1. Precision Adaptive Hormone Control for Personalized Metastatic Prostate Cancer Treatment
- Author
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Phan, Trung V., Li, Shengkai, Howe, Benjamin, Amend, Sarah R., Pienta, Kenneth J., Brown, Joel S., Gatenby, Robert A., Frangakis, Constantine, Austin, Robert H., and Keverkidis, Ioannis G.
- Subjects
Quantitative Biology - Quantitative Methods ,Nonlinear Sciences - Adaptation and Self-Organizing Systems ,Physics - Biological Physics - Abstract
With the oncologist acting as the ``game leader'', we employ a Stackelberg game-theoretic model involving multiple populations to study prostate cancer. We refine the drug dosing schedule using an empirical Bayes feed-forward analysis, based on clinical data that reflects each patient's prostate-specific drug response. Our methodology aims for a quantitative grasp of the parameter landscape of this adaptive multi-population model, focusing on arresting the growth of drug-resistant prostate cancer by promoting competition across drug-sensitive cancer cell populations. Our findings indicate that not only is it is feasible to considerably extend cancer suppression duration through careful optimization, but even transform metastatic prostate cancer into a chronic condition instead of an acute one for most patients, with supporting clinical and analytical evidence.
- Published
- 2024