AUT Journal of Mathematics and Computing

AUT Journal of Mathematics and Computing

Optimizing neoadjuvant therapy for estrogen receptor positive breast cancer based on evolutionary dynamics

Articles in Press

Document Type : Original Article

Authors
Mahdi Sohrabi-Haghighat
Atefeh Deris
Department of mathematics, Faculty of science, Arak university, Iran
10.22060/ajmc.2025.23602.1289
Abstract
Neoadjuvant therapies are commonly used in the treatment of estrogen receptor-positive breast cancer to reduce tumor burden and metastasis risk. This study employs mathematical modeling, using concepts of dynamic evolution, to determine the optimal neoadjuvant combination of aromatase inhibitors and anti-PD-L1 treatments for reducing both tumor burden and metastasis risk. The problem is formulated as an optimal control problem, and the outcomes of all combination therapies are evaluated, with the optimal therapies identified on the Pareto boundary. The results suggest that the most effective neoadjuvant treatment over a 6-month period involves two months of aromatase inhibitor treatment followed by continuous anti-PD-L1 treatment to minimize tumor volume and metastasis risk. Furthermore, continuous anti-PD-L1 administration is recommended in all treatment strategies on the Pareto boundary.
Keywords
Immune system
Tumor burden
Metastatic risk
Game Theory
Optimal control problem
Subjects
AUT Journal of Mathematics and Computing

Articles in Press, Accepted Manuscript
Available Online from 28 June 2026