Exploiting grid technologies for the simulation of clinical trials: The paradigm of in silico radiation oncology

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Abstract

In silico (on the computer) oncology is a complex and multiscale combination of sciences and technologies that focuses on the study and modelling of biological mechanisms related to the phenomenon of cancer at all levels of biocomplexity. In silico oncology simulation models may be used for evaluating and comparing different therapeutic schemes, while at the same time considering different values of critical parameters which present substantial inter-patient variability. As the number of the involved parameters characterizing both the complex tumour biosystem and possible treatment schemes increases, the resulting exponential increase in computational requirements makes the use of a grid environment for the execution of the simulations a particularly attractive solution. In this paper, a grid-enabled simulation environment for the execution of in silico oncology radiotherapy simulations on grid infrastructures is presented and implementation details are discussed. The environment provides a web portal as the end-user interface and contains advanced features that facilitate the execution of in silico oncology simulations in grid environments. Special consideration has been given during the development of the environment in order to simplify the maintenance and extension of the application, while additional services for Quality of Service provisioning have been applied. The simulation environment has been employed in order to perform several scenarios of glioblastoma multiforme radiotherapy simulations on the Enabling Grids for E-sciencE (EGEE) grid infrastructure. Indicative simulation results, as well as statistics regarding execution times on the grid, are presented. © 2010, SAGE Publications. All rights reserved.

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Athanaileas, T., Menychtas, A., Dionysiou, D., Kyriazis, D., Kaklamani, D., Varvarigou, T., … Stamatakos, G. (2011). Exploiting grid technologies for the simulation of clinical trials: The paradigm of in silico radiation oncology. SIMULATION, 87(10), 893–910. https://doi.org/10.1177/0037549710375437

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