人工智能驱动的可编程虚拟人类,以人类生理学为基础的药物发现
You Wu1, Philip E Bourne2, Lei Xie3
1School of Pharmacy and Pharmaceutical Sciences & Center for Drug Discovery, Northeastern University, Boston, MA, USA; Ph.D. Program in Computer Science, The Graduate Center, The City University of New York, New York, NY, USA.
Drug discovery today
|October 10, 2025
概括
人工智能 (AI) 能够为药物发现提供虚拟的人类模型,预测化合物的有效性和安全性. 这种新的范式超越了数字化实验,以测试新型药物在中进行早期优化.
科学领域:
- 药理学 药理学是指药理学的学科.
- 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:
- 目前在药物发现中的人工智能 (AI) 可以将实验数字化,但无法预测临床结果.
- 药理学数字双胞胎仅限于晚期发育阶段,不能弥合早期的翻译差距.
- 人工智能的真正潜力涉及虚拟实验,用于在人类模型中测试新型化合物.
研究的目的:
- 用人工智能驱动的虚拟人类在基于生理学的药物发现中引入新的范式.
- 为了能够在早期评估和优化化合物的疗效和安全性.
- 为了利用人工智能和omics在in silico药物测试中的进步.
主要方法:
- 开发代表可编程虚拟人类的动态,多尺度模型.
- 整合人工智能 (AI),高吞吐量测试,单细胞和空间奥米克.
- 创建基于生理学的模型,用于in silico化合物评估.
主要成果:
- 建立一个新的范式,以生理学为基础的药物发现.
- 使虚拟实验能够在人类模型中测试新型化合物.
- 促进早期评估化合物的疗效和安全性.
结论:
- 人工智能驱动的虚拟人类代表了药物发现的变革性方法.
- 这种方法可以进行in silico测试,克服当前实验数字化的局限性.
- 这种方法有望在药物开发管道的早期优化化合物的疗效和安全性.
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