Modeling the biological effects of combined radiation exposures

Decades of experimental work have established combined radiation exposures as a distinct radiobiological problem of increasing interest in radiation protection, radiotherapy, and space radiation research. However, the corresponding modeling literature remains fragmented across methodological traditions and application contexts. Rather than providing an exhaustive bibliographic survey, this review synthesizes representative modeling approaches and classifies them according to their structure and intended use. The reviewed approaches include analytical and semi-analytical theoretical formulations, mechanistic response models, empirical models, Monte Carlo-biology coupling workflows, and clinically oriented modeling strategies. The review examines how radiation quality, biological damage, and biological response are represented across model classes. It disambiguates the definition and use of interaction as a modeling tool and evaluates model performance, applicability, extensibility, robustness, and practical availability. The reviewed literature shows useful but uneven support across model families, with few direct benchmarking studies and limited evidence for transfer beyond the conditions already evaluated. The main priority is to generate model-compatible datasets against which individual models can be tested and competing formulations can be compared under defined combined-exposure conditions. This would clarify when current models remain adequate, when they require revision, and when replacement is justified.