优化免疫疗法:免疫检查点抑制剂与人工智能在黑色素瘤治疗中的协同作用
Mohammad Saleem1, Abigail E Watson2, Aisha Anwaar1
1Department of Dermatology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA.
Biomolecules
|April 30, 2025
概括
人工智能 (AI) 通过提高反应预测和识别生物标志物来增强免疫检查点抑制剂 (ICI) 的黑色素瘤治疗. 人工智能工具分析数据以进行个性化治疗,并预测副作用,优化患者的治疗结果.
科学领域:
- 在瘤学瘤学.
- 免疫治疗是一种免疫疗法.
- 人工智能的人工智能
背景情况:
- 免疫检查点抑制剂 (ICI) 已经彻底改变了黑色素瘤治疗.
- 预测患者对ICI的反应仍然是一个重大的临床挑战.
- 人工智能 (AI) 为优化ICI治疗提供了潜在的解决方案.
研究的目的:
- 审查AI在黑色素瘤免疫治疗中的应用.
- 探索AI在预测建模,生物标志物识别和治疗反应预测中的作用.
- 评估AI在完善患者分层和预测免疫相关不良事件 (irAEs) 的潜力.
主要方法:
- 对黑色素瘤免疫治疗中人工智能应用的综合文献综述.
- 分析机器学习和深度学习算法用于预测建模.
- 评估人工智能与RNAseq,EHR数据和成像等诊断工具的整合.
主要成果:
- 人工智能模型确定了预后性细胞因子签名,并改善了ICI结果.
- 人工智能与RNAseq相结合显示出个性化ICI治疗的潜力.
- 人工智能准确分析了瘤微环境,并量化了瘤透淋巴细胞 (TILs).
- 人工智能辅助的TIL量化对预后和预测抗PD-1反应有价值.
- 整合多个数据源适度改善了生存预测.
结论:
- 在黑色素瘤免疫疗法中,人工智能驱动的方法显示出改进生物标志物发现,治疗预测和患者分层的巨大潜力.
- 人工智能可以通过提高预测准确性和个性化治疗策略来优化ICI治疗.
- 进一步的临床验证和解决实施挑战是广泛采用人工智能的必要条件.
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