Delaying Cancer Progression by Integrating Toxicity Constraints in a Model of Adaptive Therapy

Authors

• Jana L. Gevertz, The College of New Jersey
• Harsh Vardhan Jain, University of Minnesota
• Irina Kareva, Northeastern University
• Kathleen P. Wilkie, Toronto Metropolitan University
• Joel Brown, Moffitt Cancer Center
• Yitong Pepper Huang, Smith CollegeFollow
• Eduardo Sontag, Northeastern University
• Vladimir Vinogradov, Ohio University
• Mark Davies, Cardiff University

Document Type

Article

Publication Date

2026

Publication Title

npj Systems Biology and Applications

Abstract

Cancer therapies often fail when intolerable toxicity or drug-resistant cancer cells undermine otherwise effective treatment strategies. Over the past decade, adaptive therapy has emerged as a promising approach to postpone emergence of resistance by altering dose timing based on tumor burden thresholds. Despite encouraging results, these protocols often overlook the crucial role of toxicity-induced treatment breaks, which may permit tumor regrowth. Herein, we explore the following question: would incorporating toxicity feedback improve or hinder the efficacy of adaptive therapy? To address this question, we propose a mathematical framework for incorporating toxic feedback into treatment design. We and that the degree of competition between sensitive and resistant populations, along with the growth rate of resistant cells, critically modulates the impact of toxicity feedback on time to progression. Further, our conceptual model identifies circumstances where strategic treatment breaks, which may be based on either tumor size or toxicity, can mitigate over treatment and extend time to progression, both at the baseline parameterization and across a heterogeneous virtual population. Taken together, these findings highlight the importance of integrating toxicity considerations into the design of adaptive therapy.

DOI

https://doi.org/10.1038/s41540-025-00635-6

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Rights

© The Author(s) 2026

Version

Version of Record

Recommended Citation

Gevertz, Jana L.; Jain, Harsh Vardhan; Kareva, Irina; Wilkie, Kathleen P.; Brown, Joel; Huang, Yitong Pepper; Sontag, Eduardo; Vinogradov, Vladimir; and Davies, Mark, "Delaying Cancer Progression by Integrating Toxicity Constraints in a Model of Adaptive Therapy" (2026). Mathematics Sciences: Faculty Publications, Smith College, Northampton, MA.
https://scholarworks.smith.edu/mth_facpubs/208