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MEDIVAC TERMINATED

Machine learning software to design personalized neoantigen vaccines tailored to specific vaccine delivery systems

Total Cost €

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EC-Contrib. €

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Partnership

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 MEDIVAC project word cloud

Explore the words cloud of the MEDIVAC project. It provides you a very rough idea of what is the project "MEDIVAC" about.

scalable    proprietary    utilize    vaccine    identifies    delivering    tissue    once    roll    serve    untapping    status    tumor    trained    core    perform    engineering    rna    mass    medicine    destroying    readily    time    personalisation    data    consuming    winning    optimise    exists    therapy    age    nobel    regarded    clinically    learning    sensitive    accuracy    gap    spectroscopy    cancer    datasets    samples    subsequently    machine    identification    immunogenic    avenue    dna    meets    regardless    prohibits    fold    lives    lab    healthy    grail    intensive    holy    revolutionize    akey    oi    immunotherapy    expensive    business    patient    competitive    neoantigens    solution    diseases    immunotherapies    immense    arguably    fact    constructs    despite    framework    victims    feared    performance    algorithms    public    cure    fuel    considering    opportunity    wet    fed    vaccines    generation    coupled    ngs    unmatched    neoantigen    candidates    personalised    oncoimmunity    sequencing    reached    fight    prediction    company    bridge    cornerstone   

Project "MEDIVAC" data sheet

The following table provides information about the project.

Coordinator
ONCOIMMUNITY AS 

Organization address
address: ULLERNCHAUSSEEN 64
city: OSLO
postcode: 379
website: n.a.

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Norway [NO]
 Total cost 3˙143˙437 €
 EC max contribution 2˙200˙406 € (70%)
 Programme 1. H2020-EU.3. (PRIORITY 'Societal challenges)
2. H2020-EU.2.3. (INDUSTRIAL LEADERSHIP - Innovation In SMEs)
3. H2020-EU.2.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies)
 Code Call H2020-SMEInst-2018-2020-2
 Funding Scheme SME-2
 Starting year 2019
 Duration (year-month-day) from 2019-05-01   to  2021-10-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    ONCOIMMUNITY AS NO (OSLO) coordinator 2˙200˙406.00

Map

Leaflet | Map data © OpenStreetMap contributors, CC-BY-SA, Imagery © Mapbox

 Project objective

Cancer is arguably the most feared of all diseases, destroying lives regardless of the age of its victims. Immunotherapies are currently regarded as the most promising avenue to delivering the holy grail of medicine i.e. providing a cure for cancer. Despite their Nobel-winning status, personalisation of immunotherapies remains akey challenge to which no cost-effective solution currently exists. Current methods for identifying the immunogenic neoantigens required to design patient-specific cancer vaccines typically utilize next generation sequencing (NGS) analysis of DNA and RNA coupled with wet lab methods (e.g. spectroscopy). However, these approaches are time consuming to perform, expensive and not readily scalable–which currently prohibits the mass roll-out of personalised cancer vaccines.

Despite the fact that intensive research has been dedicated to developing prediction algorithms which can identify immunogenic neoantigens from NGS data from tumor samples, their accuracy has not yet reached a competitive performance compared to wet lab methods. To bridge this gap, OncoImmunity (OI) has developed a comprehensive machine learning framework, trained using public and proprietary datasets to optimise performance. Once fed with patient NGS data from healthy and tumor tissue, OI’s algorithms identifies the most clinically relevant neoantigen candidates, with an unmatched accuracy (4-fold increase of prediction accuracy), which can be subsequently engineering into personalised vaccine cancer constructs.

Considering the potential of personalised therapy within cancer immunotherapy, OI’s core technology meets all the requirements to become a key enabling technology, providing cost-effective, scalable and sensitive identification of clinically relevant targets for vaccine development. Thus, it has the potential to serve as a cornerstone to revolutionize the fight against cancer – while untapping an immense business opportunity to fuel our company’s growth.

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The information about "MEDIVAC" are provided by the European Opendata Portal: CORDIS opendata.

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