下一代老年疗法:针对衰老和与年龄有关的疾病的AI/ML驱动的策略
Prashanth S Javali1, Ashish Kumar1, Subhajit Sarkar1
1Department of Biotechnology, School of Biosciences & Technology, Vellore Institute of Technology, Vellore, TN, India.
Advances in pharmacology (San Diego, Calif.)
|July 27, 2025
概括
针对衰老细胞的老年疗法为衰老和相关疾病提供了新的治疗方法. 像机器学习这样的创新加速了这些老年治疗药物的开发,以改善健康.
科学领域:
- 地质科学是地球科学.
- 药理学 药理学是指药理学的学科.
- 生物技术是生物技术.
背景情况:
- 衰老细胞驱动衰老和与年龄相关的疾病 (ARD),如癌症和神经退行性疾病.
- 老年治疗药物 (STs),包括老年化药物和老年制剂,向这些细胞.
- 当前的挑战包括缺乏生物标志物和有效药物.
研究的目的:
- 审查针对衰老细胞,它们的分子通路和免疫相互作用的老年疗法.
- 突出人工智能 (AI),机器学习 (ML) 和深度学习 (DL) 在发现和推进科学技术方面的作用.
- 讨论如何将临床前发现转化为临床应用.
主要方法:
- 对针对衰老细胞,SASP和免疫细胞分子通路的老年疗法药物的审查.
- 探索用于ST发现的AI/ML/DL工具 (例如,随机森林,支持矢量机,神经网络).
- 对ST发展的临床前和临床数据的分析.
主要成果:
- 老年治疗药物在打击衰老和ARD方面表现有前途.
- 人工智能/ML/DL工具可以加快STs的发现和翻译.
- 整合omics,纳米载体和基于细胞的疗法是关键的创新.
结论:
- 老年疗法代表了老年科学的一个重大进步.
- 尽管存在数据挑战,AI/ML/DL仍具有加速老疗法开发的巨大潜力.
- 进一步的研究对于克服翻译障碍和促进长寿至关重要.
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