评估基于人工智能的模型信息化药物开发 (MIDD) 的影响:比较性审查
Bingyu Mao1,2, Yue Gao1, Christine Xu1
1Sanofi, Morristown, NJ, USA.
The AAPS journal
|June 2, 2025
概括
人工智能和机器学习 (AI / ML) 增强基于模型的药物开发 (MIDD) 以获得更安全,更有效的疗法. 虽然有希望,但需要标准化指标和监管指南,以便在药物发现中实现最佳的AI整合.
科学领域:
- 药理计量和药物开发研究
- 人工智能在医学中的应用
- 监管科学 监管科学
背景情况:
- 基于模型的药物开发 (MIDD) 对于创造安全有效的个性化疗法至关重要.
- 人工智能和机器学习 (AI/ML) 在药物开发中的应用正在迅速增加.
- 人工智能/ML集成为优化剂量,临床试验设计和疗效/安全评估提供了潜力.
研究的目的:
- 与传统方法相比,系统地评估基于AI的MIDD方法的影响.
- 将监管视角纳入对AI在药物开发中的评估.
- 确定当前AI在MIDD的局限性和未来研究方向.
主要方法:
- 在PubMed上使用五个医学主题标题 (MeSH) 术语进行了系统的文献搜索.
- 在分析中包括了67项相关研究.
- 综合了现有研究的发现,混合了监管观点.
主要成果:
- 人工智能模型表明,在药物开发的各个阶段都有改善MIDD的潜力.
- 人工智能/ML可以增强临床试验中的决策过程.
- 确定的局限性包括缺乏标准化的评估指标和基于AI的MIDD的监管准则.
结论:
- 人工智能/ML具有很大的潜力,可以推进基于模型的药物开发.
- 需要进一步的研究来优化和整合基于AI的方法.
- 对指标和监管框架的标准化对于在药物开发中广泛采用人工智能至关重要.
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