Distinguishing between the Permeability Relationships with Absorption and Metabolism To Improve BCS and BDDCS Predictions in Early Drug Discovery

The biopharmaceutics classification system (BCS) and biopharmaceutics drug distribution classification system (BDDCS) are complementary classification systems that can improve, simplify, and accelerate drug discovery, development, and regulatory processes. Drug permeability has been widely accepted as a screening tool for determining intestinal absorption via the BCS during the drug development and regulatory approval processes. Currently, predicting clinically significant drug interactions during drug development is a known challenge for industry and regulatory agencies. The BDDCS, a modification of BCS that utilizes drug metabolism instead of intestinal permeability, predicts drug disposition and potential drug–drug interactions in the intestine, the liver, and most recently the brain. Although correlations between BCS and BDDCS have been observed with drug permeability rates, discrepancies have been noted in drug classifications between the two systems utilizing different permeability models, which are accepted as surrogate models for demonstrating human intestinal permeability by the FDA. Here, we recommend the most applicable permeability models for improving the prediction of BCS and BDDCS classifications. We demonstrate that the passive transcellular permeability rate, characterized by means of permeability models that are deficient in transporter expression and paracellular junctions (e.g., PAMPA and Caco-2), will most accurately predict BDDCS metabolism. These systems will inaccurately predict BCS classifications for drugs that particularly are substrates of highly expressed intestinal transporters. Moreover, in this latter case, a system more representative of complete human intestinal permeability is needed to accurately predict BCS absorption.生物药剂学分类系统（BCS）与生物药剂学药物分布分类系统（BDDCS）是互为补充的分类体系，可优化、简化并加速药物发现、开发及监管流程。在药物开发与监管审批流程中，基于BCS的药物渗透性已被广泛用作判断肠道吸收的筛选工具。当前，在药物开发阶段预测具有临床意义的药物相互作用，仍是行业与监管机构面临的公认难题。BDDCS是BCS的改良版本，以药物代谢替代肠道渗透性作为核心评价指标，可预测药物在肠道、肝脏乃至最新研究涉及的脑部的处置过程与潜在药物相互作用。尽管已有研究观察到BCS与BDDCS在药物渗透性速率上存在相关性，但二者在采用不同渗透性模型进行药物分类时存在差异——这些模型已被美国食品药品监督管理局（Food and Drug Administration, FDA）用作评估人体肠道渗透性的替代模型。本研究推荐适用于优化BCS与BDDCS分类预测效果的渗透性模型。我们证实，缺乏转运蛋白表达与细胞旁连接特征的渗透性模型（如PAMPA与Caco-2）所表征的被动跨细胞渗透性速率，可最精准地预测BDDCS相关的药物代谢。此类模型对高表达肠道转运蛋白底物类药物的BCS分类预测结果将存在偏差。此外针对这类药物，需采用更能完整反映人体肠道渗透性的测试体系，才能精准预测BCS相关的肠道吸收情况。