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Numerical Simulation of Oncolytic M1 Cancer Virotherapy Reaction-Diffusion Model by Finite Element Method | ||
| Computational Methods for Differential Equations | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 10 مرداد 1405 اصل مقاله (3.96 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22034/cmde.2026.70358.3490 | ||
| نویسندگان | ||
| Hero A. Hussein1؛ Younis A. Sabawi* 2 | ||
| 1Department of Mathematics, Faculty of Science and Health, Koya University, Koya KOY45, Kurdistan Region - F.R. Iraq. | ||
| 21. Department of Mathematics, Faculty of Science and Health, Koya University, Koya KOY45, Kurdistan Region - F.R. Iraq. 2. College of Information Technology, Imam Ja’afar AL-Sadiq University, Baghdad, Iraq. | ||
| چکیده | ||
| This paper presents a finite element analysis of the reaction-diffusion system modeling oncolytic M1 virotherapy. The governing PDEs describe coupled biologi cal interactions between tumor cells, viruses, and immune components through non linear reaction terms and diffusion processes. We develop a semi-discrete Galerkin formulation, establishing existence, uniqueness, and convergence of solutions. A comprehensive sensitivity analysis evaluates parameter influences through non normalized, half-normalized, and fully normalized measures, identifying critical therapeutic parameters including viral replication rate (µ) and tumor-virus interac tion coefficients (β3). The numerical implementation demonstrates robust handling of system nonlinearities while preserving key conservation properties. Computa tional results validate the method’s accuracy in capturing spatiotemporal dynamics, particularly in solving emergent patterns in tumor-virus interactions. The frame work provides an effective computational tool for predicting therapeutic outcomes and optimizing treatment parameters in heterogeneous tumor environments, with sensitivity results guiding parameter prioritization for clinical translation. | ||
| کلیدواژهها | ||
| Error estimate؛ Reaction-diffusion system؛ Oncolytic virotherapy؛ Cancer modeling | ||
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آمار تعداد مشاهده مقاله: 42 تعداد دریافت فایل اصل مقاله: 46 |
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