Scientific collaboration thrives when multiple perspectives converge towards a common goal. This was the atmosphere that marked the second consortium meeting of DREAMS, a Horizon Europe project committed to reshaping how therapies for rare neuromuscular disorders are discovered and developed. Still in an early stage, the project brought its partners together in Paris to take stock of the work accomplished so far, refine strategic priorities and strengthen coordination across the consortium.
DREAMS — Drug Repurposing with Artificial Intelligence for Muscular Disorders — brings together nine organisations from six European countries . The current consortium includes:
CECS/I-Stem (coordinator), INSERM, AFM-Téléthon, University College London (UCL), Kantify, Assistance Publique–Hôpitaux de Paris (AP-HP), Universidade de Coimbra (UC), Technion – Israel Institute of Technology, and Zabala Innovation.
This group represents a multidisciplinary ecosystem of stem-cell scientists, clinicians, computational modellers, regulatory experts and innovation specialists.
The project focuses on five neuromuscular disorders (NMDs) with known genetic origins: Centronuclear Myopathy (CNM), Duchenne Muscular Dystrophy (DMD), Emery–Dreifuss Muscular Dystrophy type 2 (EDMD2), Pompe disease and Danon disease. These disorders share pathophysiological features such as autophagy dysfunction and desmin disorganisation , and many currently lack effective therapeutic options. DREAMS aims to accelerate progress by combining three complementary pillars:
- iPSC-derived muscular cell models and specialised assays
- AI-powered drug discovery and repurposing
- Adaptive clinical trial design suitable for small patient populations
These pillars reflect the integrated methodology described in the detailed project documentation .
Consolidating vision and ensuring alignment
The consortium meeting offered an important opportunity to reaffirm the project’s mission: to establish a reusable drug discovery platform leveraging stem-cell data and AI, capable of identifying shared therapeutic targets across several rare neuromuscular disorders. Rather than presenting major scientific breakthroughs at this stage, partners focused on ensuring that the project’s early activities are progressing in harmony.
Each work package leader presented the status of their tasks, highlighting interdependencies and discussing how to reinforce cross-team communication. The discussions emphasised the need for consistency in data generation and processing, as well as the importance of shared timelines so that future stages — particularly AI modelling and preliminary pharmacological screening — can develop smoothly.
Given the diversity of expertise represented in the consortium, the meeting served as an essential moment to confirm that collaboration mechanisms are functioning effectively. Partners revisited their roles, clarified expectations and identified areas where integration between biological and computational workstreams could be further strengthened.
Building the scientific and methodological foundation
As DREAMS is in its foundational phase, much of the current work focuses on the infrastructure necessary for later scientific advances. Several teams are actively engaged in developing iPSC-derived skeletal muscle models and validated assays that can reliably capture disease-relevant features . Establishing robust and comparable experimental procedures is a prerequisite for generating reproducible datasets that will later feed into the AI models.
In parallel, preparations are underway for the project’s AI-driven drug discovery component. According to the official project brochure, DREAMS intends to use advanced machine-learning methodologies to accelerate target and molecule identification, reduce costs and mitigate risks linked to off-target effects and toxicity . The consortium discussions centred on ensuring that data produced across laboratories will be compatible with the computational frameworks to be developed by the AI teams.
The meeting also touched on the early planning for the project’s adaptive clinical design strategy. Rare diseases often make traditional clinical trials unfeasible due to small, heterogeneous patient populations. DREAMS seeks to design a methodology that can respond to these constraints, with the involvement of clinicians, regulatory experts and patient communities from the outset .
Keeping the societal dimension at the centre
Although the meeting focused on coordination and planning, partners repeatedly acknowledged the human impact associated with the disorders DREAMS targets. Neuromuscular disorders can severely affect mobility, independence and daily life; many begin in childhood and place a considerable emotional burden on families. These realities underline the importance of ensuring that the project’s technological and scientific developments translate into meaningful societal outcomes.
The meeting reflected this shared commitment by reinforcing the need for transparent communication, ongoing engagement with patient representatives and careful attention to ethical and regulatory considerations. As outlined in the project materials, DREAMS aims not only to advance scientific knowledge but also to reduce the socio-economic burden associated with rare diseases by contributing to more efficient and broadly applicable therapeutic approaches .
Looking ahead as a united consortium
The second consortium meeting concluded with a clear agenda for the coming months. Partners agreed on strengthening coordination in laboratory workflows, deepening collaboration between biological and computational teams, and continuing to structure the early stages of the adaptive clinical methodology. Ensuring high-quality communication within the consortium was identified as a recurring priority across all work packages.
As DREAMS progresses, the project will continue to draw on the diverse strengths of its partners. The meeting demonstrated strong cohesion, shared purpose and determination to build a framework capable of supporting future innovation. Although scientific breakthroughs will come later, the consortium’s collaborative work at this stage will be essential in enabling future achievements.
