- Despite advances in omics technologies, 30-80% of individuals with rare diseases still lack a molecular genetic diagnosis due to difficulties integrating diverse data types and specialised expertise dispersed across multiple centres.

 
- To address these challenges, the EU-funded Solve-RD project launched “Solvathons”, interdisciplinary workshops that rapidly advance rare disease diagnosis through the collaborative analysis of complex omics data.
 
- The Centro Nacional de Análisis Genómico (CNAG) played a key role by organising, hosting, and executing the pan-European Solvathons. These efforts have contributed to over 100 new diagnoses for families affected by rare diseases, as published today in Nature Genetics.
 
 
Rare diseases affect around 30 million people in Europe, yet between 30-80% of affected families still lack a confirmed genetic diagnosis. Despite advances in multi-omics technologies, diagnosing these conditions remains challenging. Integrating diverse omics data, each with its own interpretation and visualisation tools, is challenging, as specialised expertise for each data type is dispersed across multiple centres. Bridging these gaps is essential for timely, accurate diagnoses. Today, a new Perspective article published in Nature Genetics, as part of the European Solve-RD Project, showcases a pioneering solution: Solvathons. These innovative workshops bring together clinical experts, bioinformaticians, and geneticists to collaboratively analyse complex omics data. Thanks to this interdisciplinary model, more than 100 previously unsolved rare disease cases have been successfully diagnosed. The Centro Nacional de Análisis Genómico (CNAG) played a central role, co-leading the organization, and execution of the Solvathons, further strengthening its position as a hub for integrated diagnostics and expert training.
 
The primary focus of a Solvathon is to efficiently resolve rare disease cases through collaborative multidisciplinary analysis, integration, and interpretation, of patient data and omics results while enhancing collective learning. Inspired by hackathons but specifically designed for clinical genomics, these three-day hybrid workshops bring together clinicians and data scientists from across Europe to collaboratively interpret omics data generated by cutting-edge technologies such as RNA sequencing, short- and long-read genome sequencing, optical genome mapping, and DNA methylation profiling. Each workshop provides hands-on experience, with pre-analysed datasets securely shared in advance. In each session, between 50 and 70 researchers collaborate through data analysis, training, and live discussions of results, fostering mutual learning, assessment of variant pathogenicity, and the discovery of novel phenotype–genotype correlations.
 
Over 18 months, researchers implemented four Solvathons to tackle complex rare disease cases with pre-generated whole-genome and multi-omics datasets. CNAG, as lead member of the Solve-RD Data Analysis Task Force (DATF), contributed to the technical design and integration of genomic and transcriptomic data, while also providing training and mentorship to clinical teams in the interpretation of omics data. “Solvathons turned high-throughput data into real-time clinical insight,” says Dr. Anna Esteve-Codina, Functional Genomics Team Leader at CNAG and co-author of the study. “At CNAG, we helped build the infrastructure and pipelines that enabled experts to directly link omics findings to patient phenotypes. The collaborative dynamic was unique. Sitting side by side with clinicians, solving cases together, and diagnosing patients in real time. Solvathons are not just events, they are engines of diagnostic innovation, accelerating the translation of omics data into real-world clinical benefit.”
 
In total, over 1,000 families were reviewed across all Solvathons, contributing to the diagnosis of 28 cases on-site, with additional cases solved in the months that followed through collaborative follow-up and data sharing, bringing the total number of diagnoses to over 100 previously unsolved rare disease cases. For instance, researchers identified repeat expansions in the NOP56 gene using RNA-seq, successfully resolving two hereditary ataxia cases on-site that had remained unsolved for years. Dr. Steven Laurie, senior genomics data analyst at CNAG and co-author of the study, highlights: "Thanks to Solvathons, complex genome sequencing outputs, especially structural variants, became interpretable in a clinical context. The in-person collaboration with clinicians was key to reaching rapid consensus on candidate variants, something that rarely happens with traditional data exchange pipelines."
 
The samples analysed during Solvathons came from six participating European Reference Networks (ERNs) and represented unsolved cases within disease-specific cohorts. Looking ahead, the Solvathon model, developed under the EU Horizon 2020 Solve-RD project, is now expanding through the European Rare Disease Research Alliance (ERDERA), which will scale and extend the concept across more disease areas and regions, strengthening integration with national healthcare systems and continuing to bridge research and diagnostics for the benefit of patients across Europe.
 
 
REFERENCE ARTICLE
 
Yépez, Vicente A., et al. ‘The Solve-RD Solvathons as a Pan-European Interdisciplinary Collaboration to Diagnose Patients with Rare Disease’. Nature Genetics, Sep. 2025, pp. 1–10. www.nature.com, https://doi.org/10.1038/s41588-025-02290-3.