Modelling radiation adaptive response in space radiation risk assessment using Monte Carlo simulation.

Uncertainty surrounding the biological effects of chronic low-dose radiation remains an important challenge in radiation risk assessment, particularly for long-duration space missions. Although adaptive response has been proposed as a potential modifier of radiation-induced cancer risk, its impact on mission-level risk predictions has not been quantitatively evaluated. We developed an exploratory Monte Carlo framework that extends a conventional linear no-threshold-based cancer risk model by incorporating an adaptive response factor (RAF) parameterised by a maximum protection fraction (), a half-saturation priming dose (), and a persistence time constant (). Organ-specific equivalent doses and model parameters were sampled for representative International Space Station (ISS), lunar, and Mars mission scenarios over 100 000 iterations per organ-mission pair. Under the implemented single-priming with exponential decay formulation, adaptive response produced only modest changes in projected cancer risk. Median reductions were negligible for the 1000 d Mars mission and remained below 1% for ISS scenarios, while larger reductions occurred only in a small fraction of simulations associated with favourable adaptive-response parameters. Within the assumptions of the current model, adaptive response is unlikely to substantially alter mission-level cancer risk estimates. Nevertheless, the proposed framework provides a transparent method for evaluating alternative biological hypotheses and quantifying their potential influence on radiation risk assessment as new experimental evidence becomes available.