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Cancer Model Simulation in Simulink Environment for Educational Purposes of Cancer Drug Dose Control | ||
| Modeling and Simulation in Electrical and Electronics Engineering | ||
| دوره 2، شماره 2 - شماره پیاپی 8، آبان 2022، صفحه 49-60 اصل مقاله (1.58 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/mseee.2023.29214.1122 | ||
| نویسندگان | ||
| Ali Maleki* 1؛ Matin Kordbacheh2 | ||
| 1Faculty of Electrical and Computer Engineering (ECE), Semnan University, Semnan, Iran. | ||
| 2Control Engineering Department, Semnan University, Semnan, Iran | ||
| تاریخ دریافت: 15 آذر 1401، تاریخ پذیرش: 21 اسفند 1401 | ||
| چکیده | ||
| Cancer is one of the leading causes of death worldwide and the third cause of death in Iran after cardiovascular diseases and driving incidents. Therefore, having models that can describe and explain the process of cancer treatment is vital. One novel method for cancer treatment is to combine chemotherapy and immunotherapy. The purpose of immunotherapy is to enhance the body's immune system and reduce chemotherapy's side effects. Different models have been presented. The significance of the models is to understand the effect of each element on the treatment process. This article concerns the implementation of chemotherapy-immunotherapy cancer treatment in the Simulink toolbox of Matlab. Following the implementation of the model, the impact of chemotherapy, immunotherapy, and the combined technique on cancer cell growth is assessed. Simulating with Simulink allows for a graphical explanation as well as the ability to explain the hierarchy and effect of each piece. As a result, it may be advantageous for educational purposes. Simulink Toolboxes such as optimization, signal processing, and system identification allow us to analyze and control the cancer model. | ||
| کلیدواژه‌ها | ||
| Tumor cell model؛ chemotherapy؛ immunotherapy؛ Simulink؛ Simulation | ||
| مراجع | ||
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[1] Sonnenschein C and Soto AM, “Theories of carcinogenesis: an emerging perspective”, Seminars in cancer biology, 8(5): 372-377, 2008 Oct 1.
[2] Pakin DM, “The global health burden of infection-associated cancers in the years 2002”, International Journal of Cancer; 118(12):3030-44, 2006.
[3] Beir VI, “Health risks from exposure to low levels of ionizing radiation”, The National Academies report in brief. 2005.
[4] De Pillis LG and Radunskaya A, “A mathematical model of immune response to tumor invasion”, Computational fluid and solid mechanics, 1661-1668, 2003.
[5] De Pillis L and Renee Fister K and Gu W and Collins C and Daub M and Gross D and Moore J and Preskill B, “Mathematical model creation for cancer chemo-immunotherapy”, Computational and Mathematical Methods in Medicine, 10(3):165-84, 2009.
[6] Kim KS and Cho G and Jung IH, “Optimal treatment strategy for a tumor model under immune suppression” Computational and mathematical methods in medicine, 2014.
[7] De Pillis LG and Gu W and Radunskaya AE, “Mixed immunotherapy and chemotherapy of tumors: modeling, applications and biological interpretations”, Journal of theoretical biology; 238(4):841-62, 2006.
[8] Pinho ST and Bacelar FS and Andrade RF and Freedman HI, “A mathematical model for the effect of anti-angiogenic therapy in the treatment of cancer tumours by chemotherapy”, Nonlinear Analysis: Real World Applications; 14(1):815-828, 2013.
[9] Adam JA and Bellomo N. “A survey of models for tumor-immune system dynamics”, Springer Science & Business Media; 2012.
[10] Usman A and Cunningham C, “Application of the mathematical model of tumor-immune interactions for IL-2 Adoptive Immunotherapy to studies on patients with Metastatic Melanoma or Renal Cell Cancer”, Rose-Hulman Undergraduate Mathematics Journal, 6(2):9, 2005.
[11] Naderi H and Mehrabi M and Ahmadian MT, “Adaptive fuzzy controller design of drug dosage using optimal trajectories in a chemoimmunotherapy cancer treatment model”, Informatics in Medicine Unlocked; 27:100782. 2021.
[12] otolongo-Costa O, Molina LM, Perez DR, Antoranz JC, Reyes MC. Behavior of tumors under nonstationary therapy. Physica D: Nonlinear Phenomena.;178(3-4):242-53, 2003 Apr 15.
[13] Robertson-Tessi M, El-Kareh A, Goriely A. A mathematical model of tumor–immune interactions. Journal of theoretical biology; 294:56-73. 2012 Feb 7.
[14] Roberto A. Ku-Carrillo, Sandra E. Delgadillo, B.M. Chen-Charpentier, A mathematical model for the effect of obesity on cancer growth and on the immune system response, Applied Mathematical Modelling (2015)
[15] Kirschner D, Panetta JC. Modeling immunotherapy of the tumor–immune interaction. Journal of mathematical biology; 37(3):235-52. 1998 Sep.
[16] Bunimovich-Mendrazitsky S, Shochat E, Stone L. Mathematical model of BCG immunotherapy in superficial bladder cancer. Bulletin of Mathematical Biology;69(6):1847-70.2007 Aug.
[17] Boissonnas A, Fetler L, Zeelenberg IS, Hugues S, Amigorena S. In vivo imaging of cytotoxic T cell infiltration and elimination of a solid tumor. The Journal of experimental medicine; 204(2):345-56, 2007 Feb 19.
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