
Real4Reg is a project that unites the efforts of a consortium of 10 partners from 6 European countries, including experts from regulatory agencies, academia, and patient organisations. The project is funded by the European Union and started in January 2023, having a 48-month duration.
Real4Reg will use the potential of new sources of information (real-world data (RWD)) and new technologies (artificial intelligence (AI) and machine learning (ML)), to help the regulatory agencies exploit additional data in making decisions about medicines.
By doing so, the consortium will contribute to promoting and protecting human health and well-being and support the transformation of healthcare systems in their efforts towards equitable access to innovative, sustainable, and effective medicines and healthcare.
The main goal of Real4Reg is to take advantage of AI/ML to investigate the use of real-world data (national healthcare registers and claims data) and to define the methods and standards for decision-making. Thereby, regulatory agencies across Europe will be able to apply these new practices. The project will also provide guidance and training on these subjects.
Data sources from 4 European countries will be analysed in Real4Reg: Denmark, Germany, Finland, and Portugal. When dealing with data about people’s health, it is crucial to meet privacy and ethical requirements. Real4Reg will ensure these important aspects, treating the data in a non-identifiable way. Only the essential data for the study will be requested and analysed.
The Real4Reg project will have 4 major tasks investigating different disease areas and medicine’s use:
- To describe the characteristics of the patients diagnosed with a disease, improving knowledge about the condition. Real4Reg will use real-world data from national healthcare registers and claims data, which provide a large amount of information, to describe the population living with breast cancer and amyotrophic lateral sclerosis.
- To identify data that can be used as a real-world synthetic control group. Instead of collecting data from patients in a randomized controlled trial, Real4Reg will analyse the potential of RWD to create a synthetic control group. Control groups are groups of people that do not receive the new intervention, which allows making the comparison between the new treatment and former medicines. With this approach, it won’t be necessary to find a substantial number of persons receiving a placebo, or standard treatment, every time a new RCT is started. This is especially important for rare diseases such as amyotrophic lateral sclerosis or for diseases with several different subtypes, such as breast cancer which implies that the results can be different between different groups of patients.
- Safety of medicine: Real4reg will use data to find out more about adverse reactions, assuring that the medicines available are safe for all groups of people using the medicine. The use of a class of antibiotics (fluoroquinolones) will be the case study in this analysis.
- To know more about new uses for the available medicines. Real4Reg will analyse the case of a class of medicines for diabetes (SGLT2 inhibitors); in recent years, it was found that these medicines could also be used in the treatment of heart failure.