2018/06/08 by Sima Sarv Ahrabi, Alireza Momenzadeh · 10 citations
Biochemistry, Genetics and Molecular Biology · Immunology and Microbiology · Mathematics · Medicine · #Cancer #Cancer Immunotherapy and Biomarkers #Cancer immunotherapy #Computer science #Immunotherapy #Immunotherapy and Immune Responses #Internal medicine #Mathematical Biology Tumor Growth #Mathematical optimization #Mathematics #Maximum principle #Medicine #Optimal control #Pontryagin's minimum principle #math.OC #msc:49J15 #msc:49J30 #q-bio.QM
paper · pdf · open access · doi:10.1007/s00285-020-01525-7
published in Journal of Mathematical Biology 81(2), 691-723 (Springer Science+Business Media) · 12 pages, 6 figures
arxiv created 2018/06/08 · openalex publication_date 2020/07/25 · arxiv updated 2020/08/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/02
In this article, a well-known mathematical model of cancer immunotherapy is discussed and used to represent therapeutic protocols for cancer treatment. The optimal control problem is formulated based on the Pontryagin maximum principle to deal with adoptive cellular immunotherapy, then the problem has been solved by the application of particle swarm optimization (PSO) in combination with regular methods of solutions to optimal control problems. The results are compared with those of other researchers. It is explained how the PSO algorithm could be enlisted to obtain the optimal controls, then the obtained optimal controls are demonstrated to be more appropriate to the elimination of cancer cells by using fewer amounts of external sources of medicine.