Analytical Simulation to Study the Behavior of Cancerous Tumors by Using Shehu Transformation-Akbari-Ganji’s Method with the Padé Approximation
DOI:
https://doi.org/10.51699/ijhsms.v2i12.3167Keywords:
Shehu transformation, Akbari -Ganji’s method, Padé approximation, Tumors, Immunotherapy, Cytokine, StabilityAbstract
This paper presents an approximate analytical study of the dynamic model of the interaction between lymphocytes and tumor cells in the presence of cytokines. A new method that combines the Shehu transformation and Akbari-Ganji method with the Padé approximation was applied. The accuracy and high efficiency of this method were demonstrated by error tables and graphs. The study found that the rate and duration of treatment had a significant effect on preventing the growth of cancer cells and improving the function of cancer-fighting lymphocytes, confirming the importance of studying and determining the optimal concentrations of cytokines that contribute to inhibiting the growth of cancer cells and improving the function of lymphocytes in fighting cancer.
Downloads
References
Nani F. and Freedman H.I., A mathematical model of cancer treatment by immunotherapy, Mathematical Biosciences, 163, 159-199 (2000).
Sotolongo-Costa O., Molina L. M., Perez D. R., Antoranz J. C. and Reyes, M. C., Behavior of tumors under nonstationary therapy, Physica D: Nonlinear Phenomena, 178(3-4), 242-253 (2003).
Banerjee S. and Sarkar R.R. Delay-induced model for tumor–immune interaction and control of malignant tumor growth, BioSystems, 91, 268–288 (2008).
Fukuhara H., Ino Y. and Todo T., Oncolytic virus therapy: A new era of cancer treatment at dawn, Cancer Science, 107 (10), 1373–1379 (2016).
Kumar S., Kumar A., Samet B., Go ́mez-Aguilar J. F. and Osman M. S., A chaos study of tumor and effector cells in fractional tumor-immune model for cancer treatment, Chaos Soliton. Fract., 141 (2020).
Nave O. and Sigron M., A mathematical model for the treatment of melanoma with the BRAF/MEK inhibitor and Anti-PD-1, Appl. Sci., 12, (2022).
Aljahdaly, N. H., and Almushaity, N. A. A diffusive cancer model with virotherapy: Studying the immune response and its analytical simulation. AIMS Mathematics, 8 (5), 10905-10928 (2023).
Mirgolbabaee H., Ledari S. T. and Ganji D. D., Semi-analytical investigation on micropolar fluid flow and heat transfer in a permeable channel using AGM, Journal of the Association of Arab Universities for Basic and Applied Sciences, 24,213-222, (2017).
Wu B. and Qian Y., Padé approximation based on orthogonal polynomial, Advances in Computer Science Research. 58, 249- 252, (2016).
Maitama S. and Zhao W., New integral transform: Shehu transform a generalization of Sumudu and Laplace transform for solving differential equations, International Journal of Analysis and Applications 17. (2), 167-190, (2019).
Hasan Z. A. and Al-Saif A.S. J. A hybrid method with RDTM for solving the biological population model. Mathematical Theory and Modeling. 12.(2), 1-11 (2022).
Hassan, M. H., and Al-Saif, A. S. J. A mathematical model for the velocity of thin film flow of a third grade fluid down in an inclined plane. Journal of Advanced Research in Fluid Mechanics and Thermal Sciences, 102 (1), 140-152 (2023).
Al‐Griffi, T. A. J., and Al‐Saif A. S. J. Yang transform–homotopy perturbation method for solving a non‐Newtonian viscoelastic fluid flow on the turbine disk. ZAMM‐Journal of Applied Mathematics and Mechanics/Zeitschrift für Angewandte Mathematik und Mechanik 102. e202100116, 1-17 (2022).
Abdoon M.A., and Hasan F.L. Advantages of the differential equations for solving problems in mathematical physics with symbolic computation. Mathematical modelling of engineering problems 9, (1), 268-276, (2022).
Abdulameer, Y. A., and Al-Saif A. S. J., A well-founded analytical technique to solve 2D viscous flow between slowly expanding or contracting walls with weak permeability. Journal of Advanced Research in Fluid Mechanics and Thermal Sciences 97. (2), 39-56 (2022).
Khudair, A. R., and Mihan, M. W., Random fractional Laplace transform for solving random time-fractional heat equation in an infinite medium. Basrah Journal of Science, 38(2), 223-247, (2020).
Boyd J., Padé approximant algorithm for solving nonlinear ordinary differential equation boundary value problems on an unbounded domain. Computers in Physics, 11, (3), 299- 303, (1997).
Wazwaz A.M., Analytical approximations and Padé approximants for Volterra’s population model. Applied Mathematics and Mathematical Computation, 100, 31-35, (1999).
Wazwaz A.M., The modified decomposition method and Pade’s approximants for solving Thomas-Fermi equation. Applied Mathematics and Mathematical Computations, 105, 11- 19, (1999).
Al-Sadi R. and Al-Saif A.S., Development and simulation of a mathematical model representing the dynamics of type 1 diabetes mellitus with treatment. Partial Differential Equations in Applied Mathematics,8, 1-12 (2023).
Al-Jaberi A. K., Abdul-Wahab M. S., and Buti R. H., A new approximate method for solving linear and non-linear differential equation systems. In AIP Conference Proceedings, 2398, (1), 1-17 (2022).