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Optimal therapeutic methods with random-length response in probabilistic boolean networks

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3 Author(s)
Yousefi, M.R. ; Dept. of Electr. & Comput. Eng., Texas A&M Univ., College Station, TX, USA ; Datta, A. ; Dougherty, E.R.

Any antitumor agent should act very rapidly with high level of efficiency so that it may increase the patient's chance of survival along with a reasonable quality of life during the course of treatment. The goal is to kill as many tumor cells as possible or shift them into a state where they can no longer proliferate. However, biological variabilities among cells in a population and the way they interact with each other or respond to a drug introduce randomness and uncertainty at different levels. This uncertainty should be modeled when designing an intervention strategy. In this paper, we implement a tumor growth model in the presence of the antitumor agent and characterize the variability in the drug response. Then, we present a methodology to devise optimal intervention policies for probabilistic Boolean networks when the antitumor drug has a random-length duration of action.

Published in:

Genomic Signal Processing and Statistics, (GENSIPS), 2012 IEEE International Workshop on

Date of Conference:

2-4 Dec. 2012