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AutoFlow

Financiado

Cerrado

Automation of Flow Cytometric Analysis for Quality Assured Follow up Assessment...

Automation of Flow Cytometric Analysis for Quality Assured Follow up Assessment to Guide Curative Therapy for Acute Lymphoblastic Leukaemia in Children 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 blas... ver más

31/01/2018

TU WIEN

2M€

Presupuesto del proyecto: 2M€

Líder del proyecto

TECHNISCHE UNIVERSITAET WIEN No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Ver 5 Participantes

Financiación concedida El organismo FP7 notifico la concesión del proyecto el día 2018-01-31 No tenemos la información de la convocatoria

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Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

5 Participantes

TU WIEN

0.00€ | Lider

COGVIS GMBH

N.D. | Participante

CHARITE UNIVERSITAETSMEDIZI...

N.D. | Participante

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Líder del proyecto

TECHNISCHE UNIVERSITAET WIEN No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 2M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto 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.

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