Project description
AI-powered software solutions for precision cancer diagnostics
AI-powered cancer classification is a critical aspect of precision oncology. Funded by the European Innovation Council and executed by Qlucore, the QIandQD project is developing visualisation-based analytical solutions for the next-generation sequencing (NGS) market. Its goal is to revolutionise clinical diagnostics with AI-powered software that provide highly accurate diagnoses. The project will initially focus on solutions for acute myeloid leukaemia (AML) and bladder cancer. The aim is to expand gene expression-based diagnostics to all relevant cancer types, with future plans to expand into non-cancer indications such as cardiovascular and neurological diseases, and other data types including proteomics and single-cell RNA-seq.
Objective
Qlucore is developing visualisation-based analytical solutions with an established position in the next-generation sequencing (NGS) market. As pioneers in RNA-data analysis, we aim to revolutionise the field of companion and clinical diagnostics by developing software platforms integrating AI-powered machine-learning classification models for gene expression signatures and gene fusion analysis.
By providing highly accurate and specific diagnoses, our platform represents the future of precision oncology, putting Europe at the forefront of AI-powered cancer classification. A software-based setup speeds up the introduction of new clinical guidelines and companion diagnostic solutions with the ultimate purpose of increasing survival rates and overall health. We aim to cover all cancer types relevant for gene expression-based diagnostics, and then scale up into non-cancer indications (e.g. cardiovascular and neurological diseases, immunological disorders) and other data types (e.g. proteomics and single-cell RNA-seq), further disrupting the precision diagnostics industry.
Currently, we are preparing the solution with a classification model for B-cell progenitor acute lymphoblastic leukaemia (BCP-ALL) for the first IVDR certification (proof of concept). Building on those achievements and leveraging regulatory and data management experience, and progress, in the proposed project we will focus on acute myeloid leukaemia (AML) and bladder cancer (BC). For AML and BC we will develop and CE-certify classification models and companion diagnostics (CDx)-specific classification models.
The successful completion of this project will significantly improve Europe's position in genomics- and AI-based precision diagnostics and as such prompt similar initiatives across Europe. This will allow the EU to compete effectively with market leaders (in particular the US) and offer significant benefits to patients diagnosed with cancer and society as a whole.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencesbiological sciencesgenetics
- natural sciencescomputer and information sciencessoftware
- natural sciencesbiological sciencesbiochemistrybiomoleculesproteinsproteomics
- medical and health sciencesclinical medicineoncologybladder cancer
- medical and health sciencesclinical medicineoncologyleukemia
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Keywords
Programme(s)
- HORIZON.3.1 - The European Innovation Council (EIC) Main Programme
Funding Scheme
HORIZON-EIC-ACC-BF - HORIZON EIC Accelerator Blended FinanceCoordinator
223 70 Lund
Sweden
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.