药监知识图:一个范围审查
Manfred Hauben1, Mazin Rafi2, Ibrahim Abdelaziz3
1Department of Family and Community Medicine, New York Medical College, Valhalla, New York; Truliant Consulting, Baltimore, Maryland.
Clinical therapeutics
|July 9, 2024
概括
知识图表显示出在药物监测中预测药物不良反应的前景. 需要进一步的研究来比较它们的性能与现有方法,并建立最佳实践.
科学领域:
- 药监和药物安全 药监和药物安全
- 数据科学和人工智能数据科学和人工智能
- 生物医学信息学 生物医学信息学
背景情况:
- 药监系统对于监测市场后药物安全性至关重要.
- 检测药物不良反应 (ADR) 的传统方法存在局限性.
- 知识图为结构化数据的表示和分析提供了一种新的方法.
研究的目的:
- 批判性地评估知识图在药物监督中的作用和附加值.
- 评估知识图在预测药物不良反应方面的能力.
- 了解药监信号检测中的知识图表应用的当前环境.
主要方法:
- 进行了对同行评审出版物的系统范围审查.
- 数据提取侧重于目标,技术,数据源,方法和性能指标.
- 包括的研究报告使用知识图表来检测药监信号.
主要成果:
- 47篇同行评审的文章被纳入了审查中.
- 应用知识图表来检测/预测单一药物的副作用和药物相互作用.
- 报告的绩效指标是可变的,与已确定的方法进行的比较有限.
结论:
- 知识图有潜力提高药物监督中的预测信号检测.
- 需要进行进一步的研究,对ADR进行强大的参考集.
- 对传统药物监督方法进行比较研究是必要的,以确定最佳实践.
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