Objective
Acute Lymphoblastic Leukaemia is the most frequent leukaemia entity in children and adolescents. Despite continued progress and refinement of therapeutic approaches, disease relapse due to insufficient extinction of leukaemic blasts still remains the number one cause of treatment failure. About 15-20% of paediatric patients with the disease still suffer from relapse. Flow cytometry (FCM) is one of the methodologies most useful in this respect, because it is widely available and applicable to most patients. While sample preparation, antibody panels, staining procedures, and FCM acquisition can be harmonized straightforwardly, data analysis and interpretation rely largely on operator skills and experience. These assessments are time-consuming and costly to be attained via staff-training, online support between twinning laboratories, and continued quality control. Hence, these requirements represent the current bottleneck of safely applying the FCM-Minimal Residual Desease (MRD) methodology in a growing community of diagnostic laboratories to the benefit of an increasing number of patients with leukaemia.
To address this bottleneck, AutoFLOW aims at developing an objective and automated tool for multi-parameter FCM data analysis with robust and reliable MRD quantification. The consortium aims at engaging professionals from the medical and ICT fields in a network where the exchange of knowledge will culminate in a valid solution for automated FCM analysis for clinical follow-up assessment of Acute Lymphoblastic Leukaemia (ALL). Additionally, AutoFLOW is expected to gain better career perspectives for the involved personnel and increase the competitiveness of the participating SMEs.
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: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciences computer and information sciences data science
- social sciences sociology industrial relations automation
- medical and health sciences clinical medicine oncology leukemia
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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.
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.
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.
FP7-PEOPLE-2013-IAPP
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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.
MC-IAPP - Industry-Academia Partnerships and Pathways (IAPP)
Coordinator
1040 Wien
Austria
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.