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Cerebriu will use machine learning to rule out blood clots in the brain and save time and money in a pressured healthcare system

This article has been prepared in collaboration with TechBBQ.

Every minute is a matter of life and death when the brain bleeds or has a blood clot. But it takes a brain scan to find the damage inside the skull, and whether the scan takes five minutes or half an hour is crucial to further treatment.

That’s one reason why a young company called Cerebriu has developed an artificial intelligence that can help healthcare professionals decide what to do with a patient during the scan.

“When a patient comes in with a suspected blood clot or bleeding in the brain, after the first few sequences our technology can inform radiologists and doctors that we have found a clot and that it is time to stop the scan and move the patient to an emergency department immediately. We save 10-15 minutes, maybe even half an hour, and the patient needs that to get back to full cognitive function afterwards,” says Akshay Pai, co-founder and CTO of Cerebriu.

The company, founded in 2018, started with brain scans. Here, they are now so far into the evidence phase that they are in dialogue with a number of hospitals testing the solution, as well as the major scanner manufacturers, who can see the benefits of integrating the technology directly into their scanners.

Cerebriu is working not only with hospitals and major manufacturers, but also with other start-ups, says Akshay Pai: “We are trying to hit many areas at once, but we can’t do it all ourselves. Sometimes, for hospitals to see the real value, they need a number of improvements at the same time, and other startups come in to offer similar improvements in other areas that complement what we’re doing.”

Supporting the missing hands

Every year, the use of radiology scans increases by up to 15 percent, explains Akshay Pai. Analysing the images from the scans requires radiologists, but fewer and fewer are choosing to go that route in medical school, making that specialised workforce a scarce commodity in the healthcare sector.

“So the only way out is for existing radiologists to work extra hours, or we make the machines smarter and more efficient so we only need radiologists when it’s extra important,” says Akshay Pai.

Many of the scans being done are normal, routine examinations. These are very low-risk tests where patients come in for extra confirmation that everything is as it should be. Here too, Cerebriu can help healthcare. Because if the technology can determine that everything looks normal after the first five minutes in the scanner without involving a radiologist in the analysis, the rest of the programme can be interrupted, saving healthcare resources from scanning a healthy citizen any more than is absolutely necessary.

“We are different in this world of medical devices and the pharma industry in that, as a starting point, we want to change the workflows that are there. We don’t want to replace radiologists. We are here to assist and to improve processes. We try to support faster decisions in the first few minutes, but the overall mission is to make MR scans more efficient and ensure that the right information is passed on so that action can be taken quickly and correctly,” says Akshay Pai.

Facts: “Bridging the Gap”

  • The project “Bridging the Gap – A more connected life science ecosystem” aims to network and connect across the life science sector (between biotech, medtech, healthtech and welfaretech and others). At the same time, the project aims to connect the life science sector with the rest of the entrepreneurial community in Denmark and the Nordic region.
  • TechBBQ acts as a facilitator and catalyst in establishing networks where everyone is closer to each other and can benefit from each other’s knowledge.
  • The project is funded by the Novo Nordisk Foundation.
  • Read more and see the ecosystem mapping here:

On its

way to hospitals and scanners

Cerebriu is now conducting studies with a number of hospitals, including Herlev-Gentofte Hospital, Rigshospitalet and a chain of clinics in the US, Israel and India, to prove that artificial intelligence can conclude various brain conditions with very high confidence from very few scan images.

“We want to show that we can rule out anything critical. If a patient has something that is not critical but looks abnormal, you can always call the patient back and do a second scan to be sure. We can rule out anything critical with the 3-4 images we require. And once we have the evidence, we can convince doctors, radiologists and management in hospitals and clinics to change practices,” says Akshay Pai.

At the same time, the startup is working with major manufacturers to integrate the solution into their scanners.

“Because we come from the outside, see things from a different perspective and work in a completely different way, we are more able to challenge them and see potential for optimisation. I can’t reveal the name, but we’ve already signed a development agreement and potential sales agreement with a major manufacturer that has about 40 percent of the market share. We have good opportunities, so now we hope to deliver now and come out with an extremely robust product that can be used worldwide,” says Akshay Pai.

Q&A: Keld Laursen, Professor and Head of the Department of Strategy and Innovation at CBS

– Why is it important that companies in the life science industry become better at working together across (of biotech, medtech, healthtech etc.)?

“There is a reason why there is not just one company in this field but 1000 different ones, each focusing on something specific. This provides specialisation, which also allows the ecosystem to gain an advantage by coordinating activities with each other. You can bundle products across – there can be a link between medical treatment and equipment for patients, for example. And if you can offer a more complete solution together, so that those who will buy the solution can reduce their coordination costs, you are stronger.

– Why should life science start-ups mix more with tech start-ups from other industries?

“Context matters a lot, but you have completely different sales channels and product cycles, which in medicine are very, very long compared to others. So I’m not convinced that the tech industry is the one to look at the most in general. Of course, you can always learn from others and exchange experiences on a more general basis. But if you’re talking about devoting significant resources to collaboration, I think time is better spent working with players in related industries.

That said, one can imagine some complementary products across the board. With medical devices, there may well be some bundling with different products in the tech industry, which might then be integrated.”

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