Mathematical Details on a Cancer Resistance Model
Abstract
The primary factor limiting the success of chemotherapy in cancer treatment is the phenomenon of drug resistance. We have recently introduced a framework for quantifying the effects of induced and non-induced resistance to cancer chemotherapy [11, 10]. In this work, we expound on the details relating to an optimal control problem outlined in [10]. The control structure is precisely characterized as a concatenation of bang-bang and path-constrained arcs via the Pontryagin Maximum Principle and differential Lie algebra techniques. A structural identifiability analysis is also presented, demonstrating that patient-specific parameters may be measured and thus utilized in the design of optimal therapies prior to the commencement of therapy. For completeness, a detailed analysis of existence results is also included.
02 /Specification & Classification
Click any tag to browse matching papers- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Validation of a Mathematical Model of Cancer Incorporating Spontaneous and Induced Evolution to Drug Resistance
J. L. Gevertz, J. M. Greene, E. D. Sontag·bioRxiv·Dec 27, 2019
- Understanding therapeutic tolerance through a mathematical model of drug-induced resistance
Eduardo D. Sontag, Jana L. Gevertz, … Samantha Prosperi·bioRxiv·Sep 4, 2024
- Optimal drug treatment for reducing long-term drug resistance
Tina Ghodsi Asnaashari, Young Hwan Chang·IEEE Conference on Decision and Control (CDC)Peer-reviewed·Dec 6, 2022
- A mathematical approach to differentiate spontaneous and induced evolution to drug resistance during cancer treatment
J. M. Greene, J. L. Gevertz, E. D. Sontag·bioRxiv·Jul 27, 2018
- The logic of containing tumors
Y. Viossat, R. J. Noble·bioRxiv·Jan 22, 2020
- Optimal Chemotherapy Scheduling for Non-Genetic Drug Resistance
Sasan Paryad-Zanjani, Michael Saint-Antoine, Abhyudai Singh·bioRxiv·May 11, 2021