Multi-agent Modeling Simulation of In-vitro T-cells for Immunologic Alternatives to Cancer Treatment

David Nettleton, Vladimir Estivill-Castro, Vladimir Estivill-Castro, Enrique Jiménez

2020

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.

Paper Citation

in Harvard Style

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, pages 169-178. DOI: 10.5220/0008915601690178

in Bibtex Style

@conference{icaart20,
author={David Nettleton and Vladimir Estivill-Castro and Enrique 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},
}

in EndNote Style

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
AU - Nettleton D.
AU - Estivill-Castro V.
AU - Jiménez E.
PY - 2020
SP - 169
EP - 178
DO - 10.5220/0008915601690178