Advanced algorithm supports specialists in decision-making - FlowView Diagnostics raises €875,000 for further development
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Advanced algorithm supports specialists in decision-making - FlowView Diagnostics raises €875,000 for further development

FlowView Diagnostics from Heerenveen receives an investment of 875,000 euros from a consortium of investors including the NOM and the Steppingstone fund. FlowView Diagnostics is developing a decision support platform that makes it possible to perform high quality blood analyses in a fast manner that allows the medical specialist to make diagnoses quickly and easily.

An example of a situation where a blood analysis can be done is a case of traffic accident victims. The trauma surgeon must decide whether an operation should be performed immediately, or whether the patient's body cannot yet handle such an operation. Knowledge and experience assist the surgeon. FlowView's algorithm provides the supporting information within 15 minutes that allows the surgeon to make the decision to stabilize this patient or perform surgery immediately. This and other applications are being tested in detail in an intensive collaboration with UMC Utrecht and Radboud University in the form of clinical studies.


Ton van den Hoven, CEO, explains, "A blood analysis is not new. It is already possible now and is usually done in the hospital laboratory. The result often takes 24 or more hours, because the amount of information from the analysis makes interpretation complex. In the case of such a traffic victim, that is not of much immediate use to a physician.'' FlowView's software simplifies diagnostics by extracting the right information for the physician from that large amount of data and presenting it simply. This gives the physician a good impression of the response of the patient's immune system, which is an important part of the physician's clinical decision making.

The algorithm, by using data from "healthy" patients and comparing it to the analysis in question, can identify abnormalities. These abnormalities are presented to the treating physician, who is thus enabled to put together the patient's treatment plan more quickly and efficiently. Additional advantage of this automated diagnostics, is that many more links can be made between different analyses. Van den Hoven: ,,Doctors are very good at making diagnoses, but at some point they have to do so based on so much data that it becomes increasingly difficult for doctors. The algorithm solves this problem.''

Recognizing disease

Further development of the platform will focus on recognizing disease states such as Minimal Residual Disease (MRD) where the algorithm can determine with high specificity and sensitivity the amount of abnormal cells and with this inform the treating physician whether there is (an early) recurrence of bone marrow cancer. The algorithm is designed so that the analysis and the appointment with the treating physician can be handled with one visit.

FlowView Diagnostics is building a digital decision support platform equipped for those two purposes. Hardware development plays an important role in the digital platform. As it becomes ever smaller and more mobile, it is possible to start this kind of automatic analysis from the treatment room as well. Faster and simpler analysis of blood offers many more possibilities, which in the future will certainly lead to offering algorithms for other applications and perhaps predictions. "We are now testing and focusing first on supporting doctors in the indication of disease developments and on making different disease indications presentable on one platform" said Ton van den Hoven.

The technology stems from a collaboration between UMC Utrecht and Radboud UMC in Nijmegen. Because the startup is statutorily based in Heerenveen, it makes sense for NOM to be a co-investor. ,,We are always interested in this kind of AI innovation. What FlowView can do will seriously mean something in the medical world,'' says investment manager Ytsen van der Meer. NOM is investing in the startup together with medtech investment fund Stepping Stone, software developer Amatis and three business angels.

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