The first IVDR-approved commercial software solutions for AI-powered RNA-based companion and precision cancer diagnostics of acute myeloid leukaemia and bladder cancer
Qlucore aims to revolutionize precision oncology by developing AI-driven diagnostic software for cancer, enhancing accuracy in gene analysis and improving survival rates across Europe.
Projectdetails
Introduction
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.
Future of Precision Oncology
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.
Expansion Plans
We aim to cover all cancer types relevant for gene expression-based diagnostics, and then scale up into non-cancer indications, including:
- Cardiovascular diseases
- Neurological diseases
- Immunological disorders
Additionally, we plan to explore other data types such as proteomics and single-cell RNA-seq, further disrupting the precision diagnostics industry.
Current Developments
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, we will focus on acute myeloid leukaemia (AML) and bladder cancer (BC).
Project Goals
For AML and BC, we will develop and CE-certify classification models and companion diagnostics (CDx)-specific classification models.
Impact on Europe
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, particularly in the US, and offer significant benefits to patients diagnosed with cancer and society as a whole.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 2.491.650 |
Totale projectbegroting | € 3.559.500 |
Tijdlijn
Startdatum | 1-5-2024 |
Einddatum | 30-4-2027 |
Subsidiejaar | 2024 |
Partners & Locaties
Projectpartners
- QLUCORE ABpenvoerder
Land(en)
Vergelijkbare projecten binnen EIC Accelerator
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Multi-organ toxicity and efficacy test platform for Personalized medicine & Drug developmentCherry Biotech aims to revolutionize drug development and personalized medicine by providing a patented 3D cell culture platform that enhances predictability and reduces reliance on animal testing. | EIC Accelerator | € 2.499.831 | 2024 | Details |
IOO: a novel assay to predict patient response to immune checkpoint inhibitors, optimising patient stratification to these therapies and tripling solid tumour patient outcomes in immuno-oncology.The project aims to enhance cancer immunotherapy efficacy by developing a validated biomarker assay to predict patient responses, potentially doubling survival rates for lethal tumors. | EIC Accelerator | € 2.496.112 | 2024 | Details |
Human-Centric AI platform for heALth and Life sciencesAbzu ApS aims to revolutionize AI in pharma with the QLattice, a user-friendly, explainable platform that enhances R&D efficiency and reduces costs, supported by EIC funding. | EIC Accelerator | € 2.495.099 | 2023 | Details |
Multi-omic data driven drug discovery and indication prioritisation platform in oncology
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IOO: a novel assay to predict patient response to immune checkpoint inhibitors, optimising patient stratification to these therapies and tripling solid tumour patient outcomes in immuno-oncology.
The project aims to enhance cancer immunotherapy efficacy by developing a validated biomarker assay to predict patient responses, potentially doubling survival rates for lethal tumors.
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Abzu ApS aims to revolutionize AI in pharma with the QLattice, a user-friendly, explainable platform that enhances R&D efficiency and reduces costs, supported by EIC funding.
Vergelijkbare projecten uit andere regelingen
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AI-based leukemia detection in routine diagnostic blood smear dataDevelop LeukoScreen, an AI software to enhance the speed and accuracy of acute promyelocytic leukemia diagnosis, improving patient outcomes and optimizing laboratory workflows. | ERC Proof of... | € 150.000 | 2023 | Details |
Foundation models for molecular diagnostics - machine learning with biological ‘common sense’FoundationDX aims to enhance molecular diagnostics by using self-supervised learning on diverse biomolecular data to accurately predict cancer subtypes and treatment outcomes without extensive labeled datasets. | ERC Consolid... | € 2.000.000 | 2024 | Details |
DETACT - Detection of Enzymes and muTAtions for Cancer TreatmentCytura Therapeutics en ENPICOM ontwikkelen een innovatieve diagnostische assay voor vroege kankerdetectie door het meten van enzymactiviteit en mutatiepatronen in bloedcellen. | Mkb-innovati... | € 215.845 | 2019 | Details |
Applying novel single-cell multiomics to elucidate leukaemia cell plasticity in resistance to targeted therapyThis project aims to develop a single-cell multiomics method to understand epigenetic resistance mechanisms in AML, enhancing treatment strategies against drug resistance. | ERC Starting... | € 1.882.440 | 2024 | Details |
Photoacoustic imaging and artificial intelligence-based theranostic approach for cancerPHIRE aims to develop a novel theranostic device for high-resolution imaging and treatment of bladder cancer lesions under 1 mm, improving patient outcomes and reducing tumor relapse. | EIC Transition | € 2.084.871 | 2023 | Details |
AI-based leukemia detection in routine diagnostic blood smear data
Develop LeukoScreen, an AI software to enhance the speed and accuracy of acute promyelocytic leukemia diagnosis, improving patient outcomes and optimizing laboratory workflows.
Foundation models for molecular diagnostics - machine learning with biological ‘common sense’
FoundationDX aims to enhance molecular diagnostics by using self-supervised learning on diverse biomolecular data to accurately predict cancer subtypes and treatment outcomes without extensive labeled datasets.
DETACT - Detection of Enzymes and muTAtions for Cancer Treatment
Cytura Therapeutics en ENPICOM ontwikkelen een innovatieve diagnostische assay voor vroege kankerdetectie door het meten van enzymactiviteit en mutatiepatronen in bloedcellen.
Applying novel single-cell multiomics to elucidate leukaemia cell plasticity in resistance to targeted therapy
This project aims to develop a single-cell multiomics method to understand epigenetic resistance mechanisms in AML, enhancing treatment strategies against drug resistance.
Photoacoustic imaging and artificial intelligence-based theranostic approach for cancer
PHIRE aims to develop a novel theranostic device for high-resolution imaging and treatment of bladder cancer lesions under 1 mm, improving patient outcomes and reducing tumor relapse.