The Data Science of Health in Space

Abstract

Spaceflight exposes humans to unique stressors that remodel biology. Space health is emerging as a data science discipline grounded in multiomic atlases, harmonized biobanks, and open, findable, accessible, interoperable, and reusable (FAIR)-aligned infrastructures. We review this ecosystem, including the National Aeronautics and Space Administration (NASA)'s GeneLab; the Open Science Data Repository, European Space Agency, and Japan Aerospace Exploration Agency (JAXA) platforms; the Space Omics and Medical Atlas; and mission-specific repositories, and how it is used to integrate heterogeneous omics with clinical, environmental, and digital phenotypes. We highlight machine learning and causal inference approaches to identify conserved signatures of risk and resilience and to align astronaut datasets with large terrestrial cohorts and disease models. Spaceflight functions as an accelerated model of aging and systems-level stress, enabling discovery of biomarkers and countermeasures with reciprocal benefits for Earth-based medicine. Finally, we outline future directions, including countermeasure-prioritization pipelines; astronaut digital twins and virtual organs; operational analytics and wearables for personalized risk management; and federated, privacy-preserving data ecosystems that extend predictive, individualized space health to the operational edge.