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Authors: David F. Nettleton 1 ; Vladimir Estivill-Castro 1 ; 2 and Enrique Hernández Jiménez 3

Affiliations: 1 Department of Information and Communications Technology (DTIC), Universitat Pompeu Fabra, Spain ; 2 School of ICT, Griffith University, Brisbane, Australia ; 3 Institut d’Investigació Biomèdica de Bellvitge, Barcelona, Spain

Keyword(s): Simulation, Multi-agent Systems, Immunology, Cancer Cells.

Abstract: There is exciting news in recent developments suggesting the potential to treat some human cancers by stimulating the patients own immune system. However, there is still much to understand; therefore, modelling the battle between those cells that are constituents of the human immune system against tumorous cells can significantly provide insights as mathematical modelling has done regarding the immune system behaviour against virus infections. In this paper we innovate in two directions. First, we move the modelling of immune struggles from the sphere of ordinary-differential equation models to the modelling by multi-agent simulations. We highlight the advantages of the multi-agent simulation, for example the consideration of elaborate spatial proximity interactions. Secondly, we move away from the realm of infectious diseases to the complex modelling of the stimulation of T-cells and their participation in fighting cancerous cell tumours.

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Paper citation in several formats:
Nettleton, D.; Estivill-Castro, V. and Jiménez, E. (2020). Multi-agent Modeling Simulation of In-vitro T-cells for Immunologic Alternatives to Cancer Treatment. In Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-758-395-7; ISSN 2184-433X, SciTePress, pages 169-178. DOI: 10.5220/0008915601690178

@conference{icaart20,
author={David F. Nettleton. and Vladimir Estivill{-}Castro. and Enrique Hernández Jiménez.},
title={Multi-agent Modeling Simulation of In-vitro T-cells for Immunologic Alternatives to Cancer Treatment},
booktitle={Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2020},
pages={169-178},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008915601690178},
isbn={978-989-758-395-7},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - Multi-agent Modeling Simulation of In-vitro T-cells for Immunologic Alternatives to Cancer Treatment
SN - 978-989-758-395-7
IS - 2184-433X
AU - Nettleton, D.
AU - Estivill-Castro, V.
AU - Jiménez, E.
PY - 2020
SP - 169
EP - 178
DO - 10.5220/0008915601690178
PB - SciTePress

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