A French machine learning company is seeking partnerships with institutions holding large electronic health record databases in autoimmunity

Short summary A French deeptech company develops precision medicine in the field of autoimmunity via a cutting-edge machine learning technology. They have leveraged millions of patients' electronic health records (EHR) to capture the complexity of real-world disease and define personalized disease profiles. Their predictive tools use such information to determine each patient's response to treatment and identify associated biomarkers. Cooperation partnerships are sought with institutions with EHR databases.

Full description Autoimmune diseases affect approximately 5% of the world's population, with over 80 distinct conditions. While the number of patients with these chronic and incurable diseases is increasing exponentially, current treatment options remain suboptimal and rely on a costly, ineffective and often harmful "one size fits all" approach. The French company believes that the key to improving the treatment of autoimmune diseases lies in understanding the unique complexities of each patient's condition. They have successfully developed predictive tools for alternative tumour necrosis factor inhibitors (TNFi) and methotrexate response in patients with rheumatoid arthritis, and the results have been presented at international conferences and in peer-reviewed journals. They are now embarking on a new larger scientific project that aims to replicate these successes in a wide range of autoimmune diseases. To do this, they need access to large databases of electronic health records (>500,000 patients). Their main goal is to better understand the response to treatment in autoimmunity and to publish the scientific results in leading medical/scientific conferences and journals. Long-term research cooperation agreements are sought with institutions that have a large electronic health records (EHR) database.

Technical Specification or Expertise Sought The French company is looking for institutions holding large electronic health records (EHR) database with: - more than 500k patients - (un)structured data - type of data collected: EHR, clinical notes (free text), biobank, images. No claims.
Contact / source: NEXT EEN Widgets (europa.eu)