人工智能增强的协同化疗-免疫疗法:从机械学见解到临床翻译
Sajid Muhammad1, Bing Li1, Wenda Zhong1
1Institute of Drug Discovery Technology, Ningbo University, Ningbo 315211, China.
Critical reviews in oncology/hematology
|December 1, 2025
概括
化疗免疫疗法将化疗与免疫检查点抑制剂 (ICI) 结合起来,以增强抗瘤效果. 人工智能 (AI) 正在出现,以克服抵抗力并优化这些强大的癌症治疗方法.
科学领域:
- 在瘤学瘤学.
- 免疫学 免疫学 免疫学
- 人工智能的人工智能
背景情况:
- 化疗免疫疗法将化疗与免疫检查点抑制剂 (ICI) 结合起来,以获得协同作用的抗瘤效应.
- 挑战包括治疗耐药性,与免疫相关的不良事件,以及缺乏预测生物标志物.
- 本综述的重点是利用人工智能 (AI) 优化化疗免疫疗法.
研究的目的:
- 综合审查化学免疫治疗的机制基础,临床应用和挑战.
- 突出AI在优化化疗-免疫疗法组合中的作用.
- 讨论人工智能驱动的方法来识别协同作用的药物对和预测治疗反应.
主要方法:
- 对化学免疫疗法和瘤学中的AI现有文献的审查.
- 讨论化疗诱导的免疫细胞死亡 (ICD) 和瘤微环境 (TME) 改造.
- 探索人工智能技术,如多omics,放射学和深度学习,用于生物标志物发现和治疗优化.
主要成果:
- 化疗诱导的ICD,抗原释放和TME重塑可以增强ICI的疗效.
- 人工智能方法有助于识别协同作用的药物对,预测反应和患者分层.
- 在各种恶性瘤中观察到有前途的临床结果.
结论:
- 人工智能在免疫瘤学中的整合对个性化癌症治疗具有重大前景.
- 人工智能可以改善生物标志物发现,理性组合设计和动态治疗适应.
- 解决化疗诱导的免疫抑制和瘤异质性等挑战对于最大限度地提高治疗效益至关重要.
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