人工智能是否重塑了药物发现,还是还有很长的路要走?
Karthik Shree Harini1, Devaraj Ezhilarasan1
1Department of Pharmacology, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, India.
Drug development research
|March 2, 2026
概括
人工智能 (AI) 通过提高效率和降低成本来加速早期药物发现. 然而,人工智能仍然是一个支持性工具,因为数据,解释性和生物复杂性的挑战阻止了完全由人工智能产生的药物批准.
科学领域:
- 制药科学 制药科学
- 计算生物学 计算生物学
- 药物发现 药物发现 药物发现
背景情况:
- 传统的药物发现是漫长的,昂贵的和低效的.
- 由于计算和数据的进步,人工智能 (AI) 的采用在2010年代激增.
- 人工智能为简化药物开发管道提供了潜在的解决方案.
研究的目的:
- 评估人工智能在现代药物发现中的影响和局限性.
- 确定阻碍人工智能发现药物的全面监管批准的关键挑战.
- 评估AI作为辅助工具与独立解决方案的作用.
主要方法:
- 在药物发现阶段对人工智能应用的审查:目标识别,打击发现,领先优化.
- 人工智能技术的分析:分子性质预测,蛋白质结构建模,NLP,ADME/毒素预测.
- 对人工智能引导分子的临床试验进展和监管批准状况的审查.
主要成果:
- 人工智能提高了早期药物发现的效率并降低了成本.
- 几种人工智能引导的分子显示出有前途的早期临床试验成功.
- 迄今为止,没有一种仅由AI制造的药物获得了完全的监管批准.
结论:
- 人工智能显著加速早期药物发现,但面临着局限性.
- 挑战包括数据质量,模型可解释性和生物复杂性.
- 人类专业知识和实验验证对于成功的药物开发至关重要.
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