Optimal drug treatment for reducing long-term drug resistance

Tina Ghodsi Asnaashari, Young Hwan Chang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The maximum-tolerated dose principle, the highest possible drug dose in the shortest possible time period, has been the standard care for cancer treatment. Although it is appealing in a homogeneous tumor setting, tumor heterogeneity and adaptation play a significant role in driving treatment failure. They are still major obstacles in cancer treatments despite great advances in modeling and cancer therapy using optimal control theory. To address this, we first generalize two population models and examine the long-term effects of differential selective treatment strategies. Second, we take into account different drug-imposed selective pressure into designing optimal treatment strategies. Numerical examples demonstrate that the proposed treatment strategy decreases long-term tumor burden by decreasing the rate of tumor adaptation.

Original languageEnglish (US)
Title of host publication2022 IEEE 61st Conference on Decision and Control, CDC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3213-3218
Number of pages6
ISBN (Electronic)9781665467612
DOIs
StatePublished - 2022
Event61st IEEE Conference on Decision and Control, CDC 2022 - Cancun, Mexico
Duration: Dec 6 2022Dec 9 2022

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume2022-December
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Conference

Conference61st IEEE Conference on Decision and Control, CDC 2022
Country/TerritoryMexico
CityCancun
Period12/6/2212/9/22

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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