NDLI: Towards tumor growth control subject to reduced toxicity

Content Provider	IEEE Xplore Digital Library
Author	Hadjiandreou, M.M. Mitsis, G.D.
Copyright Year	2012
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Univ. of Cyprus, Nicosia, Cyprus (Hadjiandreou, M.M.; Mitsis, G.D.)
Abstract	This study examines the application of mathematical modeling and optimal control in the investigation of optimal cancer therapy. We present models to predict cancer dynamics in mice with colon cancer as well as pharmacokinetic and drug-related toxicity models to study the effect of anti-cancer agents irinotecan and 5-fluorouracil. We present two methodologies which can be used to design optimal therapies subject to reduced toxicity. The first methodology employs a toxicity model based on body weight loss as is usually the case in an experimental setting whilst the other utilises a well-documented side-effect chart to quantify overall toxicity. These drug-specific formulations are proved to be especially useful when formulating multidrug therapies. Our models replicate both tumor and toxicity data successfully and can be used in treatment planning. The optimal control results suggest that optimal therapy is a balance between minimum toxicity and minimum tumor growth. Whilst in the original experimental studies from which the data was extracted, treatment was not succesful in controlling tumor growth, our schedules successfully control growth while at the same time preventing undesirable toxicity beyond the tolerated limits set by experimental guidelines. The control study on the combination 5-FU/CPT-11 favours 5-FU administration, the main reason being that this drug has been shown experimentally to be less toxic. Lastly, we show that combination therapy is more effective than monotherapy.
Sponsorship	IEEE Control Syst. Soc.
Starting Page	5592
Ending Page	5597
File Size	472554
Page Count	6
File Format	PDF
ISBN	9781457710957
ISSN	07431619
e-ISBN	9781457710964
e-ISBN	9781467321020
DOI	10.1109/ACC.2012.6314734
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-27
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	American Automatic Control Council(AACC)
Subject Keyword	Drugs Tumors Cancer Mice Data models Optimal control
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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