摘要
药物警戒是药品全生命周期安全保障的核心环节,承担着监测、识别、评估和控制药品不良事件及守护公众健康的重要使命。2019年,新修订的《中华人民共和国药品管理法》将药物警戒制度正式确立为我国药品管理的基本制度之一;2021年,《药物警戒质量管理规范》进一步细化了监管要求。然而,现有药物警戒信息化系统仍面临不良反应报告量激增、多源数据整合困难、监测模式被动滞后等发展瓶颈。人工智能(AI)技术的突破性发展为破解药物警戒转型困境提供了重要机遇。本文阐述了AI赋能药物警戒的技术创新路径,包括多源多模态数据融合、规避违规风险、降低技术应用门槛等;分析了AI在报告自动生成、信号筛查、审核校验和风险评估等药物警戒场景的实际应用价值;探讨了AI在数据质量、模型效能、人员协同、成本控制和伦理规范等方面面临的实际挑战;最后从数据治理、技术优化、能力建设、成本管控和伦理规范5个维度对未来AI技术与药物警戒融合的发展方向提出了展望。
Pharmacovigilance is the core component of ensuring the safety of drugs throughout their entire lifecycle,undertaking the important mission of monitoring,identifying,evaluating and controlling adverse drug events,and safeguarding public health.In 2019,the newly revised Drug Administration Law of the People′s Republic of China officially established the pharmacovigilance system as one of the basic systems for drug management in China.In 2021,Good Pharmacovigilance Practice further clarifies regulatory requirements.However,existing information system of pharmacovigilance still faces bottlenecks such as a surge in adverse reaction reports,difficulties in integrating multisource data,and passive and lagging monitoring modes.The breakthrough development of artificial intelligence(AI)technology provides an important opportunity to overcome these transformation challenges in pharmacovigilance.In this paper,the technological innovation pathways of AI-empowered pharmacovigilance,including multisource and multimodal data integration,avoidance of violation risks,and reduction of technical application thresholds are elaborated;the application value of AI in pharmacovigilance scenarios such as automated report generation,signal screening,audit verification,and risk assessment is analyzed;the practical challenges that AI faces in terms of data quality,model efficiency,human-machine collaboration,cost control,and ethical standards are explored,and at last,a vision for the future development direction of the integration of AI technology and pharmacovigilance from 5 dimensions are proposed,including data governance,technological optimization,capacity building,cost control,and ethical norms.
作者
崔晓辉
王天琳
Cui Xiaohui;Wang Tianlin(Department of Pharmacy,Xuanwu Hospital,Capital Medical University,National Clinical Research Center for Geriatric Diseases,Beijing 100053,China;Department of Pharmacy,Medical Supplies Center of Chinese PLA General Hospital,Beijing 100853,China)
出处
《药物不良反应杂志》
2026年第1期10-14,共5页
Adverse Drug Reactions Journal
关键词
药物警戒
人工智能
药品质量管理
不良事件
信号检测
Pharmacovigilance
Artificial intelligence
Drug quality control
Adverse events
Signal detection
