Summary
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.
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| Web resources: | https://cordis.europa.eu/project/id/957075 |
| Start date: | 01-10-2020 |
| End date: | 31-01-2022 |
| Total budget - Public funding: | - 99 750,00 Euro |
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Original description
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.Status
CLOSEDCall topic
INNOSUP-02-2019-2020Update Date
27-10-2022
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