Department of Medicine, University of Florida, Gainesville, FL, USA.
Department of Mathematics and School of Biological Sciences, University of Utah, Salt Lake City, UT, USA.
NPJ Syst Biol Appl. 2024 Feb 16;10(1):19. doi: 10.1038/s41540-024-00345-5.
Medical digital twins are computational models of human biology relevant to a given medical condition, which are tailored to an individual patient, thereby predicting the course of disease and individualized treatments, an important goal of personalized medicine. The immune system, which has a central role in many diseases, is highly heterogeneous between individuals, and thus poses a major challenge for this technology. In February 2023, an international group of experts convened for two days to discuss these challenges related to immune digital twins. The group consisted of clinicians, immunologists, biologists, and mathematical modelers, representative of the interdisciplinary nature of medical digital twin development. A video recording of the entire event is available. This paper presents a synopsis of the discussions, brief descriptions of ongoing digital twin projects at different stages of progress. It also proposes a 5-year action plan for further developing this technology. The main recommendations are to identify and pursue a small number of promising use cases, to develop stimulation-specific assays of immune function in a clinical setting, and to develop a database of existing computational immune models, as well as advanced modeling technology and infrastructure.
医学数字孪生是与特定医疗状况相关的人类生物学的计算模型,针对特定患者进行定制,从而预测疾病的进程和个体化治疗,这是个性化医疗的重要目标。免疫系统在许多疾病中起着核心作用,个体之间存在高度异质性,因此对这项技术构成了重大挑战。2023 年 2 月,一个国际专家组召开了为期两天的会议,讨论与免疫数字孪生相关的这些挑战。该小组由临床医生、免疫学家、生物学家和数学建模师组成,代表了医学数字孪生开发的跨学科性质。整个活动的视频记录可供查阅。本文总结了讨论的内容,简要描述了不同进展阶段正在进行的数字孪生项目。它还提出了进一步开发这项技术的 5 年行动计划。主要建议是确定并追求少数有前途的用例,开发临床环境中针对免疫功能的刺激特异性检测,以及开发现有的计算免疫模型数据库,以及先进的建模技术和基础设施。