@inproceedings{1434d075c9924dc0b9e2954944f17d7d,
title = "Strategies to Reduce Long-Term Drug Resistance by Considering Effects of Differential Selective Treatments",
abstract = "Despite great advances in modeling and cancer therapy using optimal control theory, tumor heterogeneity and drug resistance are major obstacles in cancer treatments. Since recent biological studies demonstrated the evidence of tumor heterogeneity and assessed potential biological and clinical implications, tumor heterogeneity should be taken into account in the optimal control problem to improve treatment strategies. Here, first we study the effects of two different treatment strategies (i.e., symmetric and asymmetric) in a minimal two-population model to examine the long-term effects of these treatment methods on the system. Second, by considering tumor adaptation to treatment as a factor of the cost function, the optimal treatment strategy is derived. Numerical examples show that optimal treatment decreases tumor burden for the long-term by decreasing rate of tumor adaptation over time.",
keywords = "Cancer treatment, Optimal control, Tumor heterogeneity",
author = "{Ghodsi Asnaashari}, Tina and Chang, {Young Hwan}",
note = "Funding Information: This work was supported in part by the National Cancer Institute (U54CA209988). Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 3rd International Symposium on Mathematical and Computational Oncology, ISMCO 2021 ; Conference date: 11-10-2021 Through 13-10-2021",
year = "2021",
doi = "10.1007/978-3-030-91241-3_5",
language = "English (US)",
isbn = "9783030912406",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "49--60",
editor = "George Bebis and Terry Gaasterland and Mamoru Kato and Mohammad Kohandel and Kathleen Wilkie",
booktitle = "Mathematical and Computational Oncology - Third International Symposium, ISMCO 2021, Proceedings",
address = "Germany",
}