Suppr超能文献

从危害到风险优先级排序:使用基于生理的动力学建模预测药物性胆汁淤积的案例研究。

From hazard to risk prioritization: a case study to predict drug-induced cholestasis using physiologically based kinetic modeling.

机构信息

Division of Toxicology, Wageningen University and Research, Wageningen, The Netherlands.

出版信息

Arch Toxicol. 2024 Sep;98(9):3077-3095. doi: 10.1007/s00204-024-03775-6. Epub 2024 May 17.

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 K 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 K. 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

胆汁淤积症的特征是肝脏中胆汁酸的积累。只有一小部分暴露于药物的个体才会出现胆汁淤积症的临床表现。本研究旨在开发一种新的方法学(NAM),以预测药物诱导的胆汁淤积症,这是由于药物诱导的肝胆汁酸外排抑制和随之而来的胆汁酸积累所致。为此,通过通用的基于生理的药代动力学(PBK)药物模型预测了一组药物在肝脏中的浓度。它们对肝胆汁酸外排的影响被纳入了胆汁酸的 PBK 模型中。预测的胆汁酸积累被用作药物致胆汁淤积能力的衡量标准。所选药物已知在原代悬浮培养肝细胞测定中抑制肝胆汁酸外排,并按常见、罕见或无胆汁淤积发生率进行分类。常见的胆汁淤积药物包括阿托伐他汀、氯丙嗪、环孢素、格列美脲、酮康唑和利托那韦。这些药物的胆汁淤积发生率似乎不能仅通过其对肝胆汁酸外排的抑制作用的 K 值来充分预测,而是可以通过在治疗剂量水平以上,在 PBK 模型中预测的内部肝药物浓度 AUC 来预测。药物清除率较慢、胆汁酸池较大、胆汁盐输出泵(BSEP)丰度降低或给予高于治疗剂量水平的患者,预计发生药物诱导的胆汁淤积症的风险更高。结果为使用基于 PBK 的 NAM 进行胆汁淤积症风险优先排序提供了原理验证,这是由于转运体抑制和确定个体风险因素所致。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1298/11324677/d360d3f0eec8/204_2024_3775_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验