药物发现的人工智能:我们还在吗?
Catrin Hasselgren1, Tudor I Oprea2,3
1Safety Assessment, Genentech, Inc., South San Francisco, California, USA.
Annual review of pharmacology and toxicology
|September 22, 2023
概括
人工智能 (AI) 通过优化治疗和降低成本来加速药物发现. 跨疾病,目标和模式的AI整合是有效的小分子药物开发的关键.
科学领域:
- 生物技术是生物技术.
- 计算化学计算化学
- 药理学 药理学是指药理学的学科.
背景情况:
- 药物发现越来越多地采用数据科学,信息学和人工智能 (AI).
- 人工智能有可能加速治疗开发,降低成本,并尽量减少动物试验.
- 优化药理动力学,药理动力学和临床结果对于成功的药物发现至关重要.
研究的目的:
- 审查人工智能在药物发现中的应用.
- 专注于人工智能在跨疾病,目标和治疗方式的小分子药物开发中的作用.
- 要突出人工智能技术改变药物发现管道.
主要方法:
- 关于AI在药物发现中的当前文献的综述.
- 讨论人工智能技术,包括生成化学,机器学习和多属性优化.
- 分析AI对药物发现管道不同阶段的影响.
主要成果:
- 人工智能技术使得几种化合物能够进入临床试验.
- 人工智能正在被应用于优化药物特性,以获得更好的药理动力学和药理动力学.
- 生成化学和机器学习是推动创新的关键人工智能工具.
结论:
- 人工智能正在改变药物发现,吸引了各种利益相关者的重大兴趣.
- 解决可复制性危机需要仔细审查信息和坚实的基础真相.
- 实现人工智能的全部潜力需要在药物发现管道的后期阶段进行人类监督.
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