Colorectal tumour simulation using agent based modelling and high performance computing
Authored by Eduardo Cesar, Guiyeom Kang, Claudio Marquez, Ana Barat, Annette T Byrne, Jochen H M Prehn, Joan Sorribes
Date Published: 2017
DOI: 10.1016/j.future.2016.03.026
Sponsors:
European Union
Platforms:
FLAME
Model Documentation:
Other Narrative
Flow charts
Pseudocode
Model Code URLs:
Model code not found
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. (C) 2016 Elsevier B.V.
All rights reserved.
Tags
agent based modelling and simulation (ABMS)
growth
Systems-analysis
Colorectal cancer (crc)
High performance computing (hpc)
Load balancing
Apoptosis protein