Data driven cancer genome interpretation for personalised cancer treatment
CGI-Clinics aims at improving personalised medicine in oncology by optimizing genomic data interpretation (after sequencing and before advising on compatible targeted therapies). Interpretation is a bottleneck for the full deploym...
CGI-Clinics aims at improving personalised medicine in oncology by optimizing genomic data interpretation (after sequencing and before advising on compatible targeted therapies). Interpretation is a bottleneck for the full deployment and broad accessibility of Next Generation Sequencing (NGS) in cancer management. The project tackles the 3 main hurdles in the interpretation of cancer mutations: it is not systematic, it deals with a majority of variants of unknown significance and it fails to empower patients.
The interpretation of tumor genomic data relies on the work of experts reviewing scattered databases and resources, in a time-consuming process that may lead to suboptimal clinical decisions. CGI-clinics will systematize the interpretation process by integrating relevant public and private databases hospitals in a one-stop shop tool, with the possibility to organize virtual molecular tumor boards co-facilitated by reference hospitals. Project will have three phases: a setup (assess needs), validation (pilot with the 9 clinical partners) and replication (30 hospitals across EU). It will enable democratization of genomic data interpretation (independent of their size, resources and profiling technology) and provide health economics validation.
Relying on a systematic automatic learning platform, GCI-Clinics will increase the share of interpretable variants in tumors (from the current 9-12% to at least 50%), and features that constitute biomarkers of drug response. The interpretation process is complex for most cancer patients, alienating them from knowledge of their illness. CGI-Clinics will build eduCGI, an app to help them understand the information gained through interpretation of their tumors, facilitating informed discussions with clinicians and sharing their data for research. Ultimately, the project is built to inform policy-makers on cancer management and empower patients.ver más
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