CANCER GROWTH TREATMENT USING IMMUNE LINEAR QUADRATIC REGULATOR BASED ON CROW SEARCH OPTIMIZATION ALGORITHM
Mohammed A. Hussein
mohammediyad95@gmail.comMustansiriyah University, College of Engineering, Computer Engineering Department, Baghdad (Iraq)
Ekhlas H. Karam
Mustansiriyah University, College of Engineering, Computer Engineering Department, Baghdad (Iraq)
Rokaia S. Habeeb
Mustansiriyah University, College of Engineering, Computer Engineering Department, Baghdad (Iraq)
Abstract
The rapid and uncontrollable cell division that spreads to surrounding tissues medically termed as malignant neoplasm, cancer is one of the most common diseases worldwide. The need for effective cancer treatment arises due to the increase in the number of cases and the anticipation of higher levels in the coming years. Oncolytic virotherapy is a promising technique that has shown encouraging results in several cases. Mathematical models of virotherapy have been widely developed, and one such model is the interaction between tumor cells and oncolytic virus. In this paper an artificially optimized Immune- Linear Quadratic Regulator (LQR) is introduced to improve the outcome of oncolytic virotherapy. The control strategy has been evaluated in silico on number of subjects. The crow search algorithm is used to tune immune and LQR parameters. The study is conducted on two subjects, S1 and S3, with LQR and Immune-LQR. The experimental results reveal a decrease in the number of tumor cells and remain in the treatment area from day ten onwards, this indicates the robustness of treatment strategies that can achieve tumor reduction regardless of the uncertainty in the biological parameters.
Keywords:
oncolytic virotherapy, feedback mechanism, crow search algorithm, Immune-LQRReferences
Anelone, A.J.N., Villa-Tamayo, M.F., & Rivadeneira, P.S. (2020). Oncolytic virus therapy benefits from control theory. Royal Society Open Science, 7(7), 200473. https://doi.org/10.1098/rsos.200473
DOI: https://doi.org/10.1098/rsos.200473
Google Scholar
Arum, A.K., Handayani, D., & Saragih, R. (2019). Robust control design for virotherapy model using successive method. Journal of Physics: Conference Series, 1245(1), 12054. https://doi.org/10.1088/1742-6596/1245/1/012054
DOI: https://doi.org/10.1088/1742-6596/1245/1/012054
Google Scholar
Askarzadeh, A. (2016). A novel metaheuristic method for solving constrained engineering optimization problems: crow search algorithm. Computers & Structures, 169, 1–12. https://doi.org/10.1016/j.compstruc.2016.03.001
DOI: https://doi.org/10.1016/j.compstruc.2016.03.001
Google Scholar
Cancer Research UK. (2016). Worldwide cancer statistics. Cancer Research UK. Cancer Research UK (pp. 1–5). https://www.cancerresearchuk.org/health-professional/cancer-statistics/worldwide-cancer
Google Scholar
Crivelli, J.J., Földes, J., Kim, P.S., & Wares, J.R. (2012). A mathematical model for cell cycle-specific cancer virotherapy. Journal of Biological Dynamics, 6(sup1), 104–120. https://doi.org/10.1080/17513758.2011.613486
DOI: https://doi.org/10.1080/17513758.2011.613486
Google Scholar
Ding, Y., Chen, L., & Hao, K. (2018). Bio-Inspired Collaborative Intelligent Control and Optimization. Springer.
DOI: https://doi.org/10.1007/978-981-10-6689-4
Google Scholar
Jenner, A.L. (2020). Applications of mathematical modelling in oncolytic virotherapy and immunotherapy. Bulletin of the Australian Mathematical Society, 101(3), 522–524. https://doi.org/10.1017/S0004972720000283
DOI: https://doi.org/10.1017/S0004972720000283
Google Scholar
Jenner, A.L., Yun, C.-O., Kim, P.S., & Coster, A.C.F. (2018). Mathematical modelling of the interaction between cancer cells and an oncolytic virus: insights into the effects of treatment protocols. Bulletin of Mathematical Biology, 80(6), 1615–1629. https://doi.org/10.1007/s11538-018-0424-4
DOI: https://doi.org/10.1007/s11538-018-0424-4
Google Scholar
Kim, P.-H., Sohn, J.-H., Choi, J.-W., Jung, Y., Kim, S.W., Haam, S., & Yun, C.-O. (2011). Active targeting and safety profile of PEG-modified adenovirus conjugated with herceptin. Biomaterials, 32(9), 2314–2326. https://doi.org/10.1016/j.biomaterials.2010.10.031
DOI: https://doi.org/10.1016/j.biomaterials.2010.10.031
Google Scholar
NIH. (2016). Cancer Statistics – National Cancer Institute. NIH. https://www.cancer.gov/about-cancer/understanding/statistics
Google Scholar
Priya, P., & Reyes, V.M. (2015). A Cancer Biotherapy Resource. ArXiv Preprint ArXiv:1602.08111. https://arxiv.org/abs/1602.08111
Google Scholar
Purnawan, H., & Purwanto, E.B. (2017). Design of linear quadratic regulator (LQR) control system for flight stability of LSU-05. Journal of Physics: Conference Series, 890(1), 12056.
