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Research Article | Open Access

Chemo-immunotherapy for optimal control of Tumor using Hilfer fractional derivative

K. Ramalakshmi1B. Sundara Vadivoo2Dilber Uzun Ozsahin3,4,5Hijaz Ahmad5,6( )Taha Radwan7( )
Department of Mathematics, Alagappa University, Karaikudi-630 004, India
Department of Mathematics, Central University of Tamil Nadu, Thiruvarur-610 005, India
Department of Medical Diagnostic Imaging, College of Health Sciences, University of Sharjah, UAE
Research Institute for Medical and Health Sciences, University of Sharjah, UAE
Operational Research Center in Healthcare, Near East University, Nicosia/TRNC, 99138 Mersin 10, Turkey
Department of Mathematics, College of Science, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, South Korea
Department of Management Information Systems, College of Business and Economics, Qassim University, Buraydah 51452, Saudi Arabia
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Abstract

This research investigated an optimal control problem formulated using a Hilfer fractional-order differential model to describe the dynamics between tumor cells and the immune system during immuno-chemotherapy. The model emphasized the activation timing of effector cells and their capacity to generate a potent immune response against the tumor. The primary objective was to minimize the costs associated with immuno-chemotherapy while simultaneously reducing the tumor cell population through optimal control strategies. By solving both the state and adjoint equations, the optimal control problem was addressed numerically. Simulation results demonstrated that the proposed immuno-chemotherapy protocol significantly reduced the tumor burden.

CLC number: 26A33, 49K05, 92C50

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AIMS Mathematics
Pages 19512-19539

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Cite this article:
Ramalakshmi K, Vadivoo BS, Ozsahin DU, et al. Chemo-immunotherapy for optimal control of Tumor using Hilfer fractional derivative. AIMS Mathematics, 2025, 10(8): 19512-19539. https://doi.org/10.3934/math.2025871

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Received: 01 June 2025
Revised: 25 July 2025
Accepted: 06 August 2025
Published: 15 August 2025
©2025 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)