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Defining a simulation strategy for cancer immunocompetence

Figueredo, Grazziela P.; Aickelin, Uwe

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Authors

Uwe Aickelin



Contributors

Emma Hart
Editor

Chris McEwan
Editor

Jon Timmis
Editor

Andy Hone
Editor

Abstract

Although there are various types of cancer treatments, none of these currently take into account the effect of ageing of the immune system and hence altered responses to cancer. Recent studies have shown that in vitro stimulation of T cells can help in the treatment of patients. There are many factors that have to be considered when simulating an organism’s immunocompetence. Our particular interest lies in the study of loss of immunocompetence with age. We are trying to answer questions such as: Given a certain age of a patient, how fit is their immune system to fight cancer? Would an immune boost improve the effectiveness of a cancer treatment given the patient’s immune phenotype and age? We believe that understanding the processes of immune system ageing and degradation through computer simulation may help in answering these questions. Specifically, we have decided to look at the change in numbers of naive T cells with age, as they play a important role in responses to cancer and anti-tumour vaccination. In this work we present an agent-based simulation model to understand the interactions which influence the naive T cell populations over time. Our agent model is based on existing mathematical system dynamic model, but in comparisons offers better scope for customisation and detailed analysis. We believe that the results obtained can in future help with the modelling of T cell populations inside tumours.

Citation

Figueredo, G. P., & Aickelin, U. (2010, July). Defining a simulation strategy for cancer immunocompetence. Presented at 9th International Conference, ICARIS 2010, Edinburgh, UK

Presentation Conference Type Edited Proceedings
Conference Name 9th International Conference, ICARIS 2010
Start Date Jul 26, 2010
End Date Jul 29, 2010
Publication Date Jan 1, 2010
Deposit Date Jan 31, 2012
Publicly Available Date Jan 31, 2012
Publisher Springer
Peer Reviewed Peer Reviewed
Pages 4-17
Series Title Lecture notes in computer science
Series Number 6209
Series ISSN 1611-3349
Book Title Artificial immune systems
ISBN 9783642145469
Public URL https://nottingham-repository.worktribe.com/output/1012551
Publisher URL https://link.springer.com/chapter/10.1007/978-3-642-14547-6_2
Additional Information The original publication is available at www.springerlink.com)

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