Gobeau N, Stringer R, De Buck S, Tuntland T, Faller B
Metabolism and Pharmacokinetics (MAP) Department, Novartis Institutes for Biomedical Research, Basel, Switzerland.
Medicines for Malaria Venture, Route de Pré-Bois 20, PO Box 1826, 1215, Geneva 15, Switzerland.
Pharm Res. 2016 Sep;33(9):2126-39. doi: 10.1007/s11095-016-1951-z. Epub 2016 Jun 8.
The aim of this study was to evaluate the oral exposure predictions obtained early in drug discovery with a generic GastroPlus Advanced Compartmental And Transit (ACAT) model based on the in vivo intravenous blood concentration-time profile, in silico properties (lipophilicity, pKa) and in vitro high-throughput absorption-distribution-metabolism-excretion (ADME) data (as determined by PAMPA, solubility, liver microsomal stability assays).
The model was applied to a total of 623 discovery molecules and their oral exposure was predicted in rats and/or dogs. The predictions of Cmax, AUClast and Tmax were compared against the observations.
The generic model proved to make predictions of oral Cmax, AUClast and Tmax within 3-fold of the observations for rats in respectively 65%, 68% and 57% of the 537 cases. For dogs, it was respectively 77%, 79% and 85% of the 124 cases. Statistically, the model was most successful at predicting oral exposure of Biopharmaceutical Classification System (BCS) class 1 compounds compared to classes 2 and 3, and was worst at predicting class 4 compounds oral exposure.
The generic GastroPlus ACAT model provided reasonable predictions especially for BCS class 1 compounds. For compounds of other classes, the model may be refined by obtaining more information on solubility and permeability in secondary assays. This increases confidence that such a model can be used in discovery projects to understand the parameters limiting absorption and extrapolate predictions across species. Also, when predictions disagree with the observations, the model can be updated to test hypotheses and understand oral absorption.
本研究旨在评估在药物发现早期，基于体内静脉血药浓度-时间曲线、计算机模拟性质（亲脂性、pKa）和体外高通量吸收-分布-代谢-排泄（ADME）数据（通过平行人工膜渗透试验、溶解度、肝微粒体稳定性试验测定），使用通用的 GastroPlus 高级房室和转运（ACAT）模型获得的口服暴露预测结果。
该模型应用于总共 623 个发现阶段的分子，并预测了它们在大鼠和/或犬体内的口服暴露情况。将 Cmax、AUClast 和 Tmax 的预测值与观测值进行比较。
在 537 例大鼠实验中，通用模型预测的口服 Cmax、AUClast 和 Tmax 分别在观测值的 3 倍以内，比例分别为 65%、68%和 57%。在 124 例犬实验中，相应比例分别为 77%、79%和 85%。从统计学角度来看，与 2 类和 3 类化合物相比，该模型在预测生物药剂学分类系统（BCS）1 类化合物的口服暴露方面最为成功，而在预测 4 类化合物的口服暴露方面表现最差。
通用的 GastroPlus ACAT 模型提供了合理的预测，尤其是对于 BCS 1 类化合物。对于其他类别的化合物，可通过在二级试验中获取更多关于溶解度和渗透性的信息来优化该模型。这增加了人们对于此类模型可用于发现项目以理解限制吸收的参数并跨物种外推预测结果的信心。此外，当预测结果与观测值不一致时，可更新模型以检验假设并理解口服吸收情况。
