Project deliverable Open Access

# D1.2 Initial Agent-Based Model

Project consortium members

### DataCite XML Export

<?xml version='1.0' encoding='utf-8'?>
<identifier identifierType="DOI">10.5281/zenodo.4034023</identifier>
<creators>
<creator>
<creatorName>Project consortium members</creatorName>
</creator>
</creators>
<titles>
<title>D1.2 Initial Agent-Based Model</title>
</titles>
<publisher>Zenodo</publisher>
<publicationYear>2020</publicationYear>
<dates>
<date dateType="Issued">2020-04-30</date>
</dates>
<resourceType resourceTypeGeneral="Text">Project deliverable</resourceType>
<alternateIdentifiers>
<alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/4034023</alternateIdentifier>
</alternateIdentifiers>
<relatedIdentifiers>
<relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.4034022</relatedIdentifier>
<relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/infore-project</relatedIdentifier>
</relatedIdentifiers>
<rightsList>
<rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
</rightsList>
<descriptions>
<description descriptionType="Abstract">&lt;p&gt;This deliverable describes the agent-based model currently used in the Life Science use case of INFORE, the parameters used in its simulation and its HPC implementation. Additionally, we present preliminary results of a model exploration framework that is extremely useful for the study of models&amp;rsquo; parameters.&amp;nbsp;&lt;/p&gt;

&lt;p&gt;The ultimate goal of this use case is to provide a &lt;em&gt;&amp;ldquo;virtual laboratory&amp;rdquo; &lt;/em&gt;for studying cancer growth and evolution by using multiscale models of tumors. Thus, by integrating a center-based agent model into a multiscale model (MSM) allows us to study different aspects crucial for the development and growth of tumors. Indeed, given the biophysical, biochemical, and biomechanical factors present in these problems, MSM can help identify the factors that drive a given treatment to be a success or a failure. This MSM consists of several components and modules that are hereby detailed and that operate at very different time scales: environment, cells, signaling pathways, and cell cycle behavior.&amp;nbsp;&lt;/p&gt;

&lt;p&gt;Furthermore, to scale our simulations we need to parallelize our MSM. With that in mind we have started by parallelizing the environment component, which has the smallest time scale. This successful parallelization enables us to address the parallelization of the cells component, a task that is currently ongoing. These scaled-up simulations using the Barcelona Supercomputing Center (BSC) MareNostrum4 will incorporate forecasting techniques for various events of interest.&amp;nbsp;&lt;/p&gt;

&lt;p&gt;Lastly, we present a model exploration technique that allows us to define the structure and hierarchy of the model&amp;rsquo;s parameters and to evaluate its sensibility to the parameters&amp;rsquo; perturbation. All these developments will facilitate the design of different set-ups that tally cancer tumor growth conditions with increased number of cells, altered microenvironmental physical properties, different cell types, as well as, study the interaction between cancer cells and the immune system.&lt;/p&gt;</description>
</descriptions>
<fundingReferences>
<fundingReference>
<funderName>European Commission</funderName>
<funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
<awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/825070/">825070</awardNumber>
<awardTitle>Interactive Extreme-Scale Analytics and Forecasting</awardTitle>
</fundingReference>
</fundingReferences>
</resource>

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