Summary
After successful development of METAglut1, an IVD Medical Device for diagnosis of the Glut1 Deficiency Syndrome ( available for clinical use), we are currently focused on developing a new breakthrough solution: METAflow. Flow cytometry (FC) is a powerful tool widely use in research. However, the high cost and complexity of interpretation of FC data hampers its full clinical exploitation. Main pain-points of clinical FC data analysis, include need for manual analysis, which is accompanied by complexity with increasing number of dimensions, lack of robustness and limited scale-up. The lack of automated analytical process stems from dearth of robust algorithms, limited regulatory compliance and need for considerable coding skills. With METAflow we bring to the market the first digital, clinical grade FC platform, which offers comprehensive data analysis, robustness, and usability, addressing the “lost in translational research” issue of flow cytometry in the clinics.
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| Web resources: | https://cordis.europa.eu/project/id/190166506 |
| Start date: | 01-01-2023 |
| End date: | 30-06-2024 |
| Total budget - Public funding: | 3 570 827,50 Euro - 2 499 579,00 Euro |
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Original description
After successful development of METAglut1, an IVD Medical Device for diagnosis of the Glut1 Deficiency Syndrome ( available for clinical use), we are currently focused on developing a new breakthrough solution: METAflow. Flow cytometry (FC) is a powerful tool widely use in research. However, the high cost and complexity of interpretation of FC data hampers its full clinical exploitation. Main pain-points of clinical FC data analysis, include need for manual analysis, which is accompanied by complexity with increasing number of dimensions, lack of robustness and limited scale-up. The lack of automated analytical process stems from dearth of robust algorithms, limited regulatory compliance and need for considerable coding skills. With METAflow we bring to the market the first digital, clinical grade FC platform, which offers comprehensive data analysis, robustness, and usability, addressing the “lost in translational research” issue of flow cytometry in the clinics.Status
SIGNEDCall topic
HORIZON-EIC-2022-ACCELERATOROPEN-01Update Date
31-07-2023
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