Exploring pancreatic cancer cell interactions: A fractional mathematical framework for siRNA therapy assessment

This research investigates the efficacy of siRNA therapy in mitigating pancreatic cancer through a fractional-order mathematical framework. Utilizing the Caputo–Fabrizio derivative to capture memory-dependent tumor–immune–cytokine interactions, we formulate and rigorously analyze distinct systems for untreated evolution and siRNA-mediated intervention. Following the establishment of mathematical well-posedness and stability via the basic reproduction number, numerical simulations demonstrate that siRNA treatment effectively curtails tumor growth and bolsters sustained immune responses. Validating the efficacy of fractional-order modeling in portraying memory-driven dynamics, the findings biologically indicate that silencing tumor-promoting cytokines facilitates the restoration of immune function, thereby retarding cancer progression. Ultimately, this study underscores the critical role of immune feedback and temporal cellular dynamics in refining future siRNA therapeutic strategies.