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迈向机制性医学数字孪生:免疫学中的一些用例

Toward mechanistic medical digital twins: some use cases in immunology.

作者信息

Laubenbacher Reinhard, Adler Fred, An Gary, Castiglione Filippo, Eubank Stephen, Fonseca Luis L, Glazier James, Helikar Tomas, Jett-Tilton Marti, Kirschner Denise, Macklin Paul, Mehrad Borna, Moore Beth, Pasour Virginia, Shmulevich Ilya, Smith Amber, Voigt Isabel, Yankeelov Thomas E, Ziemssen Tjalf

机构信息

Department of Medicine, University of Florida, Gainesville, FL, United States.

Department of Mathematics and School of Biological Sciences, University of Utah, Salt Lake, UT, United States.

出版信息

Front Digit Health. 2024 Mar 7;6:1349595. doi: 10.3389/fdgth.2024.1349595. eCollection 2024.

Abstract

A fundamental challenge for personalized medicine is to capture enough of the complexity of an individual patient to determine an optimal way to keep them healthy or restore their health. This will require personalized computational models of sufficient resolution and with enough mechanistic information to provide actionable information to the clinician. Such personalized models are increasingly referred to as medical digital twins. Digital twin technology for health applications is still in its infancy, and extensive research and development is required. This article focuses on several projects in different stages of development that can lead to specific-and practical-medical digital twins or digital twin modeling platforms. It emerged from a two-day forum on problems related to medical digital twins, particularly those involving an immune system component. Open access video recordings of the forum discussions are available.

摘要

个性化医疗面临的一个根本挑战是捕捉个体患者足够多的复杂性,以确定保持其健康或恢复其健康的最佳方法。这将需要具有足够分辨率且包含足够机制信息的个性化计算模型,以便为临床医生提供可操作的信息。这种个性化模型越来越多地被称为医学数字孪生。用于健康应用的数字孪生技术仍处于起步阶段,需要进行广泛的研究和开发。本文重点介绍了处于不同开发阶段的几个项目,这些项目可以促成特定且实用的医学数字孪生或数字孪生建模平台。它源自一个为期两天的关于医学数字孪生相关问题的论坛,特别是那些涉及免疫系统组成部分的问题。该论坛讨论的开放获取视频记录可供观看。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f0c/10955144/5d7a7f5592ed/fdgth-06-1349595-g001.jpg

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