Fredlund Linda, Winiwarter Susanne, Hilgendorf Constanze
Molecular Screening and Profiling, Discovery Sciences, ‡Predictive Compound ADME and Safety, Discovery Safety, Drug Safety and Metabolism, and §ADME and Biotransformation, DMPK Cardiovascular and Metabolic Diseases, Innovative Medicines Biotech Unit, AstraZeneca R&D Gothenburg , Mölndal 431 83, Sweden.
Mol Pharm. 2017 May 1;14(5):1601-1609. doi: 10.1021/acs.molpharmaceut.6b01059. Epub 2017 Apr 4.
In vitro permeability data have a central place in absorption risk assessments in drug discovery and development. For compounds where active efflux impacts permeability in vitro, the inherent passive membrane permeability ("intrinsic permeability") gives a concentration-independent measure of the compound's permeability. This work describes the validation of an in vitro intrinsic permeability assay and application of the data in a predictive in silico model. Apparent intrinsic permeability (P) across Caco-2 cell monolayers is determined in the presence of an optimized cocktail of chemical inhibitors toward the three major efflux transporters ABCB1, ABCC2, and ABCG2. The intrinsic P value gives an estimate of passive permeability, which is independent of transporter expression levels and not limited by solubility or cell toxicity. An in silico model has been established to predict the Caco-2 intrinsic permeability and shown to consistently identify highly permeable compounds. The new intrinsic permeability assay is useful for early absorption estimates and suitable for absorption risk assessment in DMPK and pharmaceutical development.
体外通透性数据在药物研发的吸收风险评估中占据核心地位。对于那些主动外排在体外影响通透性的化合物，其固有的被动膜通透性（“内在通透性”）给出了一个与浓度无关的化合物通透性度量。这项工作描述了一种体外内在通透性测定法的验证以及该数据在一个预测性计算机模拟模型中的应用。在存在针对三种主要外排转运蛋白ABCB1、ABCC2和ABCG2的优化化学抑制剂混合物的情况下，测定跨Caco-2细胞单层的表观内在通透性（P）。内在P值给出了被动通透性的估计值，该值与转运蛋白表达水平无关，且不受溶解度或细胞毒性的限制。已经建立了一个计算机模拟模型来预测Caco-2内在通透性，并显示该模型能够持续识别高通透性化合物。这种新的内在通透性测定法对于早期吸收估计很有用，并且适用于药物代谢动力学（DMPK）和药物研发中的吸收风险评估。
