Rare diseases are increasingly recognised as a priority in global health and in European research programmes. Each year, World Health Day is marked on 7 April, offering a moment to reflect on how health challenges are addressed at different levels. Although each condition affects a small number of people, together they represent a significant unmet medical need.
World Health Day offers an opportunity to reflect not only on healthcare systems, but also on how research is organised to better understand these diseases.
Rare disease research in Europe
Over the past years, Europe has developed a strong ecosystem to support rare disease research. This includes collaborative projects, dedicated infrastructures, and networks such as the European Reference Networks.
These initiatives aim to improve knowledge sharing, strengthen collaboration, and support long-term research efforts across countries.
At the same time, rare disease research still faces important challenges. Data is often limited, patient populations are small, and results are not always easy to compare across studies.
Why data integration matters in rare diseases
In rare neuromuscular diseases, different conditions can share underlying biological mechanisms. Examples include dysfunctions in autophagy or alterations in protein organisation.
Identifying these shared mechanisms is essential for advancing research. It allows scientists to:
- Better understand disease biology
- Identify common pathways
- Explore new research hypotheses across conditions
However, this requires more than data alone. It depends on the ability to integrate different types of information, from cellular models to omics datasets and clinical insights.
Source: World Health Organization
The role of AI in rare disease research
Artificial intelligence is becoming an important tool in biomedical research, especially when dealing with complex and heterogeneous data.
In the context of rare diseases, AI can support:
- The analysis of multi-layered datasets
- The identification of patterns across diseases
- The generation of new research hypotheses
Its value depends on the quality of the data and on how well different sources of information are connected.
DREAMS and its contribution
The DREAMS project is part of this evolving research landscape.
It combines iPSC-derived skeletal muscle models with multi-omics and phenotypic data. These datasets are analysed using AI-based approaches to explore shared biological pathways across rare neuromuscular diseases.
The objective is to better understand connections between diseases and support future research directions.
DREAMS does not deliver validated treatments or clinical tools within its duration. Its contribution is focused on generating structured knowledge, improving data integration, and developing methodologies that can be reused in future studies.
Collaboration, data integration and knowledge connection
Advancing rare disease research requires more than individual discoveries. It depends on collaboration, data integration, and the ability to connect knowledge across disciplines and diseases.
European initiatives are increasingly moving in this direction. Projects like DREAMS contribute by strengthening how research is conducted and how knowledge is shared.
On World Health Day, this perspective is essential. Improving global health also means improving how research is organised to address complex conditions such as rare diseases.
