加强数字双胞胎的随机临床试验。

IF 3.5 2区生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY

NPJ Systems Biology and Applications Pub Date : 2025-10-03 DOI:10.1038/s41540-025-00592-0

Hossein Akbarialiabad, Amirmohammad Pasdar, Dédée F Murrell, Mehrnaz Mostafavi, Farhan Shakil, Ehsan Safaee, Sancy A Leachman, Alireza Haghighi, Michelle Tarbox, Chritopher G Bunick, Ayman Grada

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引用次数: 0

摘要

数字双胞胎（DTs）可以通过提高伦理标准（包括安全性、知情同意、公平性和数据隐私）来改变随机临床试验。它们还可以通过早期发现不良事件和简化设计来提高试验效率。本文探讨了DTs在个性化医疗中的作用，从临床前研究到上市后，同时解决了实施过程中的技术、法律和伦理挑战。

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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Enhancing randomized clinical trials with digital twins.

Digital twins (DTs) can transform randomized clinical trials by improving ethical standards, including safety, informed consent, equity, and data privacy. They also enhance trial efficiency by enabling early detection of adverse events and streamlined design. This paper explores the role of DTs in personalized medicine, from pre-clinical research to post-marketing, while addressing technological, legal, and ethical challenges in implementation.

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来源期刊

NPJ Systems Biology and Applications Mathematics-Applied Mathematics

CiteScore

5.80

自引率

0.00%

发文量

审稿时长

8 weeks

期刊介绍： npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.