Ramsden Diane, Fullenwider Cody L, Santos Cipriano, LeCluyse Edward L
Preclinical Development, Korro Bio Inc., Cambridge, Massachusetts.
Vividion Therapeutics, San Diego, California.
Drug Metab Dispos. 2025 Apr;53(4):100052. doi: 10.1016/j.dmd.2025.100052. Epub 2025 Feb 25.
Quantitative prediction and clinical risk assessment for induction of drug-metabolizing enzymes and transporters beyond CYP3A has been hindered by low dynamic response in the gold standard hepatocyte monoculture model. A gap in translation of the drug-drug interaction (DDI) potential of a compound is particularly apparent when an inducer also inhibits CYP3A, leading to uncertainty in the potential net clinical outcome for CYP3A substrates. In addition, enzymes such as CYP2C8, CYP2C9, CYP2C19, UGT1A4, and P-glycoprotein, which are coregulated with CYP3A, may result in clinically relevant induction that cannot be derisked by conducting clinical interaction studies with CYP3A substrates. Identification of an in vitro model that demonstrates consistent and well defined induction of enzymes and transporters beyond CYP3A would open the opportunity to avoid unnecessary clinical interaction studies and subsequently have high value in the drug discovery and development toolbox. The TruVivo model is a novel all-human primary cell model, containing hepatocytes plus stromal and epithelial feeder cells. Within these studies, the TruVivo model was validated as a predictive tool for clinical risk assessment for induction of CYP2C8, CYP2C9, CYP2C19, CYP3A4, UGT1A4, and P-glycoprotein using known clinical inducers. Exploration into the utility of TruVivo to delineate complex DDI involving coinducers/inhibitors was also conducted and showed immense opportunity, demonstrating the value of in situ DDI experiments when clinically relevant levels of precipitant and object drugs are used. These data highlight the potential of this in vitro tool to model induction and complex DDI. SIGNIFICANCE STATEMENT: Clinical risk assessment for induction of enzymes and transporters coregulated with CYP3A, including the CYP2C enzymes, UDP-glucuronosyltransferases, and P-gp has been hampered by the low dynamic response of available in vitro models. These studies aimed to validate a novel all-human hepatocyte model, TruVivo, as a predictive tool for induction-based DDI. In addition, the model was evaluated for in situ prediction of complex DDI and shows promise in predicting net clinical outcomes for several inducers/inhibitors against selective and nonselective CYP3A substrates.
在金标准肝细胞单培养模型中,由于动态反应较低,对细胞色素P450 3A(CYP3A)以外的药物代谢酶和转运蛋白诱导的定量预测及临床风险评估受到了阻碍。当一种诱导剂同时抑制CYP3A时,化合物药物相互作用(DDI)潜力在转化过程中的差距就尤为明显,这导致了CYP3A底物潜在净临床结果的不确定性。此外,与CYP3A共同调控的酶,如细胞色素P450 2C8(CYP2C8)、细胞色素P450 2C9(CYP2C9)、细胞色素P450 2C19(CYP2C19)、尿苷二磷酸葡萄糖醛酸基转移酶1A4(UGT1A4)和P-糖蛋白,可能会导致具有临床相关性的诱导作用,而通过与CYP3A底物进行临床相互作用研究无法降低这种风险。鉴定一种能够一致且明确地展示CYP3A以外的酶和转运蛋白诱导作用的体外模型,将为避免不必要的临床相互作用研究创造机会,进而在药物发现和开发工具库中具有很高的价值。TruVivo模型是一种新型的全人原代细胞模型,包含肝细胞以及基质和上皮饲养细胞。在这些研究中,TruVivo模型被验证为一种预测工具,可用于使用已知临床诱导剂对CYP2C8、CYP2C9、CYP2C19、CYP3A4、UGT1A4和P-糖蛋白诱导的临床风险评估。还对TruVivo在描绘涉及共同诱导剂/抑制剂的复杂DDI方面的效用进行了探索,结果显示出巨大的潜力,表明当使用临床相关水平的沉淀剂和目标药物时,原位DDI实验具有重要价值。这些数据突出了这种体外工具在模拟诱导作用和复杂DDI方面的潜力。意义声明:与CYP3A共同调控的酶和转运蛋白(包括CYP2C酶、尿苷二磷酸葡萄糖醛酸基转移酶和P-糖蛋白)诱导的临床风险评估,一直受到现有体外模型低动态反应的阻碍。这些研究旨在验证一种新型的全人肝细胞模型TruVivo作为基于诱导的DDI预测工具的有效性。此外,对该模型进行了原位预测复杂DDI的评估,结果显示在预测几种诱导剂/抑制剂对选择性和非选择性CYP3A底物的净临床结果方面具有潜力。