Work Package 1 will provide a clear organisational framework, guidance and all support mechanisms to enable a smooth project workflow in REDDIE and to ensure that objectives and milestones will be met on time.

The objective of the REDDIE project is to understand how to better use real-world data to advance research related to diabetes. As part of this, exploring the quality of real-world data is key in order to know whether the data can be trusted and for what questions it can be used for.

Work Package 2 aims to identify and evaluate diabetes-related databases from around the world in order to create a comprehensive summary of the data they contain. From this list, we will then aim to establish a set of criteria for assessing their quality, and develop a set of rules that scientists can follow in order to use and develop real-world data sets.

To do this will require a review into existing databases through a literature search and then the supply of key information from the database custodians. We will then develop a set of criteria and guidance through consultations with stakeholders such as scientists, people living with diabetes, policy makers and representatives from industry.

Work Package 3 aims to define methodological standards on how to use RWD and synthetic data to address uncertainties in technologies for diabetes encountered by decision-makers in regulation and HTA. This will be enabled by using RWD and synthetic data, explore advanced analytical methods to enhance and validate diabetes health economic models that underpin decision-making; in partnership with the world-leading public forum in diabetes, the Mount Hoodt Diabetes Challenge Network.

The main objective of work package 4 is to compare results from randomized controlled trials and results from real world data sources on glucose-lowering therapies in diabetes. Real world data is provided by four population based registries: The Danish National Administrative Registers, the German diabetes patient follow-up registry (Diabetes-Patienten-Verlaufsdokumentation, DPV), the Swedish National Diabetes Register (NDR) and the UK National Diabetes Audit (NDA). Together, these databases are considered representative of the European population with diabetes and, furthermore, they complement each other in terms of focus, strengths and limitations. In particular, work package 4 will focus on the benefits and side effects of the following glucose-lowering therapies: insulin analogues, glucagon like peptide 1 receptor agonist and sodium-glucose cotransporter-2 inhibitors.

WP5 - Advanced methodological frameworks for enhancing clinical trials with real-world and virtual evidence

Work Package 5 will advance the existing methods when conducting retrospective observational studies based on real-world data (RWD). Specifically, WP5 will go beyond the current state of the art, where models require manual tuning by the investigators before proceeding with the analyses, by developing a new framework based on machine learning and artificial intelligence for conducting retrospective observational studies in a fully-automatic way.

WP5 will also develop an advanced software tool to construct simulation models based on dynamic Bayesian networks starting from longitudinal RWD. The enhanced tool will overcome the limitations of current state-of-the-art software and include new functionalities to improve the inference phase and facilitate the use of the models for testing interventions on simulated data.

WP5 is led by the team from the University of Padova (UNIPD), Italy, who brings expertise in artificial intelligence, machine learning, and analysis of large databases.

The main objective of WP6 is to collate and report outcomes from WP2 - WP5 to enable key regulatory agencies, HTA bodies, industry, and other stakeholders to accept RWD and synthetic data as relevant adjunct to data from clinical trials using research questions on diabetes mellitus as showcase depending on the needs of stakeholders identified in WP3.

WP7 - Innovation Management: Communication, Dissemination, Exploitation

Innovation management will follow a multidimensional, integrated and impact-oriented approach: It will ensure consistent communication and dissemination, assuring optimal visibility and a wide outreach to relevant stakeholders. Strategic planning and implementation of project exploitation through dedicated innovation management will safeguard that high-quality results are captured, assessed and properly used. A proper IP management strategy will lay the foundation for further exploitation activities taking into account background knowledge of beneficiaries as well as newly created results.