Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.biosystems.2010.05.004
Title: Global sensitivity analysis and model-based reactive scheduling of targeted cancer immunotherapy
Authors: Kiran, K.L.
Lakshminarayanan, S. 
Keywords: Dendritic cell therapy
High dimensional model reduction
Intra-patient variability
Reactive scheduling
Issue Date: Aug-2010
Citation: Kiran, K.L., Lakshminarayanan, S. (2010-08). Global sensitivity analysis and model-based reactive scheduling of targeted cancer immunotherapy. BioSystems 101 (2) : 117-126. ScholarBank@NUS Repository. https://doi.org/10.1016/j.biosystems.2010.05.004
Abstract: Intra-patient variability is a key challenge in cancer treatment. This makes it necessary to find the factors affecting tumor growth and accordingly schedule therapies over the treatment horizon for the patient. In this work, model-based studies are performed to investigate these issues for optimal immunotherapeutic intervention. Dendritic cell therapy is a targeted immunotherapy where the dendritic cells and its activating agents such as interleukin are engineered, stimulated to recognize and specifically eradicate tumors. A mathematical model that integrates tumor dynamics and dendritic cell therapy is used to perform the analysis. Global sensitivity analysis of the model is done using high dimensional model reduction (HDMR) technique and the key parameters altering the tumor growth are identified. The variations in these key parameters are deemed to result in intra-patient variability during the treatment phase. Then, reactive scheduling is used to schedule dendritic cell interventions with and without interleukin interventions under the varying conditions of the patient. Moreover, the key parameters obtained from HDMR are verified using the reactive scheduling and nominal scheduling approaches. Besides saving costs, the in silico analysis done in this paper may be useful to the oncology community in designing experiments to clinically measure the influential parameters. It can also be used as a decision making tool to determine the required intervention dosage during the treatment. © 2010 Elsevier Ireland Ltd.
Source Title: BioSystems
URI: http://scholarbank.nus.edu.sg/handle/10635/63980
ISSN: 03032647
DOI: 10.1016/j.biosystems.2010.05.004
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

7
checked on Jul 14, 2018

WEB OF SCIENCETM
Citations

6
checked on Jul 4, 2018

Page view(s)

31
checked on Jul 6, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.