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REDDIE

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Real world evidence for decisions in diabetes

Randomised controlled trials are the cornerstone of evidence-based medicine. However, the digitisation of real-world data (RWD) including data from devices, wearables, and electronic health records in large national registries pro... ver más

31/12/2026

Líder desconocido

5M€

Presupuesto del proyecto: 5M€

Líder del proyecto Líder desconocido

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2022-11-22

HORIZON-HLTH-2022-TOOL-11-02: New methods for the effective use o... Expected Outcome:This topic aims at supporting activities that are enabling or contributing to one o...

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

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Duración del proyecto: 49 meses Fecha Inicio: 2022-11-22
Fecha Fin: 2026-12-31

Líder del proyecto Líder desconocido

Presupuesto del proyecto 5M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Randomised controlled trials are the cornerstone of evidence-based medicine. However, the digitisation of real-world data (RWD) including data from devices, wearables, and electronic health records in large national registries provides opportunities to demonstrate efficacy and safety of innovative technologies including drugs, devices, diagnostics, and digital health. These data are particularly relevant to long-term conditions such as diabetes mellitus, where drugs, lifestyle interventions, and digital technologies often work together. To better utilise RWD in diabetes for regulatory decision making, a development of standards, guidance, and an assessment of the efficacy to effectiveness gap is needed. REDDIE (Real-World Evidence for Decisions in Diabetes) aims to explore how RWD can complement RCTs to improve efficacy, safety, and value for money of technologies to prevent and treat diabetes. The overall aim of REDDIE is to support the use of RWD in diabetes and health-related research, which will maximise Europe’s scientific expertise and know-how to benefit people with diabetes, resulting in safer, more efficient, and cost-effective interventions. We thus aim to engage with stakeholders such as regulatory and HTA authorities and co-develop evidentiary standards for the collection, assessment, and acceptability of RWD. We will then develop and validate state-of-the art modelling techniques using synthetic data derived from large national registries to better assess outcomes of interventions using RWD. We will use data from four large national registries to elucidate the gap between outcomes in RCTs and RWD studies, and understand the factors that affect this gap. Finally, we will test the ability of machine learning to facilitate the better use of RWD. REDDIE will generate standards for RWD use for the evaluation of medicines and other interventions by regulatory authorities and HTA bodies.

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