DOI: https://doi.org/10.1088/1742-6596/890/1/012056
Google Scholar
Rochdi, B. (2014). Design and application of fuzzy immune PID control based on genetic optimization. International Workshop on Advanced Control IWAC (pp. 10–14).
Google Scholar
Saputra, J., Saragih, R., & Handayani, D. (2019). Robust H∞ controller for bilinear system to minimize HIV concentration in blood plasma. Journal of Physics: Conference Series, 1245(1), 12055.
DOI: https://doi.org/10.1088/1742-6596/1245/1/012055
Google Scholar
Takahashi, K., & Yamada, T. (1998). Application of an immune feedback mechanism to control systems. JSME International Journal Series C Mechanical Systems, Machine Elements and Manufacturing, 41(2), 184–191. https://doi.org/10.1299/jsmec.41.184
DOI: https://doi.org/10.1299/jsmec.41.184
Google Scholar
Yang, X.-S. (2020). Nature-inspired optimization algorithms. Academic Press.
DOI: https://doi.org/10.1016/B978-0-12-821986-7.00018-4
Google Scholar
Authors
Mohammed A. Husseinmohammediyad95@gmail.com
Mustansiriyah University, College of Engineering, Computer Engineering Department, Baghdad Iraq
Authors
Ekhlas H. KaramMustansiriyah University, College of Engineering, Computer Engineering Department, Baghdad Iraq
Authors
Rokaia S. HabeebMustansiriyah University, College of Engineering, Computer Engineering Department, Baghdad Iraq
Statistics
Abstract views: 145PDF downloads: 29
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
All articles published in Applied Computer Science are open-access and distributed under the terms of the Creative Commons Attribution 4.0 International License.
Similar Articles
- Nancy WOODS, Charles ROBERT, ENCAPSULATION OF IMAGE METADATA FOR EASE OF RETRIEVAL AND MOBILITY , Applied Computer Science: Vol. 15 No. 1 (2019)
- Rosa Maria VAZQUEZ, Edmundo BONILLA, Eduardo SANCHEZ, Oscar ATRIANO, Cinthya BERRUECOS, APPLICATION OF DATA MINING TECHNIQUES TO FIND RELATIONSHIPS BETWEEN THE DISHES OFFERED BY A RESTAURANT FOR THE ELABORATION OF COMBOS BASED ON THE PREFERENCES OF THE DINERS , Applied Computer Science: Vol. 15 No. 2 (2019)
- Anna MACHROWSKA, Robert KARPIŃSKI, Przemysław KRAKOWSKI, Józef JONAK, DIAGNOSTIC FACTORS FOR OPENED AND CLOSED KINEMATIC CHAIN OF VIBROARTHROGRAPHY SIGNALS , Applied Computer Science: Vol. 15 No. 3 (2019)
- Marcin TOMCZYK, Anna PLICHTA, Mariusz MIKULSKI, APPLICATION OF IMAGE ANALYSIS TO THE IDENTIFICATION OF MASS INERTIA MOMENTUM IN ELECTROMECHANICAL SYSTEM WITH CHANGEABLE BACKLASH ZONE , Applied Computer Science: Vol. 15 No. 3 (2019)
- Sunil Kumar B L, Sharmila Kumari M, RGB-D FACE RECOGNITION USING LBP-DCT ALGORITHM , Applied Computer Science: Vol. 17 No. 3 (2021)
- Łukasz WOJCIECHOWSKI, Tadeusz CISOWSKI, MODEL OF A COMPUTER SYSTEM FOR SELECTION OF OPERATING PARAMETERS FOR TRANSPORT VEHICLES IN THE ASPECT OF THEIR DURABILITY , Applied Computer Science: Vol. 14 No. 4 (2018)
- Marcin BADUROWICZ, DETECTION OF SOURCE CODE IN INTERNET TEXTS USING AUTOMATICALLY GENERATED MACHINE LEARNING MODELS , Applied Computer Science: Vol. 18 No. 1 (2022)
- Marcin TOMCZYK, Barbara BOROWIK, Bohdan BOROWIK, IDENTIFICATION OF THE MASS INERTIA MOMENT IN AN ELECTROMECHANICAL SYSTEM BASED ON WAVELET–NEURAL METHOD , Applied Computer Science: Vol. 14 No. 2 (2018)
- Denis Ratov, INTEGRATION WITH THE SOFTWARE INTERFACE OF THE COM SERVER FOR AUTHORIZED USER , Applied Computer Science: Vol. 17 No. 2 (2021)
You may also start an advanced similarity search for this article.
