Metabolism and Pharmacokinetics Platform, Novartis Institutes for BioMedical Research, 250 Massachusetts Avenue, Cambridge, Massachusetts 02139, USA.
J Pharm Sci. 2010 Jul;99(7):3246-65. doi: 10.1002/jps.22080.
We systematically validated a robust 96-well Caco-2 assay via an extended set of 93 marketed drugs with diverse transport mechanisms and quantified by LC/MS/MS, to investigate its predictive utility while dealing with challenging discovery compounds. Utilizing nonlinear fit, the validation led to a good correlation (R(2) = 0.76) between absorptive permeability, log P(app)(A-B), from in vitro Caco-2 assay and reported human fraction of dose absorbed. We observed that paracellular compounds could be flagged by log P(app)(A-B) (<-5.5 cm/s) and physicochemical property space (c log P < 1). Of 8000 Novartis discovery compounds examined 13% were subject to low recovery (<30%). Compound loss was investigated by comparing cell monolayer and artificial membrane, while 0.5% bovine serum albumin (in both donor and acceptor compartments) was utilized to improve recovery. The second focus of this study was to investigate the advantages and limitations of the current Caco-2 assay for predicting in vivo intestinal absorption. Caco-2 measurements for compounds with high aqueous solubility and low in vitro metabolic clearance were compared to 88 in vivo rat bioavailability studies. Despite the challenges posed by discovery compounds with suboptimal physicochemical properties, Caco-2 data successfully projected low intestinal absorption. This platform sets the stage for mechanistically evaluating compounds towards improving in vitro-in vivo correlations.
我们通过一组扩展的 93 种具有不同转运机制的市售药物，利用 LC/MS/MS 进行定量分析，对一种稳健的 96 孔 Caco-2 测定法进行了系统验证，以研究其在处理具有挑战性的发现化合物时的预测效用。通过非线性拟合，验证得到了吸收性渗透率与体外 Caco-2 测定法的 log P(app)(A-B)和报告的人体剂量吸收分数之间的良好相关性 (R(2) = 0.76)。我们观察到，可通过 log P(app)(A-B)(< -5.5 cm/s)和物理化学性质空间 (c log P < 1)来标记旁细胞化合物。在检查的 8000 种诺华发现化合物中，有 13%的化合物回收率低(<30%)。通过比较细胞单层和人工膜来研究化合物的损失，同时在供体和受体腔室中使用 0.5%牛血清白蛋白来提高回收率。本研究的第二个重点是研究当前 Caco-2 测定法预测体内肠道吸收的优缺点。将具有高水溶性和低体外代谢清除率的化合物的 Caco-2 测定值与 88 种体内大鼠生物利用度研究进行了比较。尽管具有不理想物理化学性质的发现化合物带来了挑战，但 Caco-2 数据成功预测了低肠道吸收。该平台为通过改善体外-体内相关性来对化合物进行机制评估奠定了基础。
