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人工新陈代谢研究中的人工智能和计算方法:一项全面的调查调查
Manzhan Zhang1, Yuxin Wan1, Jing Wang1
1Shanghai Key Laboratory of New Drug Design, State Key Laboratory of Bioreactor Engineering, School of Pharmacy, East China University of Science & Technology, Shanghai, 200237, China.
Journal of pharmaceutical analysis
|September 11, 2025
概括
人工智能 (AI) 和机器学习 (ML) 正在彻底改变人类新陈代谢研究以发现药物. 这些计算方法改善了对身体如何处理物质的预测,有助于精准医学的发展.
科学领域:
- 生物化学 生物化学
- 药理学 药理学是指药理学的学科.
- 计算生物学 计算生物学
背景情况:
- 了解人类新陈代谢对于药物开发和疾病研究至关重要.
- 代谢研究为药物的安全性,疗效和疾病机制的阐明提供了信息.
- 传统方法在预测复杂的代谢途径方面面临挑战.
研究的目的:
- 突出人工智能 (AI) 和机器学习 (ML) 在推动人类新陈代谢研究中的作用.
- 探索AI/ML在药物代谢预测建模中的应用.
- 讨论将人工智能驱动的见解集成到基因组规模代谢模型 (GEM) 中.
主要方法:
- 使用机器学习 (ML) 和深度学习 (DL) 技术进行预测建模.
- 应用计算方法来分析分子和奥米克水平的代谢途径.
- 将人工智能驱动的预测集成到基因组规模代谢模型 (GEM) 中.
主要成果:
- 人工智能/ML显著提高了预测人类新陈代谢的准确性.
- 计算方法有助于预测分子水平的新陈代谢.
- 与GEM集成提供了对代谢过程的奥米克水平洞察力.
结论:
- 人工智能和机器学习为加速药物发现和开发提供了强大的工具.
- 克服数据异质性等挑战是进一步进步的关键.
- 这项研究通过更好地了解新陈代谢,有助于精准医学的进步.
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