关键词: Adverse outcome pathway Bile acids and salts Cholestasis Physiologically based kinetic (PBK) modeling

Mesh : Cholestasis / chemically induced metabolism Humans Bile Acids and Salts / metabolism Models, Biological Hepatocytes / drug effects metabolism Risk Assessment Liver / metabolism drug effects Cells, Cultured Chemical and Drug Induced Liver Injury ATP Binding Cassette Transporter, Subfamily B, Member 11 / metabolism antagonists & inhibitors

来  源:   DOI:10.1007/s00204-024-03775-6   PDF(Pubmed)

Abstract:
Cholestasis is characterized by hepatic accumulation of bile acids. Clinical manifestation of cholestasis only occurs in a small proportion of exposed individuals. The present study aims to develop a new approach methodology (NAM) to predict drug-induced cholestasis as a result of drug-induced hepatic bile acid efflux inhibition and the resulting bile acid accumulation. To this end, hepatic concentrations of a panel of drugs were predicted by a generic physiologically based kinetic (PBK) drug model. Their effects on hepatic bile acid efflux were incorporated in a PBK model for bile acids. The predicted bile acid accumulation was used as a measure for a drug\'s cholestatic potency. The selected drugs were known to inhibit hepatic bile acid efflux in an assay with primary suspension-cultured hepatocytes and classified as common, rare, or no for cholestasis incidence. Common cholestasis drugs included were atorvastatin, chlorpromazine, cyclosporine, glimepiride, ketoconazole, and ritonavir. The cholestasis incidence of the drugs appeared not to be adequately predicted by their Ki for inhibition of hepatic bile acid efflux, but rather by the AUC of the PBK model predicted internal hepatic drug concentration at therapeutic dose level above this Ki. People with slower drug clearance, a larger bile acid pool, reduced bile salt export pump (BSEP) abundance, or given higher than therapeutic dose levels were predicted to be at higher risk to develop drug-induced cholestasis. The results provide a proof-of-principle of using a PBK-based NAM for cholestasis risk prioritization as a result of transporter inhibition and identification of individual risk factors.
摘要:
胆汁淤积的特征在于胆汁酸的肝积累。胆汁淤积的临床表现仅发生在一小部分暴露个体中。本研究旨在开发一种新的方法方法(NAM)来预测药物诱导的胆汁淤积,这是由于药物诱导的肝胆汁酸外排抑制和由此产生的胆汁酸积累。为此,一组药物的肝脏浓度通过基于生理学的动力学(PBK)药物模型预测.它们对肝胆汁酸流出的影响被纳入胆汁酸的PBK模型。预测的胆汁酸积累被用作药物胆汁淤积效力的量度。已知所选药物在原代悬浮培养肝细胞的测定中抑制肝胆汁酸流出,罕见,或无胆汁淤积发生率。常见的胆汁淤积药物包括阿托伐他汀,氯丙嗪,环孢菌素,格列美脲,酮康唑,还有Ritonavir.药物的胆汁淤积发生率似乎不能通过其抑制肝胆汁酸流出的Ki来充分预测,而是通过PBK模型的AUC预测治疗剂量水平高于此Ki的内部肝脏药物浓度。药物清除较慢的人,一个更大的胆汁酸池,胆盐出口泵(BSEP)丰度降低,或给予高于治疗剂量水平的药物发生胆汁淤积的风险较高。结果提供了使用基于PBK的NAM进行胆汁淤积风险优先排序的原理证明,这是转运蛋白抑制和个体风险因素识别的结果。
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