  There is evidence of synergy between radiotherapy and immunotherapy.
Radiotherapy can increase liberation of tumor antigens, causing activation of
antitumor T-cells. This effect can be boosted with immunotherapy.
Radioimmunotherapy has potential to increase tumor control rates.
Biomathematical models of response to radioimmunotherapy may help on
understanding of the mechanisms affecting response, and assist clinicians on
the design of optimal treatment strategies. In this work we present a
biomathematical model of tumor response to radioimmunotherapy. The model uses
the linear-quadratic response of tumor cells to radiation (or variation of it),
and builds on previous developments to include the radiation-induced immune
effect. We have focused this study on the combined effect of radiotherapy and
$\alpha$PDL1/$\alpha$CTLA4 therapies. The model can fit preclinical data of
volume dynamics and control obtained with different dose fractionations and
$\alpha$PDL1/$\alpha$CTLA4. A biomathematical study of optimal combination
strategies suggests that a good understanding of the involved biological
delays, the biokinetics of the immunotherapy drug, and the interplay between
them, may be of paramount importance to design optimal radioimmunotherapy
schedules. Biomathematical models like the one we present can help to interpret
experimental data on the synergy between radiotherapy and immunotherapy, and to
assist in the design of more effective treatments.
