Editorial: Digital twins in medicine—transition from theoretical concept to tool used in everyday care DOI Creative Commons
Stephen Gilbert, David Drummond, Fabienne Cotte

et al.

Frontiers in Digital Health, Journal Year: 2025, Volume and Issue: 7

Published: Feb. 27, 2025

This Research Topic gathers different contributions addressing the practical advancement of concept digital twins in medicine, moving it form a vague theoretical towards foundation to tools used everyday healthcare. The twin (sometimes known as virtual twin) is that mainstream manufacturing, where representation created an intended or actual real-world physical product, system, process (the twin). serves effectively indistinguishable counterpart and for purposes such simulation, monitoring maintenance (Singh et al., 2021). has existed medicine decades, but unlike industry, not found its way dayto-day application patient care (Venkatesh 2022;Derraz 2024). Despite this there renewed research interest theme.The goal was address if we are at dawn medical practice explore what needed realize this. articles help define aspects near translation those need substantially more preclinical development before possible. Digital Twins patients, which have been defined various ways "a viewable replica patient, organ, biological system contains multidimensional, patient-specific information informs decisions" (Drummond Gonsard, 2024), involve only new forms about also simulation methods often AI-based predictive analytical methods. There much hype excitation AI, AI will delivery promise firmly linked status datain other words twin. These raise regulatory ethical questions, with differing approaches countries -a bring some clarity these challenges alongside proposed strategies developments, serve description state art path impact medicine. provisional file, final typesetThe first article (Laubenbacher 2024) clinicians data-driven decision support clear, already use. 60 authors describe similarity-based approach matches patients similar historical 61 cases predict treatment outcomes. Requirements were from scientific technical literature 62 four-layer implemented. suggests multi-line 63 integration external evidence transparency data processing logic. sets 64 initial clinical evaluation illustrates through detailed 65 exemplary use case multiple myeloma. 66The third (Zhang original describes 67 framework type 2 diabetes integrates machine learning multiomic data, 68 both knowledge graphs mechanistic models. researchers developed 69 models forecast disease progression using substantial dataset comprising 70 measurements profiles. Knowledge employed interpret provide 71 context relationships. Promise demonstrated modeling reaffirming 72 targetable mechanisms features. potential DT 73 precision 74The mini review role 75 personalized therapeutics pharmaceutical manufacturing (Fischer set out 76 how pave way, systems improved 77 (as described previous three articles) facilitate 78 their management, analysis, interpretation 79 data. identify gaps be filled can part routine

Language: Английский

Advancing Healthcare with Digital Twins: A Meta-Review of Applications and Implementation Challenges (Preprint) DOI Creative Commons
Mickaël Ringeval, Faustin Armel Etindele Sosso, Martin Cousineau

et al.

Journal of Medical Internet Research, Journal Year: 2025, Volume and Issue: 27, P. e69544 - e69544

Published: Jan. 24, 2025

Background Digital twins (DTs) are digital representations of real-world systems, enabling advanced simulations, predictive modeling, and real-time optimization in various fields, including health care. Despite growing interest, the integration DTs care faces challenges such as fragmented applications, ethical concerns, barriers to adoption. Objective This study systematically reviews existing literature on DT applications with three objectives: (1) map primary (2) identify key limitations, (3) highlight gaps that can guide future research. Methods A meta-review was conducted a systematic fashion, adhering PRISMA-ScR (Preferred Reporting Items for Systematic Reviews Meta-Analyses extension Scoping Reviews) guidelines, included 25 published between 2021 2024. The search encompassed 5 databases: PubMed, CINAHL, Web Science, Embase, PsycINFO. Thematic synthesis used categorize stakeholders, Results total 3 were identified: personalized medicine, operational efficiency, medical While current diagnostics, patient-specific treatment hospital resource optimization, remain their early stages development, they significant potential DTs. Challenges include data quality, issues, socioeconomic barriers. review also identified scalability, interoperability, clinical validation. Conclusions hold transformative care, providing individualized accelerated However, adoption is hindered by technical, ethical, financial Addressing these issues requires interdisciplinary collaboration, standardized protocols, inclusive implementation strategies ensure equitable access meaningful impact.

Language: Английский

Citations

1
Editorial: Digital twins in medicine—transition from theoretical concept to tool used in everyday care DOI Creative Commons
Stephen Gilbert, David Drummond, Fabienne Cotte

et al.

Frontiers in Digital Health, Journal Year: 2025, Volume and Issue: 7

Published: Feb. 27, 2025

This Research Topic gathers different contributions addressing the practical advancement of concept digital twins in medicine, moving it form a vague theoretical towards foundation to tools used everyday healthcare. The twin (sometimes known as virtual twin) is that mainstream manufacturing, where representation created an intended or actual real-world physical product, system, process (the twin). serves effectively indistinguishable counterpart and for purposes such simulation, monitoring maintenance (Singh et al., 2021). has existed medicine decades, but unlike industry, not found its way dayto-day application patient care (Venkatesh 2022;Derraz 2024). Despite this there renewed research interest theme.The goal was address if we are at dawn medical practice explore what needed realize this. articles help define aspects near translation those need substantially more preclinical development before possible. Digital Twins patients, which have been defined various ways "a viewable replica patient, organ, biological system contains multidimensional, patient-specific information informs decisions" (Drummond Gonsard, 2024), involve only new forms about also simulation methods often AI-based predictive analytical methods. There much hype excitation AI, AI will delivery promise firmly linked status datain other words twin. These raise regulatory ethical questions, with differing approaches countries -a bring some clarity these challenges alongside proposed strategies developments, serve description state art path impact medicine. provisional file, final typesetThe first article (Laubenbacher 2024) clinicians data-driven decision support clear, already use. 60 authors describe similarity-based approach matches patients similar historical 61 cases predict treatment outcomes. Requirements were from scientific technical literature 62 four-layer implemented. suggests multi-line 63 integration external evidence transparency data processing logic. sets 64 initial clinical evaluation illustrates through detailed 65 exemplary use case multiple myeloma. 66The third (Zhang original describes 67 framework type 2 diabetes integrates machine learning multiomic data, 68 both knowledge graphs mechanistic models. researchers developed 69 models forecast disease progression using substantial dataset comprising 70 measurements profiles. Knowledge employed interpret provide 71 context relationships. Promise demonstrated modeling reaffirming 72 targetable mechanisms features. potential DT 73 precision 74The mini review role 75 personalized therapeutics pharmaceutical manufacturing (Fischer set out 76 how pave way, systems improved 77 (as described previous three articles) facilitate 78 their management, analysis, interpretation 79 data. identify gaps be filled can part routine

Language: Английский

Citations

0