Colorectal tumour simulation using agent based modelling and high performance computing
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10.1016/j.future.2016.03.026
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/88828
Tipus de documentArticle
Data publicació2016-04-11
EditorElsevier
Condicions d'accésAccés obert
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Reconeixement-NoComercial-SenseObraDerivada 4.0 Internacional
Abstract
450,000 European citizens are diagnosed every year with colorectal cancer (CRC) and more than 230,000 succumb to the disease annually. For this reason, significant resources are dedicated to the identification of more effective therapies for this disease. However, classical assessment techniques for these treatments are slow and costly. Consequently, systems biology researchers at the Royal College of Surgeons in Ireland (RCSI) are developing computational agent-based models simulating tumour growth and treatment responses with the objective of speeding up the therapeutic development process while, at the same time, producing a tool for adapting treatments to patient-specific characteristics. However, the model complexity and the high number of agents to be simulated require a thorough optimisation of the process in order to execute realistic simulations of tumour growth on currently available platforms. We propose to apply the most advanced HPC techniques to achieve the efficient and realistic simulation of a virtual tissue model that mimics tumour growth or regression in space and time. These techniques combine extensions of the previously developed agent-based simulation software platform (FLAME) with autotuning capabilities and optimisation strategies for the current tumour model. Development of such a platform could advance the development of novel therapeutic approaches for the treatment of CRC which can also be applied other solid tumours.
CitacióKang, Guiyeom [et al.]. Colorectal tumour simulation using agent based modelling and high performance computing. "Future Generation Computer Systems", 11 Abril 2016.
ISSN0167-739X
Versió de l'editorhttp://www.sciencedirect.com/science/article/pii/S0167739X16300723
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