药品不良反应数据挖掘技术在药物警戒中的应用

    Application of Adverse Drug Reaction of Data Mining in Pharmacovigilance

    • 摘要: 随着信息技术的发展,医药电子数据海量增长,药品不良事件报告大幅增加,给药物警戒研究带来了巨大的挑战。而数据挖掘技术可以自动从真实世界数据中撷取药品不良反应风险信号。因此,对海量不良事件报告数据进行高效数据挖掘是实现药品不良反应自动检测的必要措施。本研究通过介绍当前主要的大型药品不良事件报告数据库和相关数据挖掘方法,对药品不良反应数据挖掘技术在药物警戒中的应用及其局限性进行综述,为药物警戒相关机构和科研人员提供参考。

       

      Abstract: With the development of information technology, the massive growth of pharmaceutical electronic data and the significant increase in the reports of drug adverse event reports have brought great challenges to pharmacovigilance research. Data mining techniques can automatically extract the risk signals of adverse drug reaction from real-world data. Therefore, efficient data mining of massive adverse event reporting is a necessary measure to realize the automatic detection of adverse drug reactions. By introducing the current major large-scale adverse drug event reporting databases and related data mining methods, this study reviews the application and limitations of adverse drug reaction data mining technology in pharmacovigilance, which provides reference for pharmacovigilance-related institutions and researchers.

       

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