Janne Huhtala (Co-Founder and CEO, MYndspan)
Janne Huhtala is the co-founder and CEO of MYndspan, a brain wellness and analytics company on a mission to revolutionize how people understand and care for their brain health by making brain scanning technology more accessible.
Can you explain your job to a five-year-old?
I'm always explaining this to my four-year-old. He always wonders what daddy is doing. I'm helping people to understand how their brain works.
What excites you most about your job?
I've been working with the brain the last 15 years. My background is in economics. So, basically I didn't learn anything in university, but just to think. And once I got into the brain, I realized how little we know about that.
No matter whether you're talking about a neurosurgeon in Germany or a researcher in the US or somebody doing something in China or Australia, we have really only a glimpse into what we understand about the brain, how it's actually working.
So that's the thing we've figured out. With my co-founder, with our previous jobs, we were touching the technology, which basically gives us a really accurate view of the brain, but it's not really commercialized properly to help people. It's targeting really small-segment MEG technology.
But nobody has really automated the analysis and gone on to help people. So we decided to go B2C, which was basically crazy and, tried to say to the real world that, yeah, we can help you to understand the brain. So we've had a lot of pushbacks, saying ‘You can’t do that,’ ‘It's not easy,’ so on.
It wasn't easy, and it isn't easy, but it gives us an understanding. We just yesterday had a discussion with our team, and they figured out some new stuff from the brain which is not published. Nobody knew about it. It's one way to analyze the brain when you get older and whether you actually have some degenerative disease—and really early on.
So that's the thing: figuring out how the brain works, helping people to understand how their own brain works.
Which trend will change the future of medicine?
AI. I mean, it's trendy to say that, but at the end of the day, if you think about it, we are dealing with a lot of signals from the brain. We have millisecond accuracy with a millimeter accuracy. So temporal and spatial accuracy is there. The amount of data we take out from 10 minutes of just reading the resting state is unbelievable.
I was just told by a researcher that they can identify a person based on three seconds of their brain resting state analysis. So think about the data we are collecting each time we are talking with the subject. And we are also taking their cognitive testing, metadata about their lifestyle, and everything, and getting consent from them also to utilize it. And once we do that, AI will, and has helped already, to really figure out new stuff, which nobody has thought about because our concept of the brain is like alpha, beta, gamma, all these different frequency bands and how they operate. And then we have this location map where things are in the brain. But if you try to connect all the dots, you really have a huge amount of data. And if you try to do it, let's say five, ten years ago, you’d try to preset your rules. You’d look for certain functions, visual networks. You’d try to figure out how it works.
But today, it's almost like we drop it in the bucket and see what comes out. We develop, for example, kind of an identifier of your brain health. And the analysis is that it calculates your meaningful metrics based on your own data. So if we do it for you, it's a different set of metrics than for me.
So at the same time, we can see how your trend is evolving, but it's based on your data rather than general data of the understanding of the brain. So you can't do that really without this modern AI or ML approach, more or less, and figuring out how you do it without giving it too many boundaries.
So that's brain analysis, but then if you step back, think about the whole healthcare and mental health industry mental health, it's scary. We have a huge amount of mental health issues at the moment within the population, and no way our healthcare systems are built to deal with that.
We don't have enough doctors. We don't have enough therapy. We don't have any tools to actually deal with the population-level issues which are coming. So in healthcare, the AI/ML approach will be good and bad. It will destroy people's minds because of all the separation of issues and everything. But at the same time, let's try to harness it for good and understand how we are going to help people.
Looking back, which trends have you missed or underestimated?
The slowness of adaptation. I think AI adaptation is the first that has been faster than expected. It's evolving faster than we actually think.
We always sort of don't really see how slow the change in the system will be. Because there’s people involved. There are doctors, payers, and providers involved. And they all have to make a decision to adopt something new for the benefit of the patient.
And if we turn this around, put the patient or subject in the middle, what is best for them? Is it to wait five years for some clinical consensus or is it something which is proven in one year to actually start utilizing that in clinical care rather than negotiating reimbursement codes and reimbursement coverage and clinical adaptation, KOL teaching, etcetera? So that's part of the reason why we are in the B2C market directly.
My co-founder sent one email to her network, and we got 100 people lining up. People are interested in their brain data because nobody else can give that to them. You can go and have structural imaging of your brain done, but you don't know actually how it's working. So when you turn it around and put the consumer in the middle and start thinking about how we go forward, the change is actually faster.
So now the healthcare system is behind. So, if you ask me what I thought was different, it's the speed. What I would do differently is start earlier with the consumer.
Which MedTech initiative or startup deserves more attention?
I think one of my ex-colleagues said to me that the rising tide lifts all boats. So it's almost like everybody working together is way better off than you're trying to do it on your own. So it is interesting talking with a lot of companies, talking about what they are.
Because I have a nine-month-old daughter. There is a Belgium company called Gabi. They are working on baby monitoring tools which basically help parents and doctors to follow whether the baby's breathing properly, how they are doing.
And it's more for medical use because, if you have a breathing issue with the infant—for instance, our second one was in the NICU, and I was struggling the first few days. She's fine now, but there are a lot of babies who actually struggle with breathing longer. I like the way that company is handling that. They are in the middle—like not purely consumer and not purely medical device. So I think that's a great company.
Where would you put a million dollars?
I don't have a specific startup in mind, but I would put it in somebody who is putting the consumer in the middle and working with AI to solve a provider issue.
Let’s think about the millions of people who have limited access to healthcare, and partly because of societal issues but partly because of provider and expense issues. So all this hype with AI and ML, if we think about it, it's based on our universe.
But we can turn it around and say: how can we treat these common things which people are devastated by as cheaply as possible and fast as possible? How can we enhance AI to do that? How we can use automatic sequencing to have better drugs?
So I would support somebody on that kind of approach. That's kind of what led us to actually solve the brain issue as far as we can. We don't have resources like billions to do this, but we can sort of chip in small pieces and go forward, and hopefully, we can get people thinking and this will sort of bloom.
What's the best advice you've ever received?
I have had a few really good chairmen. One of them, his advice to me when we were building, was to remember that good companies get bought, bad companies get sold.
So what he meant with that was don't try to go with the VC flow. Don't try to go with somebody pushing a trend so that you just build your strategy and your solution to fit somebody's universe. Build it so that it is actually a long-lasting business. And if you need to sell it because you have VCs on board, you get a way better price.
So, yeah, that was really good advice. Build a company that will last, rather than try to build it for somebody to buy.