TY - GEN
T1 - Optimal drug treatment for reducing long-term drug resistance
AU - Asnaashari, Tina Ghodsi
AU - Chang, Young Hwan
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
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U2 - 10.1109/CDC51059.2022.9992804
DO - 10.1109/CDC51059.2022.9992804
M3 - Conference contribution
AN - SCOPUS:85147002942
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 3213
EP - 3218
BT - 2022 IEEE 61st Conference on Decision and Control, CDC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 61st IEEE Conference on Decision and Control, CDC 2022
Y2 - 6 December 2022 through 9 December 2022
ER -