F. Hoffmann-La Roche AG, pRED, Pharma Research & Early Development, Non-Clinical Safety, Basel, Switzerland.
Eur J Pharm Sci. 2012 Sep 29;47(2):375-86. doi: 10.1016/j.ejps.2012.06.013. Epub 2012 Jul 1.
First pass metabolism in the intestinal mucosa is a determinant of oral bioavailability of CYP3A substrates and so the prediction of intestinal availability (Fg) of potential drug candidates is important. Although intestinal metabolism can be modeled in commercial physiologically based pharmacokinetic (PBPK) software tools, a thorough evaluation of prediction performance is lacking. The current study evaluates the accuracy and precision of GastroPlus Fg predictions for 20 CYP3A substrates using in vitro and in silico input data for metabolic clearance and membrane permeation, and illustrates a potential impact of intestinal metabolism modeling on decision making in a drug Research and Development project. This analysis supports that CYP3A mediated metabolic clearance measured in human liver microsomes can be used to predict gut wall metabolism. Using values scaled from in vitro cell permeability as input for effective jejunal permeability resulted in good Fg prediction accuracy (no significant bias and ∼95% of predictions within 2 fold from in vivo estimated Fg), whereas simulations with in silico predicted permeability tended to overestimate gut metabolism (40% of Fg predictions under predicted more than 2 fold) ±2 fold range as an estimate of imprecision in metabolic clearance and permeability inputs propagated to >5 and <2 fold ranges of predicted Fg for compounds with <30% and >75% in vivo Fg, respectively, suggesting lower precision of predictions for high extraction compounds. Furthermore, parameter sensitivity analysis suggests that limitations in solubility or dissolution may either decrease Fg by preventing saturation of metabolism or increase Fg by shifting the site of absorption towards the colon where expression of CYP3A is low. The case example illustrates how, when accounting for the associated uncertainty in predicted pharmacokinetics and linking to predictive models for efficacy, PBPK modeling of intestinally metabolized compounds can support decision making in drug Research and Development.
肠道黏膜的首过代谢是 CYP3A 底物口服生物利用度的决定因素，因此预测潜在药物候选物的肠道可用性（Fg）非常重要。虽然可以在商业生理相关药代动力学（PBPK）软件工具中对肠道代谢进行建模，但缺乏对预测性能的彻底评估。本研究使用代谢清除率和膜通透性的体外和计算输入数据，评估 GastroPlus Fg 对 20 种 CYP3A 底物的预测准确性和精密度，并说明了肠道代谢建模对药物研发项目决策的潜在影响。该分析支持用人肝微粒体中测量的 CYP3A 介导的代谢清除率来预测肠壁代谢。使用从体外细胞通透性缩放的值作为有效空肠通透性的输入，可实现良好的 Fg 预测准确性（无显著偏差，且约 95%的预测值在体内估计的 Fg 的 2 倍以内），而使用计算预测的通透性进行模拟则倾向于高估肠道代谢（40%的 Fg 预测值高于 2 倍）±2 倍范围可作为代谢清除率和通透性输入的不精确性的估计值，在体内 Fg 分别小于 30%和大于 75%的化合物中，预测 Fg 的范围大于 5 倍或小于 2 倍，这表明对于高提取化合物，预测的精度较低。此外，参数敏感性分析表明，溶解度或溶解度的限制可能会通过阻止代谢饱和来降低 Fg，或者通过将吸收部位转移到 CYP3A 表达较低的结肠来增加 Fg。该案例说明了如何在考虑预测药代动力学的相关不确定性并与功效预测模型关联的情况下，对肠道代谢化合物进行 PBPK 建模可支持药物研发的决策。
