Imagine trying to find a specific typo in a massive library of books to figure out why a patient is sick. Right now, doctors do this manually, which is slow and often confusing. This project builds a smart digital assistant that scans these genetic 'books' automatically to suggest the best medicine for each person. It also includes an app so patients can actually understand what's happening with their own health.
Interpreting cancer genomic data is currently a slow, non-systematic process that relies on scattered databases. This creates a bottleneck that prevents the broad use of Next Generation Sequencing in cancer treatment.
The CGI-Platform and CGI-Pipeline for systematic mutation interpretation, a biomarkers database, and the eduCGI patient app.
If you are a software provider dealing with the slow manual review of genetic data — this project developed the CGI-Platform and CGI-Pipeline that systematizes mutation interpretation. This allows for faster, data-driven clinical decisions and increases the share of interpretable variants from 9-12% to at least 50%.
If you are a clinic dealing with a lack of in-house genomic experts — this project developed a one-stop shop tool and virtual molecular tumor boards. This enables the democratization of genomic data interpretation regardless of the clinic's size or resources.
If you are a drug developer dealing with identifying which patients respond to targeted therapies — this project developed a biomarkers database including new drug treatments for solid tumors and hematological malignancies. This provides a structured, interoperable way to map mutations to drug responses.
Based on available project data, there is no specific pricing or cost model mentioned; the project is funded by a EUR 9,584,298 EU contribution.
Yes, the project plan includes a replication phase targeting 30 hospitals across the EU after the initial validation phase.
Based on available project data, specific licensing terms are not provided, though the project emphasizes data sharing and interoperability via the OSIRIS data model.
The tool maps data to the OSIRIS data model to ensure standardization and interoperability with EU infrastructures.
The project period runs from 2022-11-01 to 2027-10-31, moving from setup to validation and finally replication.
The consortium is heavily weighted toward research and clinical application, consisting of 19 partners across 6 countries. With 10 research organizations and 3 universities, the technical depth is high, but the industrial ratio is low at 5% (only 1 industry partner). This suggests the project is currently in a clinical validation stage rather than a commercial product launch stage.
Contact Fundacio Institut de Recerca Biomedica (IRB Barcelona)
Contact us to explore licensing opportunities for the CGI-Pipeline or to join the replication phase.
