人工智能用于阿尔茨海默病药物发现和开发
Yunguang Qiu1, Feixiong Cheng2
1Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA. Electronic address: https://twitter.com/YunguangQiu.
Current opinion in structural biology
|February 9, 2024
概括
人工智能 (AI) 通过分析多omics数据来加速阿尔茨海默病 (AD) 药物发现. 虚拟查和药物重定位等人工智能方法为开发新的AD疗法提供了有希望的策略.
科学领域:
- 神经科学是一个神经科学.
- 计算生物学 计算生物学
- 药理学 药理学是指药理学的学科.
背景情况:
- 阿尔茨海默病 (AD) 的病理生理学和分子机制仍然复杂,阻碍了有效的治疗开发.
- 精准医学方法,整合遗传学和多omics数据,对于理解AD和相关痴呆症至关重要.
- 人工智能 (AI) 提供了强大的工具来导航复杂的生物数据,用于药物发现.
研究的目的:
- 审查用于阿尔茨海默病 (AD) 药物发现和开发的AI驱动的方法.
- 突出AI在了解AD病理生理学和推进精准医学方面的潜力.
- 讨论新兴的AD目标和AI应用在神经退行性疾病的药物发现中.
主要方法:
- 总结人工智能驱动的方法,包括新药设计,虚拟查和药物向相互作用预测.
- 分析人类遗传学和多omics数据,以确定新的AD目标.
- 审查最近基于AI的技术及其在AD药物发现中的应用.
主要成果:
- 人工智能引导的药物发现显示出了解AD病理生理学的潜力,并使精准医学成为可能.
- 以人工智能为基础的药物重新定位是一种引人注目的策略,用于识别AD现有药物的新指示.
- 来自遗传学和多omics数据的新兴AD目标正在使用AI进行探索.
结论:
- 人工智能对了解AD和开发新疗法作出了重大贡献.
- 基于人工智能的药物发现,特别是重定向,为AD治疗提供了一个有前途的途径.
- 未来的方向包括应对挑战,并扩大对AD和其他神经退行性疾病的AI应用.
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