药物发现和开发中的因果推理.
Tom Michoel1, Jitao David Zhang2
1Computational Biology Unit, Department of Informatics, University of Bergen, Postboks 7803, 5020 Bergen, Norway.
Drug discovery today
|August 17, 2023
概括
使用数据和人工智能的方法因果推断可以通过减少偏差来改善药物发现. 本文介绍了因果推理及其在开发新药中的应用.
科学领域:
- 药物的发现和开发.
- 因果推理的原因推理.
- 机器智能是机器的智能.
背景情况:
- 药物发现从根本上依赖于建立因果关系.
- 因果推理是一种新兴的方法,它使用数据和人工智能来改善决策.
- 目前对因果推理在药物发现中的理解和应用仍然有限.
研究的目的:
- 提供对因果推理的非技术介绍.
- 审查因果推理在药物发现中的近期应用.
- 讨论在制药行业采用因果推理的机遇和挑战.
主要方法:
- 对因果推理应用的文献综述.
- 因果推理原则的概念解释.
- 讨论在药物发现中的实际实施.
主要成果:
- 因果推理提供了一个框架,以减少药物发现中的认知偏见.
- 应用涵盖了药物开发价值链的各个阶段.
- 采用需要克服概念理解和实际整合的挑战.
结论:
- 因果推理对提高药物发现和开发具有显著的前景.
- 更广泛的采用需要消除概念的神秘性,并解决实施障碍.
- 整合因果语言可以导致更强大,更有效的药物创新.
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