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Fractional-Order Modeling and Neural Network Simulation of NK Cell-Oncolytic Virus Interactions

Year: 2025

Type: article

Abstract: Oncolytic virotherapy (OV) uses viruses to selectively destroy cancer cells, but the role of natural killer (NK) cells ‎in this process remains unclear. This study develops a discrete fractional-order model to examine NK cell activity ‎and identify activation conditions. Existence of the model solution is established via fixed-point theorems, and ‎the basic reproduction number (R_0) is derived using the next-generation matrix method with sensitivity analysis ‎to determine key parameters. Stability of equilibria is analyzed, and numerical simulations reveal how NK cell ‎activation affects interactions among cancer cells, infected cells, and viruses. Additionally, an artificial neural ‎network (ANN) trained with the Levenberg-Marquardt algorithm efficiently approximates the model's dynamics, ‎showing high accuracy (low MSE) and providing a rapid, reliable tool for predicting complex biological behaviors.

Source: International Journal of Basic and Applied Sciences

DOI: 10.14419/9pjcye33

Authors: M. Sharmila, S. Indrakala

Institutions: Bharathidasan University, Kunthavai Naacchiyaar Government Arts College for Women (Autonomous)

Topic: Mathematical Biology Tumor Growth

Subfield: Modeling and Simulation

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: diamond

OpenAlex ID: W4417036463

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