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口服吸收的测量和预测。

Measurement and prediction of oral absorption.

机构信息

BayerHealthCare, Global Drug Discovery, Drug Metabolism and Pharmacokinetics, PharmaResearch Center, DE-42096 Wuppertal.

出版信息

Chem Biodivers. 2009 Nov;6(11):2000-13. doi: 10.1002/cbdv.200900054.

Abstract

After defining oral absorption, this review article summarizes the influence of different physiological and physicochemical parameters on oral absorption explained according to the situation at BayerScheringPharma. Along the optimization process in industries, prediction of oral absorption is exemplified. In silico prediction of oral absorption in early stages of research is highlighted with three examples, i.e., a classification algorithm, a single parameter prediction, and a linear free-energy relationship. In vitro prediction of permeation using Caco-2 cell layers and physicochemical modeling is exemplified. The influence of solubility is shown by a concrete example, in particular, using physiologically based pharmacokinetic (PBPK) modeling and physicochemical parameters. For later stages, optimization examples of in vivo animal models stress the importance of excellent in vivo data and in vivo/in vivo correlations for the prediction of human oral absorption from animal experiments.

摘要

本文在定义了口服吸收后,根据拜耳先灵医药的情况总结了不同生理和物理化学参数对口服吸收的影响。沿着工业优化过程,举例说明了口服吸收的预测。本文通过三个例子强调了在研究早期通过计算机预测口服吸收的情况,即分类算法、单一参数预测和线性自由能关系。通过 Caco-2 细胞层的体外渗透预测和物理化学模型举例说明了体外预测。通过一个具体的例子展示了溶解度的影响,特别是使用基于生理学的药代动力学(PBPK)模型和物理化学参数。对于后期,体内动物模型的优化实例强调了从动物实验预测人体口服吸收时,获得优秀的体内数据和体内/体内相关性的重要性。

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