Modeling radiation adaptive response in space radiation risk assessment using Monte Carlo simulation

BACKGROUND: Uncertainty surrounding the biological effects of chronic lowdose 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. METHODS: We developed an exploratory Monte Carlo framework that extends a conventional LNT-based cancer risk model by incorporating an Adaptive Response Factor (RAF) parameterized by a maximum protection fraction (RAF max ), a half-saturation priming dose (d 50 ), and a persistence time constant (τ ). Organ-specific equivalent doses and model parameters were sampled for representative ISS, lunar, and Mars mission scenarios over 100,000 iterations per organ-mission pair. RESULTS: 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-day Mars mission and remained below 1% for ISS scenarios, while larger reductions occurred only in a small fraction of simulations associated with favorable adaptive-response parameters. CONCLUSIONS: 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.