Kastrinou-Lampou Vlasia, Rodríguez-Pérez Raquel, Poller Birk, Huth Felix, Schadt Heiko S, Kullak-Ublick Gerd A, Arand Michael, Camenisch Gian
Pharmacokinetic Sciences, BioMedical Research, Novartis, Basel, Switzerland.
Preclinical Safety, BioMedical Research, Novartis, Basel, Switzerland.
Arch Toxicol. 2025 Jan;99(1):377-391. doi: 10.1007/s00204-024-03895-z. Epub 2024 Nov 14.
Drug-induced cholestasis (DIC) is recognized as a major safety concern in drug development, as it represents one of the three types of drug-induced liver injury (DILI). Cholestasis is characterized by the disruption of bile flow, leading to intrahepatic accumulation of toxic bile acids. Bile acid regulation is a multifarious process, orchestrated by several hepatic mechanisms, namely sinusoidal uptake and efflux, canalicular secretion and intracellular metabolism. In the present study, we developed a prediction model of DIC using in vitro inhibition data for 47 marketed drugs on nine transporters and five enzymes known to regulate bile acid homeostasis. The resulting model was able to distinguish between drugs with or without DILI concern (p-value = 0.039) and demonstrated a satisfactory predictive performance, with the area under the precision-recall curve (PR AUC) measured at 0.91. Furthermore, we simplified the model considering only two processes, namely reversible inhibition of OATP1B1 and time-dependent inhibition of CYP3A4, which provided an enhanced performance (PR AUC = 0.95). Our study supports literature findings suggesting a contribution not only from a single process inhibition, but a rather synergistic effect of the key bile acid clearance processes in the development of cholestasis. The use of a quantitative model in the preclinical investigations of DIC is expected to reduce attrition rate in advanced development programs and guide the discovery and development of safe medicines.
药物性胆汁淤积(DIC)被认为是药物研发中的一个主要安全问题,因为它是药物性肝损伤(DILI)的三种类型之一。胆汁淤积的特征是胆汁流动受阻,导致有毒胆汁酸在肝内蓄积。胆汁酸调节是一个多方面的过程,由几种肝脏机制协调,即窦状隙摄取和流出、胆小管分泌和细胞内代谢。在本研究中,我们利用47种上市药物对9种转运蛋白和5种已知调节胆汁酸稳态的酶的体外抑制数据,开发了一种DIC预测模型。所得模型能够区分有无DILI风险的药物(p值 = 0.039),并表现出令人满意的预测性能,精确召回曲线下面积(PR AUC)为0.91。此外,我们仅考虑两个过程简化了模型,即OATP1B1的可逆抑制和CYP3A4的时间依赖性抑制,这提供了更高的性能(PR AUC = 0.95)。我们的研究支持文献研究结果,表明胆汁淤积的发生不仅源于单一过程抑制,而且关键胆汁酸清除过程存在协同效应。在DIC的临床前研究中使用定量模型有望降低后期研发项目的淘汰率,并指导安全药物的发现和开发。