中国药物警戒 ›› 2020, Vol. 17 ›› Issue (5): 311-314.
DOI: 10.19803/j.1672-8629.2020.05.12

• 综述 • 上一篇    下一篇

大数据在药物警戒中的应用研究进展

李蒙, 胡豪, 吴霭琳   

  1. 澳门大学中华医药研究院,澳门 999078
  • 收稿日期:2019-10-10 修回日期:2020-06-22 出版日期:2020-05-15 发布日期:2020-05-13
  • 通讯作者: *吴霭琳,女,博士,药物相关政策法规研究。E-mail:carolinaung@um.edu.mo
  • 作者简介:李蒙,女,在读博士,药物经济与政策。

Big Data and Pharmacovigilance: Recent Developments and Applications

LI Meng, HU Hao, UNG Oi Lam Carolina   

  1. Institute of Chinese Medical Sciences, University of Macau, Macau 999078, China
  • Received:2019-10-10 Revised:2020-06-22 Online:2020-05-15 Published:2020-05-13

摘要: 目的 对国际上大数据技术在药物警戒中的应用和发展情况进行回顾总结,为完善我国药物警戒系统提供参考。方法 对官方文件以及近几年来国内外相关文献中报道的大数据在药物警戒中的应用进行整理、分析与归纳,并以药物性肝损伤为案例进行分析。结果 越来越多的国家逐步开始建立药物警戒的数据库、协作网络及联盟,其中大数据技术发挥了很大的作用,不仅用于药品不良事件的监测和分析,还可以形成辅助药物警戒的预测模型,对不良反应进行预警和防范。结论 药物警戒的发展模式已经发生改变,未来大数据技术在药物警戒中的作用会更加显著,我国可以借鉴国际发展经验,积极探索适合我国的药物警戒发展道路。

关键词: 药物警戒, 大数据, 真实世界数据, 药物性肝损伤

Abstract: ObjectiveTo review and summarize the recent developments and applications of big data technology in pharmacovigilance in order to shed light on possible measures for improving the identification of adverse drug events in China. Methods Official documents from developed countries and recent literature were searched to identify, analyze and summarize the status quo and future developments of big data applications in pharmacovigilance. To elucidate the findings, drug-induced liver injury was used as a case study. Results An increasing number of countries are establishing registries and databases, collaboration networks and alliances to support the big data approach to pharmacovigilance. Big data has played a big role not only in the monitoring and analysis of adverse drug events, but also in the establishment of predictive models of adjuvant pharmacovigilance to predict and prevent potential adverse reactions. Conclusion The development paradigm of pharmacovigilance has changed, and the role of big data in pharmacovigilance will become more prominent in the future. For China, we can learn from other countries to make more informed decisions on the strategies for advancing the pharmacovigilance system.

Key words: pharmacovigilance, big data, real world data, drug-induced liver injury

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