Prediction of the human oral bioavailability by using in vitro and in silico drug related parameters in a physiologically based absorption model
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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DOI：
10.1016/j.ijpharm.2012.03.019
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发表时间：
2012-06-15
影响因子：
5.8
通讯作者：
Morais, Jose A. G.
中科院分区：
文献类型：
--
作者：
Paixao, Paulo;Gouveia, Luis F.;Morais, Jose A. G.
在胃肠道pH值为1.5-7.5的范围内，用基于生理的药代动力学吸收和药物溶解度模型、Caco-2细胞的表观渗透率(P-app)和人肝细胞混悬液的固有清除量(Cl-int)作为主要药物相关参数，估算了口服药物的绝对生物利用度。在164种药物中测试了这种方法的预测能力，这些药物分为四个输入数据水平：(I)P-APP和Cl-INT的体外数据；(Ii)仅Cl-INT的体外数据：(Iii)仅P-APP的体外数据和(Iv)P-APP和Cl-INT的计算机数据。在所有情况下，溶解度都是以硅胶为单位进行估计的。当同时使用P-APP和氯-INT的体外数据时，观察到良好的预测能力，84%的口服生物利用度预测在正确值的+/-20%区间内。这种预测能力随着电子估算参数的引入而降低，特别是当使用氯-INT时。仅在电子计算机数据中使用该模型的性能为53%的药物提供了在+/-20%接受区间内的生物利用度预测。然而，在同一情景下，74%的药物的生物利用度预测在+/-35%的区间内，这表明对绝对生物利用度的定性预测仍然是可能的。这种方法是一种估计基本药代动力学参数的有价值的方法，使用通常在药物发现和早期开发阶段收集的数据，还提供药物限制生物利用度步骤的机械信息。(C)2012爱思唯尔B.V.保留所有权利。
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 +/- 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 +/- 20% acceptance interval. However, 74% of drugs in the same scenario resulted in bioavailability predictions within a +/- 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. (c) 2012 Elsevier B.V. All rights reserved.