Towards Personalized Prostate Cancer Therapy Using Delta-Reachability Analysis

Autor:	Liu, Bing, Kong, Soonho, Gao, Sicun, Zuliani, Paolo, Clarke, Edmund M.
Rok vydání:	2014
Předmět:	Quantitative Biology - Quantitative Methods Computer Science - Logic in Computer Science
Druh dokumentu:	Working Paper
DOI:	10.1145/2728606.2728634
Popis:	Recent clinical studies suggest that the efficacy of hormone therapy for prostate cancer depends on the characteristics of individual patients. In this paper, we develop a computational framework for identifying patient-specific androgen ablation therapy schedules for postponing the potential cancer relapse. We model the population dynamics of heterogeneous prostate cancer cells in response to androgen suppression as a nonlinear hybrid automaton. We estimate personalized kinetic parameters to characterize patients and employ $\delta$-reachability analysis to predict patient-specific therapeutic strategies. The results show that our methods are promising and may lead to a prognostic tool for personalized cancer therapy. Comment: HSCC 2015
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1410.7346 Zobrazit plný text záznamu View this record from Arxiv