Project description
Personalised medicine strategy for early cancer detection using Big Data tools and AI
Spanish Amadix is a molecular diagnostics company developing innovative diagnostic tests for early cancer detection based on liquid biopsy. The company focuses on non-invasive early cancer detection, working not only at a molecular level but exploring information from clinical records and patient data. It employs the latest AI and advanced data analysis tools to identify new risk factors and develop predictive models to uncover hidden underlying cancer risk factors. The EU-funded AMX DATA project aims to identify risk factors in colon, lung, and pancreatic cancers based on medical history, individual habits, and image analysis using Big Data tools and AI in combination with blood test gene signatures.
Objective
Founded in 2010, AMADIX is a leading molecular diagnostics company focused on liquid biopsy, developing innovative diagnostic tests for early cancer detection in blood. The mission of the company is extending people lives, developing disruptive technologies to detect the tumor years in advance, before the symptoms appear. The company’s products are oriented to non-invasive early cancer detection, avoiding the complications of existing invasive procedures, as tumor biopsies in colon, lung and pancreatic cancer.
The application of Advanced Data Analytical tools in healthcare has a lot of positive and also life-saving potential. When speaking about data, we are referring to the vast quantities of information created in digitization of medical documents, and that could be consolidated and analyzed applying specific technologies. Aligned with our mission, AMADIX continues to go further, not only working at a molecular level but also exploring possibilities that clinical records and patient data offer (particular conditions, lifestyle, living area…). We are registering, processing and analyzing data through the latest Artificial Intelligence (AI) and Advanced Data Analytical Tools, in order to identify new risk factors, to develop predictive models which will help us anticipate hidden underlying cancer risk factors, treat patients in time and help improve the quality of life and survival of cancer patients. So, as an overview, the objective of AMX DATA is identifying risk factors in colon, lung and pancreatic cancer based on medical history, individual habits and image analysis to incorporate new risk cancer factors - in combination with our blood test gene signature - into our algorithms using Big Data tools and Artificial Intelligence.
The development of this disruptive project requires the recruitment of an Innovation Associate with a multidisciplinary set of skills combining expertise and knowledge in cancer diagnostics and data analysis tools.
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.
- natural sciences computer and information sciences artificial intelligence
- natural sciences computer and information sciences data science big data
- medical and health sciences clinical medicine oncology colorectal cancer
- engineering and technology medical engineering medical laboratory technology laboratory samples analysis
- medical and health sciences clinical medicine oncology pancreatic cancer
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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-LSP - Coordination and support action Lump sum
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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.
47004 Valladolid
Spain
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.