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通过人工智能推进CAR T细胞疗法:机遇和挑战

Fabio Luciani¹, Arman Safavi¹, Puneeth Guruprasad^2,3

¹Systems Immunology and Immunogenomics, School of Biomedical Sciences, UNSW Sydney, Sydney, Australia.

Blood cancer discovery

|March 28, 2025

概括

人工智能 (AI) 可以通过优化各个阶段来改善仿真抗原受体T细胞疗法. 标准化数据存储库对于人工智能克服数据异质性和患者隐私等挑战至关重要.

科学领域:

免疫治疗是一种免疫疗法.
计算生物学计算生物学
生物技术是生物技术.

背景情况:

化学抗原受体T细胞 (CAR T) 疗法在癌症治疗中表现有前途.
在优化CART疗法的疗效和可访问性方面仍然存在重大挑战.
人工智能 (AI) 为应对这些挑战提供了一个变革性的机会.

研究的目的:

探索人工智能的潜力,以增强CAR T细胞治疗的各个方面.
确定将AI整合到CAR T细胞治疗工作流程中的关键步骤和要求.
突出阻碍人工智能实施的关键障碍,并提出解决方案.

主要方法:

对当前生物和医学研究中人工智能应用的审查.
分析CAR T细胞治疗管道从目标识别到临床决策.
识别人工智能模型培训的数据要求和挑战.

主要成果:

人工智能可以优化目标识别,矢量设计和制造流程.
人工智能能够实现个性化,数据驱动的临床决策,以改善患者的治疗结果.
解决数据异质性和患者隐私问题对于人工智能进步至关重要.

结论:

人工智能集成具有重大潜力,可以彻底改变CAR T细胞疗法.
开发标准化,全面的数据存储库是关键的下一步.
克服与数据相关的障碍将释放AI在免疫治疗中的全部潜力.

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