首页|基于不良反应监测大数据的药品安全风险发现与识别策略

基于不良反应监测大数据的药品安全风险发现与识别策略

Discovery and identification strategy for drug safety risks based on big data monitoring of adverse reactions

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目的 探索如何从国内外海量的中西药不良反应报告中快速发现与精准识别药物安全风险,并进行科学有效地预测与防控.方法 以药物性肝损伤数据为例,针对上市后药品安全风险的发现、评价、确证和防控策略进行论述.结果 初步探索建立"不良反应监测大数据发现—多模型识别评析—病证毒理学验证"一体化应对策略和方法体系,并成功应用于药物性肝损伤的识别和评析.结论 该策略为药物安全性评价领域的持续发展和创新提供了新的视角,也为保障公众安全用药和促进中西药产业的健康发展提供了技术支撑.
Objective To explore how to quickly discover and accurately identify drug safety risks from a vast number of adverse reaction reports from domestic and foreign Chinese and Western medicines.The aim is also to make scientific and effective predictions and control measures for these risks.Methods Drug-induced liver injury data was taken as an example,and the process of discovering,evaluating,confirming,and controlling risks associated with drugs were discussed.Results A preliminary exploration was conducted,leading to the establishment of an integrated strategy and method system for"large-scale adverse reaction monitoring and discovery-multi-model recognition and analysis-disease-symptom-toxicology verification."This system has been successfully applied in identifying and analyzing drug-induced liver injury.Conclusion This strategy offers a fresh perspective for the continuous development and innovation of drug safety evaluation.It also provides technical support for ensuring public safety in medication and promoting the healthy development of the Chinese and Western medicine industry.

drug adverse reactionsmonitoringbig datarisk discoverydata analysismachine learning

高云娟、赵旭、白天凯、柏兆方、王伽伯、宋海波、肖小河

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中国人民解放军总医院第五医学中心,全军中医药研究所,北京 100039

成都中医药大学药学院,四川 成都 611137

首都医科大学中医药学院,北京 100069

国家药品监督管理局药品评价中心,国家药品监督管理局药物警戒研究与评价重点实验室,北京 100076

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药品不良反应 监测 大数据 风险发现 数据分析 机器学习

国家自然科学基金资助项目国家自然科学基金资助项目国家中医药管理局中医药创新团队及人才支持计划项目北京市杰出青年科学基金项目

8172100282230118ZYYCXTD-C-202005JQ21026

2024

中国药物警戒
国家药品监督管理局药品评价中心(国家药品不良反应监测中心)

中国药物警戒

CSTPCD
影响因子:1.105
ISSN:1672-8629
年,卷(期):2024.21(1)
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