Summary
We will develop and commercialize an innovative device for diagnosis and monitoring of cancer in liquid biopsies based on a label-free interferometric phase microscopy (IPM) unit, coupled with dedicated real-time artificial intelligence (AI) for cell classification. This device will materialize an innovative approach for the much-anticipated imaging flow cytometry, dramatically decreasing its costs, and improving patient care by accurate monitoring of cancer in the clinical lab from a simple lab test (liquid biopsy). The success of the project is dependent on four high-risk/high-gain aspects: (a) Building the first clinical IPM device. (b) Designing and manufacturing a disposable microfluidic device for imaging flow cytometry. (c) Obtaining high-enough acquisition and processing throughput in imaging flow cytometry of urine samples. (d) Training a deep natural network to detect cancer cells based on the information-deep label-free IPM images of cancer cells during flow. The proposed PoC project stems from my on-going ERC StG project that focuses on the application of IPM for grading the metastatic potential of cancer cells, as a basic-science research tool.
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| Web resources: | https://cordis.europa.eu/project/id/101100664 |
| Start date: | 01-01-2023 |
| End date: | 30-06-2024 |
| Total budget - Public funding: | - 150 000,00 Euro |
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Original description
We will develop and commercialize an innovative device for diagnosis and monitoring of cancer in liquid biopsies based on a label-free interferometric phase microscopy (IPM) unit, coupled with dedicated real-time artificial intelligence (AI) for cell classification. This device will materialize an innovative approach for the much-anticipated imaging flow cytometry, dramatically decreasing its costs, and improving patient care by accurate monitoring of cancer in the clinical lab from a simple lab test (liquid biopsy). The success of the project is dependent on four high-risk/high-gain aspects: (a) Building the first clinical IPM device. (b) Designing and manufacturing a disposable microfluidic device for imaging flow cytometry. (c) Obtaining high-enough acquisition and processing throughput in imaging flow cytometry of urine samples. (d) Training a deep natural network to detect cancer cells based on the information-deep label-free IPM images of cancer cells during flow. The proposed PoC project stems from my on-going ERC StG project that focuses on the application of IPM for grading the metastatic potential of cancer cells, as a basic-science research tool.Status
SIGNEDCall topic
ERC-2022-POC2Update Date
09-02-2023
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