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预测超出五规则属性空间的化合物的口服吸收。

Predicting Oral Absorption for Compounds Outside the Rule of Five Property Space.

机构信息

Pharmacokinetic Sciences, Novartis Institutes for BioMedical Research, Basel, Switzerland.

Pharmacokinetic Sciences, Novartis Institutes for BioMedical Research, Basel, Switzerland.

出版信息

J Pharm Sci. 2021 Jun;110(6):2562-2569. doi: 10.1016/j.xphs.2021.01.029. Epub 2021 Feb 1.

DOI:10.1016/j.xphs.2021.01.029
PMID:33539870
Abstract

The estimation of the extent of absorption of drug candidates intended for oral drug delivery is an important selection criteria in drug discovery. The use of cell-based transwell assays examining flux across cell-monolayers (e.g., Caco-2 or MDCK cells) usually provide satisfactory predictions of the extent of absorption in vivo. These predictions often fall short of expection for molecules outside the traditional low molecular weight property space. In this manuscript the transwell permeability assay was modified to circumvent potential issues that can be encountered when evaluating the aforementioned drug molecules. Particularly, the addition of albumin in the acceptor compartment to reduce potential binding to cells and the acceptor compartment, improved the predictive power of the assay. Cellular binding and lysosomal trapping effects are significantly reduced for larger molecules, particularly lipophilic bases under these more physiological conditions, resulting in higher recovery values and a better prediction power. The data indicate that lysosomal trapping does not impact the rate of absorption of lipophilic bases in general but is rather an exception. Finally, compounds believed to permeate by passive mechanisms were used in a calibration curve for the effective prediction of the fraction absorbed of molecules of interest in current medicinal chemistry efforts.

摘要

用于口服药物递送的候选药物的吸收程度的估计是药物发现中的一个重要选择标准。使用基于细胞的 Transwell 测定法来检查跨细胞单层(例如,Caco-2 或 MDCK 细胞)的通量,通常可以对体内吸收的程度提供令人满意的预测。对于超出传统低分子量性质范围的分子,这些预测通常不符合预期。在本文中,修改了 Transwell 渗透率测定法,以避免在评估上述药物分子时可能遇到的问题。特别是,在接受腔中添加白蛋白以减少与细胞和接受腔的潜在结合,提高了测定法的预测能力。对于较大的分子,特别是亲脂性碱基,在这些更生理的条件下,细胞结合和溶酶体捕获效应显著降低,导致更高的回收率和更好的预测能力。数据表明,溶酶体捕获一般不会影响亲脂性碱基的吸收速率,但这是一个例外。最后,将被认为通过被动机制渗透的化合物用于校准曲线中,以有效预测当前药物化学研究中感兴趣的分子的吸收分数。

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