RadPhysBio: A Radiobiological Database for Predicting Human Cell Survival under Space-Relevant Ionizing Radiation

Kurzfassung

INTRODUCTION Exposure to ionizing radiation remains one of the dominant biological risks for long-duration human space missions, driven by complex mixed radiation fields from galactic cosmic rays (GCR) and solar particle events (SPE). Although decades of radiobiological experiments exist, their fragmentation across radiation qualities, biological endpoints, and modelling assumptions limits their direct use in space radiation risk assessment.

METHODS We present RadPhysBio, an open, curated radiobiological database and predictive framework designed to quantify cell survival across radiation types and qualities relevant to space environments. RadPhysBio aggregates experimentally derived survival parameters, including linear–quadratic α and β coefficients, across photon, proton, and heavy-ion irradiations, linked with radiation quality descriptors such as linear energy transfer (LET). The platform is openly accessible at: https://radbiodb.physics.ntua.gr/radphysbio/

RESULTS The database structure, data curation strategy, and validation are described in detail in our open-access publication [1]. Using RadPhysBio, we identify consistent LET-dependent trends in cell survival parameters across human cell models and demonstrate comparative differences between low-LET and high-LET radiation exposures. The framework enables exploratory predictions for mixed radiation fields characteristic of GCR and SPE spectra and provides a quantitative basis for integrating radiobiological response data with physical transport and shielding models.

CONCLUSION RadPhysBio addresses a critical gap between experimental radiobiology and operational space radiation risk modelling. It offers a transparent, extensible resource for astronaut health risk assessment, comparative radiation quality studies, and the development of mitigation strategies relevant to future exploration missions beyond low Earth orbit.