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中国临床药理学与治疗学 ›› 2021, Vol. 26 ›› Issue (8): 923-930.doi: 10.12092/j.issn.1009-2501.2021.08.007

• 药代动力学:技术与拓展 • 上一篇    下一篇

肝毒性风险的体外早期发现和预测

刘文静1,2,武之涛1,2,潘国宇1,2   

  1. 1南京中医药大学,南京 210000,江苏;2中国科学院上海药物研究所安全评价研究中心,上海 201203
  • 收稿日期:2021-06-23 修回日期:2021-07-13 出版日期:2021-08-26 发布日期:2021-09-10
  • 通讯作者: 潘国宇,男,博士,研究员,博士生导师,研究方向:药物诱导的肝毒性及新型肝样细胞模型的建立和应用。 Tel: 021-20231000#1715 E-mail: gypan@simm.an.cn
  • 作者简介:刘文静,女,硕士研究生,研究方向:肝保护药物的筛选和评价。 Tel: 021-20231000#1715 E-mail: 1399246329@qq.com 武之涛,共同第一作者,男,博士研究生,研究方向:新型肝样细胞模型的建立和评价。 Tel: 021-20231000#1715 E-mail: zhitaowu@simm.ac.cn
  • 基金资助:
    国家自然科学基金(81872927)

Early dectection and prediction hepatotoxic risk in vitro

LIU Wenjing 1,2, WU Zhitao 1,2, PAN Guoyu 1,2   

  1. 1 Nanjing University of Chinese Medicine, Nanjing 210000, Jiangsu, China; 2 Center for Drug Safety Evaluation and Research (CDSER), Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
  • Received:2021-06-23 Revised:2021-07-13 Online:2021-08-26 Published:2021-09-10

摘要: 药物诱导的肝损伤(DILI)是临床研究中药品研发失败和药品上市后撤回的主要原因。动物模型对药物诱导的肝损伤风险进行预测,因为物种差异,准确性较差。因此,有效、快速的人源性体外肝毒性预测模型一直受到学术界和工业界的重视。本文综述了常用的体外肝毒性预测模型,以及对肝细胞培养方法的改进,尤其是共培养体系和三维培养系统可以有效提高体外肝毒性预测模型的准确性,也为临床药物肝毒性机制研究提供参考。 

关键词: 肝毒性, 药物诱导的肝损伤, 体外肝脏替代模型

Abstract: Drug-induced liver injury (DILI) is a major cause of drug failure in clinical trial and market withdrawal. Animal models are utilized to predict the risk of drug-induced liver injury. However, due to species differences, the accuracy of animal models is poor. Multiple human-derived hepatotoxic prediction models have been developed to assess this potential risk. This article reviews commonly used in vitro hepatotoxic models, as well as the latest improvement of hepatocyte culture protocols, especially hepatic co-culture system and 3D culture system in order to improve the accuracy of hepatotoxic risk prediction, which may also guide the liver toxicity mechanistic investigation in clinic. 

Key words: hepatotoxicity, drug-induced liver injury, alternative models of liver 

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