Engineering Longevity: A Multi-Scale Systems Framework Using Digital Twins and AI to Achieve Sustainable Public Health

(Background) The 20th-century reductionist medical paradigm is reaching its limits, facing unsustainable costs from aging populations and chronic multi-morbidity. This context necessitates a paradigm shift from reactively treating disease to proactively engineering healthspan, highlighting the purpose of this study: to establish the comprehensive rationale for adopting a systems engineering perspective to guide this transformation. (Methods) Through a structured literature review, this study synthesizes the theoretical foundations of Complex Adaptive Systems (CAS) and Systems Engineering as applied to healthcare. It surveys the emerging technological architecture, including high-level simulation toolkits like Digital Twins and AI, and the pervasive layer of personal health devices. The review further analyzes the practical implications of this shift across education, clinical practice, and policy. (Results) The synthesis reveals that Systems Engineering offers a robust methodology to manage the inherent complexity of health systems. This review identifies the possible technological architecture and confirms that a paradigm shift requires reforms across multiple areas of the healthcare ecosystem. (Conclusions) A systems engineering approach is a step forward, presenting a sustainable approach for the future of health systems: mandating the integration of new theoretical, technological, practical, and ethical frameworks to move beyond extending lifespan to truly engineering longevity.

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Publication Details

Journal
Mitteilungen Klosterneuburg
Published
2025-01-01
DOI
https://doi.org/10.61586/77dme
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
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article

Engineering Longevity: A Multi-Scale Systems Framework Using Digital Twins and AI to Achieve Sustainable Public Health

Timur Chis, Mihai Caramihai, Daniel Ioan CHIS, Ioan Dumitrache
Mitteilungen Klosterneuburg
Digital Transformation in Industry
article

Engineering Longevity: A Multi-Scale Systems Framework Using Digital Twins and AI to Achieve Sustainable Public Health

Timur Chis, Mihai Caramihai, Daniel Ioan CHIS, Ioan Dumitrache
article en

Abstract

(Background) The 20th-century reductionist medical paradigm is reaching its limits, facing unsustainable costs from aging populations and chronic multi-morbidity. This context necessitates a paradigm shift from reactively treating disease to proactively engineering healthspan, highlighting the purpose of this study: to establish the comprehensive rationale for adopting a systems engineering perspective to guide this transformation. (Methods) Through a structured literature review, this study synthesizes the theoretical foundations of Complex Adaptive Systems (CAS) and Systems Engineering as applied to healthcare. It surveys the emerging technological architecture, including high-level simulation toolkits like Digital Twins and AI, and the pervasive layer of personal health devices. The review further analyzes the practical implications of this shift across education, clinical practice, and policy. (Results) The synthesis reveals that Systems Engineering offers a robust methodology to manage the inherent complexity of health systems. This review identifies the possible technological architecture and confirms that a paradigm shift requires reforms across multiple areas of the healthcare ecosystem. (Conclusions) A systems engineering approach is a step forward, presenting a sustainable approach for the future of health systems: mandating the integration of new theoretical, technological, practical, and ethical frameworks to move beyond extending lifespan to truly engineering longevity.

Mitteilungen Klosterneuburg
Openalex Percentile: Top 61%
Digital Transformation in Industry
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