Prediction of the human oral bioavailability by using in vitro and in silico drug related parameters in a physiologically based absorption model

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• 作者：Paulo Paixã ; o^a ; ^b ; ^{ppaixao@ff.ul.pt} ; Luí ; s F. Gouveia^a ; José ; A.G. Morais^a
• 关键词：Physiological-based pharmacokinetic model of absorption ; In vitro&ndash ; in vivo correlation ; In silico&ndash ; in vivo correlation ; Human absolute bioavailability
• 刊名：International Journal of Pharmaceutics
• 出版年：2012
• 期刊代码：24_03785173
• 类别：pha
• 出版时间：15 June, 2012
• 卷：429
• 期：1-2
• 页码：84-98
• 文件大小：845 K

摘要

Estimates of the human oral absolute bioavailability were made by using a physiological-based pharmacokinetic model of absorption and the drug solubility at the gastrointestinal pH range 1.5-7.5, the apparent permeability (P_app) in Caco-2 cells and the intrinsic clearance (Cl_int) in human hepatocytes suspensions as major drug related parameters. The predictive ability of this approach was tested in 164 drugs divided in four levels of input data: (i) in vitro data for both P_app and Cl_int; (ii) in vitro data for Cl_int only; (iii) in vitro data for P_app only and (iv) in silico data for both P_app and Cl_int. In all scenarios, solubility was estimated in silico. Excellent predictive abilities were observed when in vitro data for both P_app and Cl_int were used, with 84%of drugs with oral bioavailability predictions within a 卤 20%interval of the correct value. This predictive ability is reduced with the introduction of the in silico estimated parameters, particularly when Cl_int is used. Performance of the model using only in silico data provided 53%of drugs with bioavailability predictions within a 卤 20%acceptance interval. However, 74%of drugs in the same scenario resulted in bioavailability predictions within a 卤 35%interval, which indicates that a qualitative prediction of the absolute bioavailability is still possible. This approach is a valuable way to estimate a fundamental pharmacokinetic parameter, using data typically collected in the drug discovery and early development phases, providing also mechanistic information of the limiting bioavailability steps of the drug.