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CORDIS - EU research results
CORDIS

PERSONALIZED ENGINE FOR CANCER INTEGRATIVE STUDY AND EVALUATION

Objective

Despite of their great promise, high-throughput technologies in cancer research have often failed to translate to major therapeutic advances in the clinic. One challenge has been tumour heterogeneity, where multiple competing subclones coexist within a single tumour. Genomic heterogeneity renders it difficult to identify all driving molecular alterations, and thus results in therapies that only target subsets of aggressive tumour cells. Another challenge lies in the integration of multiple types of molecular data into mathematical disease models that can make actionable clinical statements.

We aim to develop predictive computational technology that can exploit molecular and clinical data to improve our understanding of disease mechanisms and to inform clinicians about optimized strategies for therapeutic intervention. We propose to focus on prostate cancer, a leading cause of cancer death amongst men in Europe, but also prone to over-treatment. Our approach combines the exploitation of genomic, transcriptomic, proteomic, and clinical data in primary and metastatic tumours, prospective cohorts of well characterized prostate cancer patients, drug screenings in cell lines, and the use of the Watson technology, a last generation cognitive computer developed at IBM.

The translational objective of this study is to develop technology for identifying disease mechanisms and produce treatment recommendations for individual patients based on a therapeutic biomarker panel. The proposed software framework will be accessible through a graphical interface that will facilitate its dissemination and use by researchers, clinicians, and biomedical industries. The framework will provide intuitive tools to deposit, share, analyze, and visualize molecular and clinical data; as well as to infer prognosis, elucidate implicated mechanisms and recommend therapy accordingly. This software framework will serve as a proof of concept for future development by industrial partners in Europe.

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.

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Programme(s)

Multi-annual funding programmes that define the EU’s priorities for research and innovation.

Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

RIA - Research and Innovation action

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) H2020-PHC-2014-2015

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Coordinator

TECHNIKON FORSCHUNGS- UND PLANUNGSGESELLSCHAFT MBH
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 358 125,00
Address
BURGPLATZ 3A
9500 Villach
Austria

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SME

The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Yes
Region
Südösterreich Kärnten Klagenfurt-Villach
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 358 125,00

Participants (9)

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