Project description
The making of smart diagnostic technologies
Artificial intelligence (AI) and the big data are making a huge impact in all industries, including medical diagnostics. The EU-funded AI-PATH project, coordinated by the Ellogon AI start-up, will develop innovative original approaches for analysing complex histopathology images of tumour biopsies by directly combining them with treatment outcomes. This unique approach is based on the use of self-learning algorithms that allow for the analysis of whole-slide image big data and the almost perfectly accurate identification and detection of cellular structures that could be cancer biomarkers. Ellogon AI’s first product will be an AI-driven digital biomarker to assess the antitumour immune response in biopsies.
Objective
Ellogon AI is an innovative start-up established in 2019 as a spin-off from University of Amsterdam, by leading academic experts in artificial intelligence, medical imaging, and computational pathology. The company develops a unique approach to analysis of complex histopathology images of tumour biopsies by directly connecting them to treatment outcomes. The developed technology is based on self-learning algorithms able to analyse whole-slide image big data and with a near-perfect accuracy to identify and detect specific cellular structures serving as potential cancer biomarkers. The company’s leading product will be the first AI-driven digital biomarker to assess the anti-tumor immune response in biopsies using identification and quantification of tumour infiltrating lymphocytes (TILs). The company’s future strategy is to integrate clinical/genomic data with multiple visual biomarkers for >95% accurate diagnostics and prediction of treatment outcome. Currently, only the management team works for the company and seeks to recruit the core technology expert associate that will be in charge of the technology development, with the outlook to become the leader of the development team and eventually the chief technology officer (CTO). In the company’s strategy to build leading technology expert team, filling this particular vacancy represent the critical recruitment milestone. The associate will develop and expand skills in high-performance machine learning applications working with state-of-the-art deep learning models, but also towards managing position in innovative small enterprise. The proposed grant will allow the company to secure the necessary financial resources to overcome the competition (scarcity in the candidates/ salary level) and resources barrier, as well as the visibility barrier to attract the needed expert. Competition in the national market is severe, hence acquiring talent outside the Netherlands is necessary.
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: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- medical and health sciences clinical medicine oncology
- medical and health sciences basic medicine pathology
- natural sciences computer and information sciences artificial intelligence machine learning deep learning
- medical and health sciences basic medicine immunology immunotherapy
- engineering and technology medical engineering diagnostic imaging
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.2.3. - INDUSTRIAL LEADERSHIP - Innovation In SMEs
MAIN PROGRAMME
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H2020-EU.2.3.2.2. - Enhancing the innovation capacity of SMEs
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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.
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.
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.
CSA - Coordination and support action
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-INNOSUP-2018-2020
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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.
1094GG Amsterdam
Netherlands
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
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.