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从虚拟患者到免疫瘤学中的数字双胞胎:从机械定量系统药理学建模中吸取的经验教训
Hanwen Wang1, Theinmozhi Arulraj2, Alberto Ippolito2
1Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA. hwang163@jhmi.edu.
虚拟患者和数字双胞胎显示出加速免疫瘤学药物开发的前景. 它们的生成和应用存在挑战,特别是数字双胞胎需要研究特定的模型.
科学领域:
- 计算生物学是一种计算生物学.
- 翻译医学是一种翻译医学.
- 免疫瘤学 免疫瘤学
背景情况:
- 虚拟患者和数字双胞胎是新兴的医疗保健概念.
- 这些技术旨在加快药物开发并提高患者的生存率.
- 目前的应用,特别是免疫瘤学,面临着局限性.
研究的目的:
- 讨论创建免疫瘤学虚拟患者群体的挑战.
- 为个人化医疗开发数字双胞胎的举措强调.
- 探索虚拟患者和数字双胞胎研究之间的协同潜力.
主要方法:
- 对虚拟患者生成现有方法的审查.
- 分析创建特定研究的数字双胞胎模型所面临的挑战.
- 讨论最近在免疫瘤学方面的经验和正在进行的倡议.
主要成果:
- 虚拟患者模型在免疫瘤学研究中的有限应用.
- 数字双胞胎通常需要针对特定的临床环境 (治疗,癌症,数据) 进行定制.
- 在虚拟患者和数字双胞胎的生成和验证方面仍然存在重大挑战.
结论:
- 需要进一步的研究来克服虚拟患者和免疫瘤学数字双胞胎开发的局限性.
- 协同的研究努力可以促进这些数字健康技术的应用.
- 应对当前的挑战对于实现临床实践中虚拟和数字患者的全部潜力至关重要.
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