患者衍生异种移植模型和人工智能对准确医学的作用
Venkatachalababu Janitri1, Kandasamy Nagarajan ArulJothi2, Vijay Murali Ravi Mythili2
1Department of Biomedical Engineering Rochester Institute of Technology Rochester New York USA.
MedComm
|September 27, 2024
概括
患者衍生异种移植 (PDX) 提供高保真性癌症模型,优于传统方法. 本综述详细介绍了PDX生成,应用以及AI/ML的整合,以便在瘤学研究中加速治疗评估.
科学领域:
- 在瘤学瘤学.
- 翻译癌症研究 翻译癌症研究
- 生物医学工程 生物医学工程
背景情况:
- 患者衍生异种移植 (PDX) 是先进的癌症模型,保留了原始瘤特征.
- PDX模型比细胞系异种移植和基因工程模型提供更高的保真性.
- 了解影响PDX可靠性的因素对于其有效使用至关重要.
研究的目的:
- 审查PDX模型生成,应用和癌症研究中的优势.
- 在PDX研究中探索人工智能 (AI) 和机器学习 (ML) 的整合.
- 为了解决PDX模型的成本,时间和可变性等挑战.
主要方法:
- 详细审查生成PDX模型的方法.
- 在临床前和临床前药物测试中分析PDX模型应用.
- 对用于治疗评估的PDX数据应用AI和ML技术的探索.
主要成果:
- 在PDX模型中,患者的瘤分子和生物特征可以跨代保存.
- 与其他模型相比,PDX模型对治疗疗效的预测能力更强.
- 人工智能和机器学习的整合可以加速PDX研究和治疗评估的分析.
结论:
- PDX模型是促进癌症研究,生物标志物发现和个性化医学的宝贵工具.
- 解决PDX模型当前的局限性将提高其实用性和预测能力.
- 持续开发和集成先进的计算方法将进一步优化瘤学中的PDX应用.
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