人工智能:在药监信号管理中的应用
Jeffrey Warner1, Anaclara Prada Jardim1, Claudia Albera2
1Eli Lilly and Company, Indianapolis, IN, USA.
Pharmaceutical medicine
|April 21, 2025
概括
人工智能,包括机器学习和自然语言处理,在改善药物安全的药物监督信号管理方面显示出前景. 然而,透明度和道德考虑对于未来的进步至关重要.
科学领域:
- 药物监督和人工智能 药物监督和人工智能
- 药物安全监测监测 药物安全监测
- 制药数据科学 制药数据科学
背景情况:
- 药监督通过监测不良事件来确保药物安全.
- 信号管理是识别潜在的新药反应的关键.
- 人工智能 (AI) 提供自动化和高级分析.
研究的目的:
- 批判性地评估人工智能在药监信号管理中的应用.
- 描述AI在这个领域的好处,局限性和透明度.
- 为未来在药物安全方面整合人工智能提出最佳实践建议.
主要方法:
- 在PubMed和Embase对信号管理中的AI进行系统的文献搜索.
- 提取人工智能模型,参数,性能和数据集的数据.
- 分析常见的人工智能方法,如k-means,随机森林和梯度增强机.
主要成果:
- 机器学习算法,特别是随机森林和梯度增强,在信号检测方面表现优于传统方法.
- 自然语言处理 (NLP) 通常用于信号验证和评估.
- 方法透明度有所不同,对"黄金标准"控制数据集的使用有限.
结论:
- 人工智能,特别是机器学习和NLP,正在推动药监信号管理方面的创新.
- 这些技术可以加快药物安全的进展,当使用透明和道德.
- 需要进一步的研究来评估AI在各种治疗领域的适用性.
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