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探索生物药剂学中的动力学模型方法:估算口服给药在人体中的吸收分数。

Exploring a Kinetic Model Approach in Biopharmaceutics: Estimating the Fraction Absorbed of Orally Administered Drugs in Humans.

机构信息

Global Research and Development, SMPS, Genentech Inc., South San Francisco, California 94080.

Global Research and Development, SMPS, Genentech Inc., South San Francisco, California 94080.

出版信息

J Pharm Sci. 2018 Jul;107(7):1798-1805. doi: 10.1016/j.xphs.2018.03.015. Epub 2018 Mar 21.

Abstract

Increasing costs of research and development in the pharmaceutical industry has necessitated a growing interest in the early prediction of human pharmacokinetics of drug candidates. Of growing interest is the need to understand oral absorption, the most common route of small molecule drug administration. The fraction of dose absorbed (%Fa) is considered a critical yet challenging parameter to predict. A kinetic model has been developed and tested to provide an early prediction of the fraction dose absorbed in humans. Unlike the traditional plug-flow model, this model assumes first-order kinetics to estimate the amount of drug present in the stomach and small intestine as a function of time and calculates the amount of drug released and absorbed during the transit. Other variables can be included in calculation as a function of time to better mimic the physiological condition with this approach. Absorption efficiency is assigned along with %Fa to give a quantitative estimate of the limiting factor for oral absorption. The model was tested with literature and in-house compounds. It was found that this model gives a good prediction of human %Fa with a correction coefficient (R) of 0.8 and greater between predicted and reported %Fa for all compounds.

摘要

制药行业研发成本的不断增加,使得人们越来越关注对候选药物的人体药代动力学的早期预测。人们越来越关注的是需要了解口服吸收,这是小分子药物给药的最常见途径。吸收率分数(% Fa)被认为是一个关键但具有挑战性的预测参数。已经开发并测试了一种动力学模型,以提供对人体吸收剂量分数的早期预测。与传统的柱塞流模型不同,该模型假设一级动力学来估计胃和小肠中存在的药物量随时间的变化,并计算在转运过程中释放和吸收的药物量。其他变量可以作为时间的函数包含在计算中,以通过这种方法更好地模拟生理状况。吸收效率与% Fa 一起分配,以定量估计口服吸收的限制因素。该模型使用文献和内部化合物进行了测试。结果发现,该模型对人体% Fa 的预测效果良好,所有化合物的预测和报告的% Fa 之间的校正系数(R)为 0.8 或更高。

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