Work

Digital twin modelling in microgravity: A framework for predictive and personalised space medicine

Year: 2025

Type: article

Abstract: Human spaceflight exposes the body to a complex array of physiological stressors that collectively alter cardiovascular, musculoskeletal, immune, and nervous systems. Continuous biomedical monitoring produces vast, but fragmented datasets including physiological data, omics profiles, imaging, and behavioural metrics. However, these data are often analysed retrospectively rather than used dynamically to guide countermeasures in real time. Digital twin technology, which creates adaptive computational replicas of physical systems that evolve with incoming data, provides a novel framework for personalised astronaut health management. This article outlines how individualised digital twins could integrate multi-omics, physiological, and environmental data to predict deconditioning, optimise countermeasure protocols, and guide in-flight medical decisions. A phased roadmap for implementation is proposed, from Earth-based analogue validation to mission-integrated predictive modelling. Digital twins could ultimately enable precision space medicine, transforming astronaut monitoring from observation to anticipation.

Source: Life Sciences in Space Research

DOI: 10.1016/j.lssr.2025.11.004

Authors: Ruqaiyyah Siddiqui, Rizwan Qaisar, Adel Elmoselhi, Naveed Ahmed Khan

Institutions: Heriot-Watt University, Istinye University, University of Sharjah, University of Derby

Language: English

Topic: Spaceflight effects on biology

Subfield: Physiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $3,060