SubsidieMeestersPrecision biomarker based on digital pathology and artificial intelligence to guide fast and cost-effective personalized treatment decision support for colorectal cancer patients
DoMore Dx offers innovative diagnostics software using deep learning on cancer tissue images to personalize chemotherapy decisions, potentially saving 250,000 patients and 4 billion EUR annually.
Projectdetails
Introduction
There is consensus in the oncology community that there is a large need for personalized cancer treatment decisions as patients suffer from large-scale overtreatment. Up to 90% of patients receiving adjuvant chemotherapy have no effect, and many suffer severe side effects.
Solution Overview
DoMore Diagnostics (DoMore Dx) delivers pioneering diagnostics software that enables personalized cancer treatment in a simple and cost-efficient way. We provide deep learning algorithms applied to cancer tissue whole slide images (WSI) in the adjuvant chemotherapy setting.
Innovative Approach
With end-to-end deep learning, we have taken a completely new approach to this challenge. Our test can be run in local labs with digital pathology equipment and does not consume any tissue. DoMore Dx is personalized medicine made simple.
Impact on CRC Patients
In CRC, our test can stratify patients into low, intermediate, or high risk with a hazard ratio >10. This information can be used to take up to 250,000 patients out of chemotherapy and save 4 billion EUR globally every year.
Financiële details & Tijdlijn
Financiële details
| Subsidiebedrag | € 2.499.999 |
| Totale projectbegroting | € 5.326.967 |
Tijdlijn
| Startdatum | 1-6-2024 |
| Einddatum | 31-5-2026 |
| Subsidiejaar | 2024 |
Partners & Locaties
Projectpartners
- DOMORE DIAGNOSTICS ASpenvoerder
Land(en)
Vergelijkbare projecten binnen EIC Accelerator
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Disruptive and high accuracy test for early colorectal cancer detection in blood
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Multi-omic data driven drug discovery and indication prioritisation platform in oncology
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Vergelijkbare projecten uit andere regelingen
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|---|---|---|---|---|
Chemometric histopathology via coherent Raman imaging for precision medicineThe CHARM project aims to revolutionize cancer diagnosis with a novel AI-integrated, label-free tissue analysis system, achieving high accuracy in tumor identification and classification. | EIC Transition | € 2.441.979 | 2022 | Details |
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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 |
Uitbreiding methylatie platformsMLA Dx ontwikkelt een prognostische methode voor vroeg stadium melanomen via LY75 methylatie, ter verbetering van diagnose en behandeling. | Mkb-innovati... | € 20.000 | 2021 | Details |
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Chemometric histopathology via coherent Raman imaging for precision medicine
The CHARM project aims to revolutionize cancer diagnosis with a novel AI-integrated, label-free tissue analysis system, achieving high accuracy in tumor identification and classification.
AI-based medical assistant - Herkennen en classificeren van tumoren m.b.v. kunstmatige intelligentie
Dit project ontwikkelt een geavanceerde beeldherkenningstechnologie voor realtime screening van eiwittypologieën in biopten, om de behandeling van complexe tumoren te verbeteren.
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.
Uitbreiding methylatie platforms
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