“I want to take you on a little journey of what the brain focus is in the healthcare sector. I would like to give you a little bit of a cross-overview on how these things come together, and also touch upon, obviously, the global perspective here.

As you may know, around the world, about five, six years ago, there was a mushrooming of brain initiatives of a pretty large magnitude. We started this in Europe with the Human Brain Project [which I once led], which is a one-billion-euro initiative by the European Commission together with 19 member states. The goal of that initiative is to drive a marriage between biology and computational power.

What's being created here is sort of a new epistemology of how to describe the brain and also to actually simulate some of the functions of the brain in order to better understand it. And you can derive a whole host of benefits from that, specifically for healthcare.

The US BRAIN Initiative was then shortly afterwards announced by then President Obama. It is currently funded with about 300 million per year and the focus is a little bit complementary to the European version. It goes more into actual imaging, measuring and mapping the human brain.

There's a Chinese brain initiative that's getting off the ground. There's a Japanese one, an Australian one, a Korean one. So around the world, we have what people call the Century of the Brain, and that's where this is all coming from.

It's a little bit of an indicator of how fast we're actually moving that this century of the brain was five years of everybody talking about this. Now, we're basically already talking about the results of some of these technologies. We're talking about AI and a whole list of buzzwords.

In terms of getting this together, I had the opportunity to start an initiative called the International Brain Initiative in Australia last year in Canberra. We set up a Canberra declaration and we are trying to unite those initiatives. I'm trying to really make sure that we map out what's happening around the globe.

Now, why is this so important? Why is brain health so important? About a third of you in this room have some kind of brain disease right now. And that's not meant as an insult, it's just a statistical fact. I'm talking about things from migraine to depression, to all sorts of things that are happening that you may or may not know about even at this point.

Brain health is one of the major challenges of our century.

In Europe, the economic burden or societal burden of health of brain disease is higher than heart disease and cancer combined. So there is a very clear drive from the healthcare perspective to understand the brain better.

The other big challenge we have, of course, is to understand intelligence itself. So, you can have three approaches. What we're doing now, what we're seeing happening now, those two things are coming together and they're converging and driving each other in some sort of positive feedback cycle, which is not without its challenges.

I want to put out four theses that I believe will be drivers in healthcare in the coming years. Number one: we are seeing clearly a patient-centric data universe emerging.

Number two: new disease models. The initiatives like the Human Brain Project, like the brain initiatives around the world, but also other types of digital biology are creating new versions of how we understand disease. If we are finding new models, the disease models are going to be different. And that means different types of treatments as well.

Number three: there are also not just disease models, but also people models. I'm going to give you a direct example for that. What we're talking about is the creation of patient avatars, if you will. We've actually done this in the Human Brain Project, and there's a clinical trial starting in January in France, where one of our brain models actually is created now for each individual patient. It's about surgery for epilepsy. There has been no development in 50 years. No improvement of any sort. So what we're doing is basically making a brain model that's created from general data, making it personal, using the data from about 20 different hospitals, putting that into this model of the individual, and then planning the intervention based on that.

This is going to be an interesting result, I think. And we also are commercialising this with Dassault Systèmes in France. So this is what's starting to happen very concretely.

The fourth point is: the rise of artificial intelligence, as I mentioned before. In diagnostics, we're starting to see this very clearly in the imaging world where we're using AI – quickly and sometimes with amazing accuracy – for diagnostics and histology, etc. We use this for cancer and a lot of other things.

And when you think about the whole data flood that's happening with wearables, these four drivers are absolutely key now to actually push this on the supply side. So why are we not seeing more currently? Why are there not more services on the market?

There's somehow a no man's land in the regulatory area.

[This is because], first of all, it's a little bit of an unsexy thing to talk about, but on the other hand, there is a lack of actual understanding what AI and machine learning, etc. are actually doing. What are these algorithms actually doing? And how are we going to create policy based on the sort of fuzzy understanding of what's going on?

So that's where I want to kind of close the loop a little bit with those types of brain initiatives and the understanding of intelligence and the understanding of the actual modelling of intelligence, which an AI essentially is.

I want to see if you can create in some way an independent, let's say multipolar world, where you have an independence of understanding.  

To understand what is in the black box of AI is absolutely crucial in order to have an independent view, and then in order to actually have regulation, which gives you the risking capability that you actually need to market things, and to actually innovate. That's where I think a lot of the blockages are currently happening. And I think that is something that we have to really look at very, very carefully, and where we can actually de-block a lot by just having that sort of independent view on AI.

The convergence of data and compute is the technological basis for all of this, of course. What we're seeing here now is people are talking about the race to AI. But the race to AI is really based on the race to access scale at this point in computing.

High-performance computing is what is really driving a lot of this. Those of you who are a little bit into that, you know that there is basically a race between China, the United States, and Europe, to a certain degree. I happen to work a lot with the European scene here, and we're actually fielding a new concept here, which we call modular high-performance computing, which will massively decrease the cost of high-performance computing and will drive a lot of this type of innovation because it combines different types of computing including brain-inspired computing. And down the road also, we can integrate quantum accelerators into those systems.

What's the outlook for healthcare for innovation? Those four drivers that I mentioned before, the patient-centric model, new disease models, new patient models, and the rise of AI combined with the race to access scale, will pretty much define the future of healthcare.

The opportunities are tremendous, especially if we're looking at the numbers that have been mentioned by previous speakers. I think we're seeing a mathematics emerging here that's quite staggering. The challenge for all of us, and this is part of why we're here, is to make sense of this and try to find the verticals that we can actually implement.”