使用真实世界的数据进行疫苗安全研究的当前方法:发表文献的系统审查
Juan Joanne Wu1, Manfred Hauben2, Muhammad Younus1
1Safety Surveillance Research, Worldwide Medical and Safety, Pfizer Inc, New York, NY.
Clinical therapeutics
|August 14, 2024
概括
现实数据 (RWD) 方法的进步提高了疫苗安全监测. 新的数字技术和分析方法改善了疫苗不良事件的检测和评估,增强了公众的信心.
科学领域:
- 疫苗安全研究疫苗安全研究
- 药物监督 药物监督 药物监督
- 现实世界数据 (RWD) 分析分析.
背景情况:
- 使用真实世界数据 (RWD) 的营销后观察性研究对于疫苗安全证据和公众信任至关重要.
- 对当前的方法,技术进步及其在疫苗安全研究中的局限性进行系统审查.
研究的目的:
- 在批准后的疫苗安全研究中介绍当前的研究方法.
- 突出技术进步,增强疫苗安全研究资源和能力.
- 总结现有的疫苗安全研究方法的优点和局限性.
主要方法:
- 从2019年1月1日到2022年12月31日进行全面的PubMed搜索.
- 根据设计,国家,疫苗,数据源和人口,总结了符合条件的研究.
- 深入审查代表新设计,分析方法和数据收集方法的精选研究.
主要成果:
- 在977篇选的文章中,审查了135篇文章.
- 科学方法,数字技术和分析技术的进步显著改善了基于RWD的疫苗安全研究.
- 接近实时监控,自控设计,人工智能,NLP和社交媒体分析提高了信号检测和结果的准确性.
结论:
- 对疫苗安全研究的RWD方法的持续开发是必不可少的.
- 未来的疫苗安全研究将整合数字技术,链接RWD网络,机器学习和先进分析.
- 这些综合方法将使快速和强大的现实世界安全信息生成成为可能,特别是在罕见事件中.
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