领先的人工智能驱动药物发现平台:2025年景观和全球前景
Mahendiran Dharmasivam1, Busra Kaya1, Adedoyin Akinware1
1Centre for Cancer Cell Biology and Drug Discovery, Institute for Biomedicine and Glycomics, Griffith University, Southport, Queensland, Australia.
Pharmacological reviews
|December 13, 2025
概括
人工智能 (AI) 正通过加快时间表和降低成本来彻底改变药物发现. 人工智能设计的疗法正在通过临床试验取得进展,展示了该技术日益增长的临床实用性和重塑药理学的潜力.
科学领域:
- 药理学和药物发现
- 人工智能在医学中的应用
- 计算化学的计算化学
背景情况:
- 人工智能 (AI) 从理论概念过渡到医学中的实际应用.
- 人工智能设计的疗法目前正在各种医疗领域进行人类临床试验.
- 人工智能的整合正在显著影响药物发现和开发过程.
研究的目的:
- 为了批判性地比较五个领先的AI驱动药物发现平台.
- 突出AI药物发现领域的关键进展和新兴参与者.
- 讨论人工智能在重塑制药研发方面的更广泛影响.
主要方法:
- 综述和比较生成化学,现象学第一系统,集成管道,知识图重新定位和物理加机器学习设计.
- 分析最近的临床试验结果和行业合并.
- 检查新兴的人工智能平台及其贡献.
主要成果:
- 在异常性肺纤维化中,Insilico Medicine的ISM001-055的IIa期阳性结果.
- 在Recursion-Exscientia合并后,创建了一个集成的端到端药物发现平台.
- 施罗丁格的基于物理的设计导致扎索西提尼布 (TAK-279) 进入第三阶段试验.
- 像Insitro,Isomorphic Labs,Atomwise和XtalPi这样的新兴平台展示了该领域的扩张.
结论:
- 人工智能正在缩短药物发现时间表,降低消耗率,并扩大治疗设计的可能性.
- 监管机构正在为药物开发中的AI制定框架,解决透明度,偏见和数据隐私问题.
- 人工智能驱动的机器人和混合物理-人工智能策略将加速翻译和降低药物开发风险.
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