Breakthrough studies in brain science are unlocking unseen mechanisms of cognition, healing and sleep; this session highlights transformative medical impact.
At Davos, neuroscientists and clinicians argued that brain science is shifting from “sick care” to prediction, prevention, and targeted repair—enabled by better measurement, big datasets, and AI. Sleep researcher Caroline Lustenberger highlighted a step change: brain activity can now be measured at home and at scale, making it possible to predict illness long before symptoms. She cited work showing sleep patterns can forecast “over 100 disorders” as much as “25 years in advance,” opening the door to earlier intervention. Irene Tracey emphasized that neuroscience is finally moving beyond the “black box” through living human neuroimaging and cross-disciplinary collaboration, with a practical takeaway: “Harnessing plasticity is key.” Evidence that the brain can rewire—through learning new skills or paired stimulation and rehabilitation—challenges older assumptions that loss is irreversible.
Nancy Ip underscored breakthroughs in high-resolution brain mapping and blood-based biomarkers, noting the FDA’s approval of a first Alzheimer’s blood test and the potential to assess risk “10 to 15 years” ahead. Chris Mansi argued AI’s near-term impact is operational: reducing variability so more patients receive guideline-level care. In stroke, “time is brain,” and AI-driven pathways cut treatment delays and variability dramatically.
The panel cautioned that continuous monitoring will expand, but must empower rather than create anxiety, as “optimizing” can itself become a stressor.
Hello everybody. Today we are going to talk about the latest discoveries about the brain. So there is a lot of great stuff coming out of the neuroscience labs across the world. And we have a great panel with us. For example, there are new discoveries about how to repair neural circuits, that as well unlock new possibilities for treating chronic pain and little pain you have in your shoulder or elsewhere. But as well, how to treat psychiatric disorders and eventually maybe as well, keep our brains young. At the same time, we are also going to talk about sleep and how sleep may help us to enhance learning, well-being and recovery. But there would be no session here in Davos without artificial intelligence and artificial intelligence, as we've all heard, is transforming every single aspect of our lives from personal to professional. And it is as well transforming patient care, neuroscience, diagnostics. So today we will be discussing all of these different discoveries. And we have an amazing panel with us of experts. So we have Nancy Yip over here. She's the president of the Hong Kong University of Science and Technology and one of Asia's most influential neuroscientists, working on both neurodegeneration, but as well how we can regenerate our brains. We have over there. Caroline Lustenberger. She is a neuroscientist in Switzerland directing the sleep lab at the Swiss Federal Institute of Technology in Zurich. Caroline also co-founded Veronika. I hope I pronounced that right, a startup which aims to tackle Alzheimer's disease. We have as well with us the charismatic Irene Tracey. She's a distinguished neuroscientist and as well the vice chancellor at the University of Oxford and an expert on pain. And we have here with us from the US, Chris Manzi, he's a neurosurgeon and the CEO and co-founder of Viz.ai, a leading company in AI powered disease detection and care coordination. So I'm Kamila Markram, I'm the CEO and co-founder of frontiers, a research publishing platform on a mission to make all of science open. But my background is as well in neuroscience. I hold a PhD in neuroscience, but I'm not an expert on any of these subjects, so we will see what comes out. So let's start this session. So what's really changing in brain science. We're seeing all of these transformative discoveries. So I'm going to ask all of you what is the most amazing discovery that you've seen. And why does it matter right now? Maybe. Caroline, we start with you, and then we work our way down here. Perfect.
I try to keep it short, but I think, of course, there are many things, and it's difficult to choose, but I will put on the sleep lens here. And maybe also two things. I'm involved myself. So I now studying sleep for more than 60 years, and studying sleep was something notoriously difficult to do. Very resourceful people had to come to labs, very artificial environment. And what it meant is you could only collect, you know, a bit of data in a few nights of a few people. So a very small snapshot of the whole thing. But now we are in a digital era, which means we can now look at how we sleep, how long we sleep with variables, and not just the one trackers all of us are wearing, which we indirectly measure it, but really literally measure brain activity in home settings. It also means we can now do large scale studies. We can look at long time periods, we can measure a lot of people, and we can combine it with AI, because also with all the data, what do you do if you have limited resources and abilities? You again, just use a handful of information. You will not see the whole picture. And I think what this allows us is actually completely new perspective. Not for a long time you were really reacting to things like we we detect the disease and then we have to react to it to do sick care. But now we can start to predict. In sleep we have a lot of information predicting actually disease years in advance. Just a few weeks ago in Nature Medicine, they showed that 25 years in advance they cannot predict over 100 disorders with high accuracy from just the sleep patterns. And that means we can go to prevention and not just to seek care. And the second one is that we not only observe now the state of the brain, we can actually shape it, not just only during wake, but also we start to do that during sleep, to actually try to really go into the processes that actually make sleep restorative and try to improve the restorative function of sleep, but we may come to that later.
