Controlled and uncontrolled stochastic Norton-Simon-Massagué tumor growth models Conference Paper
| Authors: | Belkhatir, Z.; Pavon, M.; Mathews, J. C.; Pouryahya, M.; Deasy, J. O.; Norton, L.; Tannenbaum, A. R. |
| Title: | Controlled and uncontrolled stochastic Norton-Simon-Massagué tumor growth models |
| Conference Title: | 58th IEEE Conference on Decision and Control (CDC 2019) |
| Abstract: | Tumorigenesis is a complex process that is heterogeneous and affected by numerous sources of variability. This study presents a stochastic extension of a biologically grounded tumor growth model, referred to as the Norton-Simon-Massague (NSM) tumor growth model. We first studý the uncontrolled version of the model where the effect of chemotherapeutic drug agent is absent. Conditions on the model's parameters are derived to guarantee the positivity of the tumor volume and hence the validity of the proposed stochastic NSM model. To calibrate the proposed model we utilize a maximum likelihood-based estimation algorithm and population mixed-effect modeling formulation. The algorithm is tested by fitting previously published tumor volume mice data. Then, we study the controlled version of the model which includes the effect of chemotherapy treatment. A closed-loop control strategy that relies on model predictive control (MPC) combined with extended Kalman filter (EKF) is proposed to solve an optimal cancer therapy planning problem. © 2019 IEEE. |
| Keywords: | chemotherapy; tumors; mammals; stochastic models; predictive control systems; controlled drug delivery; maximum likelihood estimation; stochastic systems; chemotherapeutic drugs; tumor growth models; extended kalman filters; model predictive control; chemotherapy treatment; closed loop control strategy; estimation algorithm; mixed-effect models; sources of variability; tumor growth modeling |
| Journal Title | Proceedings of the IEEE Conference on Decision and Control |
| Conference Dates: | 2019 Dec 11-13 |
| Conference Location: | Nice, France |
| ISBN: | 0743-1546 |
| Publisher: | IEEE |
| Date Published: | 2019-01-01 |
| Start Page: | 7530 |
| End Page: | 7535 |
| Language: | English |
| DOI: | 10.1109/cdc40024.2019.9029755 |
| PROVIDER: | scopus |
| DOI/URL: | |
| Notes: | Conference Paper -- Export Date: 1 May 2020 -- Source: Scopus |
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