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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.

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

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

 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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