Solvathons: New Approaches to Diagnosing Rare Diseases
Research |
They report on the successful model in the article “The Solve-RD Solvathons as a pan-European interdisciplinary collaboration to diagnose patients with rare disease” in Nature Genetics. Solvathons are structured, interdisciplinary workshops developed within the EU-funded “Solve-RD” project (Solving the Unsolved Rare Diseases) to improve the diagnosis of rare diseases. Inspired by hackathons, they bring together clinical experts and bioinformatics researchers to collaboratively investigate real cases using advanced technologies.
Where Diagnostics Meets Data Science
The goal is to resolve unclear genetic findings through collaborative analysis while promoting knowledge exchange. Between 2023 and 2024, four Solvathons were held, each focusing on data modalities complementary to the classical short-read genome sequencing routinely used by genetic diagnostic labs.
These innovative data types, which include long-read sequencing, optical mapping, and ribonucleic acid (RNA) sequencing, among others, fall under the umbrella of “omics,” a collective term for scientific disciplines that analyze biological molecules on a large scale. In medicine, especially in the context of rare diseases, omics methods help identify disease mechanisms, discover new biomarkers, and develop personalized therapies. However, their analyses require expertise beyond that found in routine diagnostic labs. This makes solvathons necessary.
A European Network for Rare Diseases
From 2018 to 2024, more than 100 partner institutions from 26 countries collaborated in the Solve-RD project to tackle undiagnosed cases using cutting-edge omics technologies and collaborative data analysis. The Technical University of Munich (TUM) played a leading role in the design and implementation of Solvathons through Professor Julien Gagneur and Dr. Vicente A. Yépez from the Chair of Computational Molecular Medicine.
The follow-up project ERDERA (European Rare Disease Research Alliance) will continue and expand the Solvathon format, aiming to establish it as a permanent part of Europe’s diagnostic infrastructure.
"These Solvathons weren’t just meetings – they were real-time, problem-solving missions,” said Dr. Vicente A. Yépez, first author from the Technical University of Munich. "They allowed for hands-on case resolution and deep collaboration between clinical and analytical experts.”
"Over the last years, we have developed a whole suite of algorithms to increase rare diagnostic rates using omics data. It was fantastic to see it deployed at that scale and to pinpoint the disease causes for dozens of patients together with colleagues across Europe," added Prof. Julien Gagneur.
A Model for the Future
Each Solvathon combined real patient cases with sophisticated data analysis and interpretation. In total, over 1,000 families were investigated, with results leading to 28 direct diagnoses during the events and at least 80 more afterwards.
Beyond the diagnoses, the workshops provided valuable training opportunities. RNA sequencing and long-read genome sequencing played a key role in uncovering previously undetected genetic causes. Researchers also developed new analytical and visualization methods that are now being used across Europe.
The Solvathons described in the article illustrate how interdisciplinary collaboration, modern data analysis, and clinical expertise can work hand in hand. The publication also offers a practical framework for implementing similar diagnostic efforts globally, which is an essential contribution to the evolving landscape of personalized medicine.