https://www.epo.org/en/node/jan-van-den-boogaart-and-oliver-hayden

Jan van den Boogaart and Oliver Hayden

Rapid blood test for malaria

Category
Industry
Technical field
Medical technology
Company
Siemens Healthineers
Malaria is one of the ten deadliest diseases of our time and is diagnosed in only 10% of all cases. Changing the paradigm, Dutch haematologist Jan van den Boogaart and Austrian biochemist Oliver Hayden developed the first automated, computer-based blood test for malaria. Combining medicine and information sciences, the test is based on a computer algorithm that detects infections with unprecedented accuracy.

Winners of the European Inventor Award 2017

Prior to the invention, modern medicine had no automated blood test that could accurately detect malaria, the infectious tropical disease that kills one person every 12 seconds. As the key to success, Jan van den Boogaart and Oliver Hayden at Siemens Healthineers pioneered a data-driven approach. Instead of looking for the presence of malaria pathogens in the blood, they used information technology to detect the disease's damaging effects, as indicated by key blood parameters, such as lowered platelet counts.

Van den Boogaart was inspired by talking to a colleague from South Africa in 2008, who had noticed similar changes in the haemograms - or blood profile tests - of several malaria patients. Viewed in isolation, none of these factors were sufficient for a diagnosis - but a combination of 30 parameters revealed a "data fingerprint" that identified malaria with 97% certainty.

With Hayden contributing key statistical analysis, the inventors filed a European patent application in 2011, and the two connected with a Siemens biosensors research group in Vienna to develop a malaria-specific algorithm for the company's blood testing system. Currently, van den Boogaart and Hayden are expanding the "data fingerprint" method to detect other diseases in blood samples, including leukaemia.

Societal benefit

Fast, reliable and automated testing of large patient populations could tilt the scales in the fight against the deadly disease. Around 3.2 billion people are at risk from malaria, which affected over 200 million and killed around 430 000 in 2015 (WHO). According to recent studies, accurate malaria testing could prevent 100 000 deaths and more than 400 million false treatments per year in Africa alone.

The team's test could also improve outcomes for travellers from Western countries returning home infected with malaria. Currently, over 59% of these cases are initially misdiagnosed, and almost eight days elapse before doctors initiate correct treatment, increasing the risk of complications and even death.

Economic benefit

Accurate and rapid testing of large patient populations could help to break the vicious cycle of poverty and malaria that has held large parts of Africa and tropical Asia in its grip for centuries. While the disease has been eradicated from North America and Europe since the mid-1950s, it remains rampant in malaria "hot spots". Today, malaria's economic burden in African countries - where almost 86% of infections occur - is estimated at around EUR 11 billion per year.

Analysts at Grand View Research valued the malaria diagnostics market at EUR 535 million in 2015 and estimate that the overall market size will reach EUR 728 million by 2022, with Africa remaining the dominant market region with a 58% share.

 

How it works

Previous detection methods include a time-intensive microscopic procedure that requires a technician working roughly an hour in the lab or a dip-and-react test for malaria antigens - similar to a pregnancy test - that yields inaccurate results.

The key to the discovery was a statistical method called linear discriminant analysis (LDA). Van den Boogaart and Hayden computed the average levels of certain blood parameters in both malaria-positive and malaria-negative patients with statistics software.

This data formed the basis for defining a set of 30 parameters that indicate a malarial infection - including the density of red blood cells, as well as levels of the blood-colouring agent haemoglobin - and the percentage deviation from healthy levels needed to signal a "positive".

The inventors developed an algorithm to program malaria's "data fingerprint" into the Siemens ADVIA 2120i haematology system. This automated blood analysis device, similar in size to a washing machine, is already widely deployed at clinics (over 3 000 units worldwide). It can create haemograms with 300 to 500 parameters at a rate of 120 blood samples per hour. With near-100% accuracy, the system identifies malaria in a blood sample even if only low levels of pathogens are present.

The inventors

Van den Boogaart studied at H.B.O. Eindhoven, earning a bachelor's degree in microbiology in 1980 and a second bachelor's in clinical chemistry a year later. He began his career at the hospital laboratory of H.B.O. Eindhoven before joining Bayer as a field technician in 1991. His unit in Bayer later became part of Siemens Healthineers.  

A dedicated researcher in the field of haematology and blood test development for over 35 years, van den Boogaart is listed as inventor on three patents filed worldwide. He is currently perfecting the "data fingerprint" method for automated blood tests for sickle cell anaemia and acute promyelocytic leukaemia (APL) as the DX Product Manager at Siemens Healthineers in The Hague.

Having earned his PhD in Biochemistry from the University of Vienna in 1999, Hayden conducted postdoctoral research in nanotechnology at Harvard. He also earned an MBA in Business Administration from the Julius Maximilian University of Würzburg in 2011.

Formerly the Head of In-Vitro Diagnostics & Bioscience Germany at Siemens Healthineers in Erlangen, Hayden is the author of over 80 articles, and is listed as inventor or co-inventor on some 100 patent families. His research has been honoured with the Young Investigator Award of the Austrian Chemical Society (2002), the AMA Innovation Award (2016) and the Siemens NTF Award for Medical Imaging Patents. He has also received the EUREKA Lillehammer Award (2006) and the "Best of Biotech" Award for start-up company Polymimetics (2000). In June 2017 he took up the Heinz Nixdorf Chair of Biomedical Electronics in the Department of Electrical and Computer Engineering at the Technical University of Munich.

Did you know?

 The story of malaria is one of the greatest mysteries of medical science. Its true cause has remained murky ever since 240 BC, when ancient Greek physician Hippocrates attributed the disease to drinking "stagnant waters" from swamps. The name "malaria" itself falsely assumes that malaria is caused by bad air - Italian "mala aria" - from swamps and marshlands.

Nevertheless, the killer behind malaria did actually reside in swamps, as proven by French military doctor Alphonse Laveran while stationed in Algeria in 1880. Laveran identified protozoan parasites of the genus Plasmodium, spread by mosquitoes, as the culprit. The discovery salvaged the French-led construction of the Panama Canal, a dramatic failure due to malaria outbreaks for 20 years, and won Laveran the 1907 Nobel Prize.

Malaria treatments have improved dramatically over the years, including an effective medication against the disease based on ancient Chinese medicine created by Professor Yiqing Zhou , winner of the 2009 European Inventor Award in the category "Non-European countries". But malaria diagnosis often remained a guessing game, at least until Hayden and van den Boogaart's invention unmasked malaria with near-100% accuracy.

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Jan van den Boogaart and Oliver Hayden
The book of life

Blood tells a story, and if you were able to read it, you would know precisely what is happening in the body. Jan van den Boogaart and Oliver Hayden have dedicated their careers to technology that analyses blood. From malaria to cancer and the novel coronavirus, the inventors are developing cutting‑edge tools to enable accurate diagnoses and therefore optimal treatment.

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Talk innovation 

In this episode of Talk innovation, Oliver Hayden shares his expertise on analysing COVID-19 and provides a glimpse of his work at the Technical University of Munich.

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