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

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.

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.

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.

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.