Project description
Virtual mechanistic modelling to predict personalised therapies for paediatric cancers
The EU-funded iPC project is developing a personalised medicine approach for children with cancer, focussing on high-incidence and high-risk paediatric tumours. This computational effort will combine knowledge-based, machine-learning and mechanistic models to predict optimal standard and experimental therapies for each child. The approach is based on virtual patient models whose analysis will inform personalised diagnostics and recommend treatments. The consortium comprises experts in basic, translational and clinical research, and it has established strong relationships with prestigious patient organisations and clinical trials focussed on personalised medicine for the proposed case studies.
Objective
Effective personalized medicine for paediatric cancers must address a multitude of challenges, including domain-specific challenges. To overcome these challenges, we propose a comprehensive computational effort to combine knowledge-base, machine-learning, and mechanistic models to predict optimal standard and experimental therapies for each child. Our approach is based on virtual patient models–in-silico avatars whose analysis can inform personalized diagnostics and recommend treatments. Our platform will also allow care givers to query models and infer benefits and drawbacks for specific treatment combinations for each child. To construct these models, we will combine state-of-the-art computational methods and data from molecular assays, and clinical and preclinical studies. We will test their predictions prospectively on data from clinical trials and test therapies in pre-clinical settings. We will focus on a select panel of paediatric tumours including both high-incidence and high-risk tumour types. To accomplish our goals, we have assembled an interdisciplinary team consisting of basic, translational, and clinical researchers—all amongst the leaders in their respective fields—and established strong relationships with European Centres of Excellence, patient organizations, and clinical trials focus on personalized medicine for our proposed case studies. We will produce, assemble, standardize, and harmonize accessible high-quality multi-disciplinary data and leverage the potential of Big Data and HPC for the personalized treatments of European citizens. We will make our models and data available through a cloud-based platform, whose exploitation will be maximised through a collaboration with the European Open Science Cloud initiative. In summary, iPC will address the critical need for personalized medicine for children with cancer, contribute to the digitalization of clinical workflows, and enable the Digital Single Market of the EU data infrastructure.
Fields of science
- natural sciencescomputer and information sciencesdata sciencebig data
- natural sciencescomputer and information sciencescomputational science
- medical and health sciencesclinical medicineoncology
- medical and health scienceshealth sciencespersonalized medicine
- medical and health sciencesclinical medicinepaediatrics
Keywords
Programme(s)
Funding Scheme
RIA - Research and Innovation actionCoordinator
9500 Villach
Austria
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
Participants (22)
8803 Rueschlikon
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77030 Houston Tx
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75231 Paris
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64289 Darmstadt
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80138 Napoli
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9000 Gent
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08034 Barcelona
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Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
08003 Barcelona
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1000 Ljubljana
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
3584CS Utrecht
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80539 Munchen
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1081 HV Amsterdam
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69120 Heidelberg
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08916 Badalona Barcelona
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12489 Berlin
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
8006 Zurich
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69120 Heidelberg
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80539 Muenchen
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19104 Philadelphia
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00185 Roma
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2145 Westmead, New South Wales
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10117 Berlin
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