understand intestinal absorption. Here, we assembled a large, structurally diverse dataset of similar to 1000 compounds with known in vitro, preclinical, and human permeability and/or absorption data. In silico (quantitative structure-activity relationship), in vitro (Caco-2), and in vivo (rat) models were statistically evaluated for predictive performance against this human intestinal absorption dataset. We expect this evaluation to serve as a resource for DMPK scientists and medicinal/computational chemists to increase their understanding of permeability and absorption model utility and applications for academia and industry.
机译:用于预测肠道吸收的模型是药物开发过程的重要组成部分。尽管存在许多用于捕获肠道吸收的模型,但围绕这些模型对“超出 5 规则”(bRo5) 和低吸收化合物等药物类型的适用性仍然存在许多问题。这带来了挑战,因为目前的模型还没有经过严格的测试来了解肠道吸收。在这里,我们组装了一个大型的、结构多样化的数据集,其中包含类似于 1000 种化合物,具有已知的体外、临床前和人体渗透性和/或吸收数据。对计算机模拟(定量构效关系)、体外(Caco-2)和体内(大鼠)模型的预测性能进行了统计评估。我们希望这一评估能够成为DMPK科学家和药物/计算化学家的资源,以增加他们对渗透性和吸收模型的效用以及学术界和工业界应用的理解。

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