The overall objective of the REDDIE project is to understand how to better use real-world data to advance research related to diabetes.
- Develop a set of evidentiary standards to be pre-specified and used in analysis of real-world / synthetic data and applied to different types of regulatory advice and/or health-technology assessment
- Address aspects that would enable moving towards a standard data quality framework reproducible across different RWD / synthetic data sources that link RWD with data collected during RCTs
- Enhance performance and efficiency of large RCTs by developing standardised methods to access RWD / synthetic data
- Define methodological standards for the regulatory acceptability of RWD, and/or synthetic data
- Test the ability of machine learning methods to help identify relevant RWD, and/or synthetic data
- Assess and validate machine-learning methods to harness a large amount of unstructured data