The future of in silico trials and digital twins in medicine.

IF 2.2 Q2 MULTIDISCIPLINARY SCIENCES
PNAS nexus Pub Date : 2025-04-18 eCollection Date: 2025-05-01 DOI:10.1093/pnasnexus/pgaf123
Ehsan Samei
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引用次数: 0

Abstract

In silico trials and digital twins are emerging as transformative medical technologies, as they offer a unique way to design medical innovations, optimize their application, and evaluate their utility. Their use spans from individual care-appropriating the technology for personalized decision, to population care-presenting an alternative to design, supplement, or replace clinical trials. They effectually offer a new way to efficiently qualify, quantify, and personalize healthcare innovations in advance or in conjunction with clinical application. While much progress is underway to advance these technologies across diverse developments, realizing their full potential requires a cohesive goal to unify separate activities towards a common objective. Such a cohesive goal-moonshot-can be defined as forming and fostering a digital twin of every single human person, owned by the individual, progressively updated with new data, and used to deliver optimized care, technology assessment, and real-world evidence. The feasibility of such a vision builds upon a growing body of work in computational modeling, regulatory science, and digital healthcare. Bringing this vision to reality requires ownership and active engagement of all stakeholders to contribute diverse expertise and resources for transforming medicine and medical appropriation towards a more accurate, efficient, and quantitative future.

未来的计算机试验和医学上的数字双胞胎。
计算机试验和数字孪生正在成为变革性的医疗技术,因为它们提供了一种独特的方式来设计医疗创新、优化其应用和评估其效用。它们的使用范围从个人护理——将技术用于个性化决策,到人群护理——提供设计、补充或替代临床试验的替代方案。它们有效地提供了一种新的方法,可以提前或与临床应用相结合,有效地对医疗保健创新进行鉴定、量化和个性化。虽然在不同的发展中推进这些技术正在取得很大进展,但要实现它们的全部潜力,需要一个有凝聚力的目标,将不同的活动统一到一个共同的目标。这样一个有凝聚力的目标——登月计划——可以被定义为形成和培养每个人的数字双胞胎,由个人拥有,逐步更新新数据,并用于提供优化的护理、技术评估和现实世界的证据。这种愿景的可行性建立在计算建模、监管科学和数字医疗保健领域不断增长的工作基础上。将这一愿景变为现实需要所有利益攸关方的所有权和积极参与,以贡献各种专业知识和资源,使医学和医疗拨款朝着更准确、更高效和更定量的未来发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.80
自引率
0.00%
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0
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