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Mechanistic in silico explorations of the immunogenic and synergistic effects of radiotherapy and immunotherapy: a critical review.
Ng, Allison M; MacKinnon, Kelly M; Cook, Alistair A; D'Alonzo, Rebecca A; Rowshanfarzad, Pejman; Nowak, Anna K; Gill, Suki; Ebert, Martin A.
Affiliation
  • Ng AM; School of Physics, Mathematics and Computing, The University of Western Australia, Crawley, WA, Australia.
  • MacKinnon KM; School of Physics, Mathematics and Computing, The University of Western Australia, Crawley, WA, Australia.
  • Cook AA; National Centre for Asbestos Related Diseases, The University of Western Australia, Crawley, WA, Australia.
  • D'Alonzo RA; National Centre for Asbestos Related Diseases, The University of Western Australia, Crawley, WA, Australia.
  • Rowshanfarzad P; Institute for Respiratory Health, Institute for Respiratory Health, Perth, WA, Australia.
  • Nowak AK; School of Biomedical Sciences, The University of Western Australia, Crawley, WA, Australia.
  • Gill S; School of Physics, Mathematics and Computing, The University of Western Australia, Crawley, WA, Australia.
  • Ebert MA; National Centre for Asbestos Related Diseases, The University of Western Australia, Crawley, WA, Australia.
Phys Eng Sci Med ; 2024 Jul 17.
Article in En | MEDLINE | ID: mdl-39017990
ABSTRACT
Immunotherapy is a rapidly evolving field, with many models attempting to describe its impact on the immune system, especially when paired with radiotherapy. Tumor response to this combination involves a complex spatiotemporal dynamic which makes either clinical or pre-clinical in vivo investigation across the resulting extensive solution space extremely difficult. In this review, several in silico models of the interaction between radiotherapy, immunotherapy, and the patient's immune system are examined. The study included only mathematical models published in English that investigated the effects of radiotherapy on the immune system, or the effect of immuno-radiotherapy with immune checkpoint inhibitors. The findings indicate that treatment efficacy was predicted to improve when both radiotherapy and immunotherapy were administered, compared to radiotherapy or immunotherapy alone. However, the models do not agree on the optimal schedule and fractionation of radiotherapy and immunotherapy. This corresponds to relevant clinical trials, which report an improved treatment efficacy with combination therapy, however, the optimal scheduling varies between clinical trials. This discrepancy between the models can be attributed to the variation in model approach and the specific cancer types modeled, making the determination of the optimum general treatment schedule and model challenging. Further research needs to be conducted with similar data sets to evaluate the best model and treatment schedule for a specific cancer type and stage.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Phys Eng Sci Med Year: 2024 Document type: Article Affiliation country: Australia

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Phys Eng Sci Med Year: 2024 Document type: Article Affiliation country: Australia
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