FlowCytometry technology allows detailed analysis of blood samples using a variety of markers that are being used to identify specific disease patterns. Continuous innovation of the technology results in large datasets that are difficult to interpret by humans. Researchers and clinicians from UMC Utrecht and Radboud University have addressed this problem by developing an algorithm that uses raw data from a flow cytometry machine and analyses each cell which differs compared to the patient’s prior analysis. A case study performed by the researchers shows that the algorithm is able to detect MRD more precisely (processing 8M cells in one go) and much faster (2 minutes versus >15 minutes expert analysis). Moreover, the results are presented to the technician in a simplified 2D image, showing all the cell populations. Interpretation can thus be done by less experienced people, in less time and more accurate. More importantly, the increased precision means that the number of false negatives can be reduced.
Ton van den Hoven is one of the founders and CEO of FlowView Diagnostics bv and is responsible for the overall development of the company.
The source code of the algorithm is finished and already tested in patient samples. The Graphical User Interface is in the process of being developed. The clinical validation of this decision support algorithm will follow. Seed funding has been raised for the first phase of development of the solution and the organisation
Algorithm for flow cytometry. Software as a Medical Device, Artifical Intelligence, Decision support systems. Pre-disease detection
TVH: Founder and CEO