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Professor Oliver Hayden is the winner of the European Inventor Award 2017 in the category Industry. Courtesy of Andreas Heddergott / Technical University of Munich
Diagnosing malaria has been a very time-consuming and error-prone process up to now. Together with his Dutch colleague Jan van den Boogaart, professor Oliver Hayden from the Technical University of Munich (TUM) has now developed an automated rapid blood test that provides an accurate diagnosis in almost 100 percent of cases. The researchers were presented with the European Inventor Award, which honors outstanding inventors from Europe and the rest of the world, for the development of the new method on 15 June.
According to the World Health Organization (WHO), malaria claimed the lives of approximately 430,000 people throughout the world in 2015. A major problem associated with this infectious tropical disease is the difficulty in obtaining a fast and reliable diagnosis. Up to now it was diagnosed mainly by means of the microscopic detection of pathogens in the blood by medical technicians - an inaccurate and time-consuming method. The new rapid test developed by Prof Oliver Hayden, holder of the Heinz Nixdorf Chair for Biomedical Electronics, and Jan van den Boogaart from Siemens Healthineers uses a combination of 30 different blood values that can be determined using an automated process.
The researchers carried out a statistical evaluation of the blood parameters of healthy subjects and malaria patients. Based on this they were able to identify a set of 30 blood values which presented quantifiable deviations from the norm in people suffering from the disease. The two researchers then developed an algorithm that can be programmed into blood analysis devices already used in laboratories and clinics so that they recognize the malaria "data fingerprint." The new method enables the diagnosis of the disease with 97 percent accuracy. Van den Boogaart and Hayden aim to develop the detection method further for use with other diseases in the future.
Source: Technical University of Munich (TUM)