Exploring pancreatic cancer cell interactions: A fractional mathematical framework for siRNA therapy assessment
Year: 2026
Type: article
Abstract: 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.
Source: Franklin Open
Authors: Mihir Thakkar, Nimisha Pathak, Dhara Patel, Anil Chavada
Institution: Maharaja Sayajirao University of Baroda
Language: English
Subfield: Modeling and Simulation
Field: Mathematics
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,900
OpenAlex ID: W7128424093