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REBECCA

Financiado

Cerrado

REsearch on BrEast Cancer induced chronic conditions supported by Causal Analysi...

REsearch on BrEast Cancer induced chronic conditions supported by Causal Analysis of multi source data The REBECCA proposal aspires to tap into the potential of Real-world Data (RWD) for supporting groundbreaking clinical research on complex chronic conditions (CCC) as a complement to Randomised Controlled Trials (RCT). REBECCA mov... ver más

30/09/2025

ARISTOTLE UNIVERSI...

5M€

Presupuesto del proyecto: 5M€

Líder del proyecto

ARISTOTELIO PANEPISTIMIO THESSALONIKIS 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 13 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2021-01-18

SC1-DTH-12-2020: Use of Real-World Data to advance r... Specific Challenge:The number of people with chronic illness is growing and almost half of them have...

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Este proyecto no cuenta con búsquedas de partenariado abiertas en este momento.

Información adicional privada

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13 Participantes

ARISTOTLE UNIVERSITY OF THES...

827.56K€ | Lider

FUNDICIONES DEL ESTANDA

373.40K€ | Participante

291.44K€ | Participante

EIGHT BELLS LTD

221.25K€ | Participante

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Duración del proyecto: 56 meses Fecha Inicio: 2021-01-18
Fecha Fin: 2025-09-30

Líder del proyecto

ARISTOTELIO PANEPISTIMIO THESSALONIKIS No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 5M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto The REBECCA proposal aspires to tap into the potential of Real-world Data (RWD) for supporting groundbreaking clinical research on complex chronic conditions (CCC) as a complement to Randomised Controlled Trials (RCT). REBECCA moves beyond the analysis of Electronic health records (EHR), by combining it with detailed monitoring data from multiple wearable, online behaviour and registry data to monitor patients’ functional, emotional and Quality of Life trajectories, with high temporal granularity. REBECCA also proposes explainable causal modelling combined with deep learning to account for observed and latent confounders in RWD analysis. The project will focus on the complex array of chronic comorbidities developed during breast cancer recovery, in particular studying the impact of primary and adjuvant cancer treatment on patients’ quality of life and assessing the value of detailed patient monitoring as a means for improved patient care, but will also demonstrate the extensibility of REBECCA to other forms of cancer. To this end, a total of seven studies in Sweden, Norway and Spain will produce new knowledge on clinical management of cancer patients that will shape future guidelines and practices for post-cancer treatments. Best practices resulting from the REBECCA studies will be disseminated to researchers, public health and regulatory bodies throughout Europe to facilitate wider adoption of RWD in clinical research. In addition, the REBECCA platform, capable of detailed monitoring and privacy-preserving federated cross-country data analysis, will provide an infrastructure for continued progress on use of RWD beyond the end of the project. Through these activities, REBECCA aims at the mass adoption of RWD for understanding CCCs and ultimately at establishing RWD as a valuable clinical research and patient management tool.

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