A Bayesian Dynamical Systems Framework for Adaptive Treatment Policies in Metastatic Castration-Resistant Prostate Cancer

Zenodo (CERN European Organization for Nuclear Research) 2026 Preprint Open access

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Authors: Dmytro Ihorovych Faliush
DOI: 10.5281/zenodo.18406515
Cited by: 0

Abstract

This extended manuscript presents a control-theoretic and Bayesian dynamical framework for adaptive therapy in metastatic castration-resistant prostate cancer (mCRPC). Standard oncology rests on an invalid assumption: that tumors are passive masses responding linearly to cytotoxic pressure. In reality, cancer is an adaptive dynamical system with drift fields, attractors, and phase transitions.

Fields of Study & Subjects

Mathematical Biology Tumor Growth Prostate Cancer Treatment and Research Mathematical and Theoretical Epidemiology and Ecology Models

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
28 January 2026
Document type
Preprint