School of Pharmacy, Department of Pharmaceutics, University of Washington, Seattle, WA 98195-7610, USA.
Drug Metab Dispos. 2012 Jan;40(1):159-68. doi: 10.1124/dmd.111.042200. Epub 2011 Oct 18.
Metabolites can have pharmacological or toxicological effects, inhibit metabolic enzymes, and be used as probes of drug-drug interactions or specific cytochrome P450 (P450) phenotypes. Thus, better understanding and prediction methods are needed to characterize metabolite exposures in vivo. This study aimed to test whether in vitro data could be used to predict and rationalize in vivo metabolite exposures using two model drugs and P450 probes: dextromethorphan and omeprazole with their primary metabolites dextrorphan, 5-hydroxyomeprazole (5OH-omeprazole), and omeprazole sulfone. Relative metabolite exposures were predicted using metabolite formation and elimination clearances. For dextrorphan, the formation clearances of dextrorphan glucuronide and 3-hydroxymorphinan from dextrorphan in human liver microsomes were used to predict metabolite (dextrorphan) clearance. For 5OH-omeprazole and omeprazole sulfone, the depletion rates of the metabolites in human hepatocytes were used to predict metabolite clearance. Dextrorphan/dextromethorphan in vivo metabolite/parent area under the plasma concentration versus time curve ratio (AUC(m)/AUC(p)) was overpredicted by 2.1-fold, whereas 5OH-omeprazole/omeprazole and omeprazole sulfone/omeprazole were predicted within 0.75- and 1.1-fold, respectively. The effect of inhibition or induction of the metabolite's formation and elimination on the AUC(m)/AUC(p) ratio was simulated. The simulations showed that unless metabolite clearance pathways are characterized, interpretation of the metabolic ratios is exceedingly difficult. This study shows that relative in vivo metabolite exposure can be predicted from in vitro data and characterization of secondary metabolism of probe metabolites is critical for interpretation of phenotypic data.
代谢物可能具有药理学或毒理学效应,抑制代谢酶,并可用作药物相互作用或特定细胞色素 P450(P450)表型的探针。因此,需要更好地理解和预测方法来描述体内代谢物的暴露情况。本研究旨在测试体外数据是否可用于预测和合理化使用两种模型药物和 P450 探针(右美沙芬和奥美拉唑)及其主要代谢物右啡烷、5-羟奥美拉唑(5OH-奥美拉唑)和奥美拉唑砜的体内代谢物暴露情况。使用代谢物形成和消除清除率预测相对代谢物暴露情况。对于右啡烷,使用右美沙芬在人肝微粒体中形成右啡烷葡萄糖醛酸和 3-羟吗啡烷的清除率来预测代谢物(右啡烷)清除率。对于 5OH-奥美拉唑和奥美拉唑砜,使用代谢物在人肝细胞中的耗竭率来预测代谢物清除率。体内右啡烷/右美沙芬代谢物/母体的血浆浓度-时间曲线下面积比(AUC(m)/AUC(p))被高估了 2.1 倍,而 5OH-奥美拉唑/奥美拉唑和奥美拉唑砜/奥美拉唑的预测值分别在 0.75-和 1.1 倍范围内。模拟了代谢物形成和消除的抑制或诱导对 AUC(m)/AUC(p)比值的影响。模拟结果表明,除非对代谢物清除途径进行特征描述,否则对代谢比值的解释非常困难。本研究表明,可以从体外数据预测相对体内代谢物暴露情况,并且探针代谢物的次级代谢特征对于表型数据的解释至关重要。