Real4Reg will employ use cases for the development, optimisation, and implementation of artificial intelligence and machine learning methods for real-world data (RWD) analyses in regulatory decision-making and health technology assessment (HTA). The selected use cases have practical relevance along the product life cycle. For pre-authorisation and evaluation, Use Case 1 explores the usage of RWD to describe the study population, whereas Use Case 2 will explore the construction of historical arms/synthetic data. For post-authorisation, the usage of RWD to assess safety will be analysed in Use Case 3, and effectiveness and drug repurposing will be addressed in Use Case 4.
Description of study population: breast cancer, ALS
Use Case 1 (description of the study population) aims to assess the value of RWD from national healthcare registers and claims data in generating high-quality, accessible, population-based information on amyotrophic lateral sclerosis and breast cancer (diagnosis, treatment, outcomes).
Historical controls and synthetic data: breast cancer, ALS
Use case 2 seeks to demonstrate how RWD can contribute to answering questions that are not typically answered by clinical trials, due to ethical or practical issues. These questions need to be answered for regulatory evaluation and HTA, in the improvement of external validity and statistical power and precision.
Safety: fluoroquinolones
The overall objective of Use Case 3 is the preparation of a good practice example for safety analyses of Real-World Data (RWD) for the post-authorisation stage and the improvement of methods for risk estimation in observational data. Use Case 3 will also evaluate the impact of regulatory warnings on the use of broad-spectrum antibiotics.
Effectiveness and drug repurposing: SGLT2 Inhibitors
Use Case 4 aims to prepare a good practice example for drug effectiveness and drug repurposing analyses of Real-World Data (RWD) for the drug post-authorisation stage.