Wonderful, Irene.
Well, good evening, everybody, and thank you so much for inviting me on the panel. It's great to be here. Maybe following on from your point about the broad topic of brain manipulation. So if we think about the history of neuroscience, it's very much was anatomical. It was just understanding the structure of it. And then we understood a little bit more about the chemistry. This was all very much done in either brains that were dead, that we then solidified and chopped up or in animal models. But it was quite limited. And so it's always been perceived as this black box until we started to have tools. I think a lot of science, particularly medical science, the advances come when there's a new technology or technologies, and that opens up the opportunity for us to learn. So obviously, I've spent my career in neuroimaging. That was a tool that has been, you know, incredibly important for giving us the capacity to actually take that basic anatomical knowledge, very much informed from non-human animals, and take it into the human brain and actually have a look at it as it's living, and then particularly developing technologies that allow us to see it in it's working function, and that's opened up our understanding. But of course, what's happened with that is it's given us a sort of gross scale, what we call it systems neuroscience. You're seeing your brain patterns of activity. It's not giving us the genetic or the cellular understanding of what's going on. So we still need that. Bidirectionality. So for me, some of the greater excitement that's coming out of the neuroscience space writ large is to sort of three areas. One is the increasing norm for our younger generation to work across these disciplinary divides on temporal dimensions and spatial. So people who are working at the genetic, cellular level, people working with me at the imaging systems level, people working at looking at how the brain talks to itself in milliseconds versus how does it change over birth to adulthood, where your brain is developing. So temporal and spatial scales require different people, trained different people with different technologies. But I see more in our big research intensive universities, collaborations between those partners so that we can accelerate how much we learn about how the human brain works. I was saying this the other day, the the challenge we've got in neuroscience is you're trying to understand particularly the important diseases that we must challenge, particularly with an aging demographic in an organ, that we're still working out how it works. It's like trying to fix a car engine that's broken when you don't actually know how a car engine works. And so in parallel, you're developing an understanding of just the normal human brain in its healthy state. How does it develop? How does it age? And then if it does have injury or disease or infection, how does that go wrong when you're updating all the time your model. So we're not going to do that at the pace we need to to address all these diseases that are affecting us very quickly. If we don't have people working across those temporal and spatial domains and bringing in then technologies that allow us to manipulate, as you were saying, bringing in brain computer interfaces, bringing in different ways that we haven't thought about how we can change our brain. And that might be through physical exercise, better nutrition, better awareness, which is my final point. And then I'll stop about collecting and curating huge data sets. So UK Biobank is one example of, you know, thousands, hundreds of thousands of human brains being looked at in terms of their function, their conversations, their structure, and then the types of questions you can ask about how does the human brain work and how does it go wrong or what predicts it. Developing dementia. You can ask questions that can relate that structural, functional, chemical understanding to things like socioeconomic status, educational background, nutrition, whether they take exercise or not. Genetics. So now you've got geneticists working with neuroscientists, and they're able to ask completely different questions that we've never been able to ask before because we've been sharing data and building these huge data sets. So sharing data, big data, obviously brain imaging, I'll always say it's a marvellous thing to have because it's given us the access to the human brain for the first time. And then now I think the next big era is the computational neuroscience brain computer interfaces manipulating. We can get into the ethics of that the brain in different ways, beyond taking a cup of coffee and feeling a bit more perky, or having a good night's sleep and feeling better, really actively manipulating it in in a normal way. And I'm sure we can get into the ethics of those things.
Nancy, what are the biggest discoveries? Why do they matter now?
Yes, I think that one of the most transformative discoveries over the past few years has been the, the, you know, high speed, detailed mapping of the brain combined with the blood based biomarkers, the use of these biomarkers to to actually, track brain health and also disease risk. So, you know, omics technology actually, allow us now to, to profile the brain, you know, with really remarkable resolution. And, now we can see how glial cells, for instance, you know, how they shift between different states, how they reprogram themselves in order to regulate neurocircuit, inflammation or repair. So, you know, this advance in technology allow us to achieve that. And, for, for the blood based biomarkers, as you all know, last year, actually FDA approved the first blood test for Alzheimer's disease. And and they use the phosphorylated tau 217. This really marks a significant milestone, for, you know, the prediction of the risk. And so with this kind of, achievement, now we can use the, the blood test to evaluate the risk of individuals. And this is very important because now, we can evaluate the risk for, you know, 15 years, you know, before the, the onset of the of the symptoms, we can also use it to track the progression of the disease. You can also identify early molecular signatures, and also come up with, tailor made therapeutic approaches. So so of course all these create, you know, massive data sets as was mentioned earlier. So again, you know, AI is indispensable. It really allows us to, to analyze these data sets and couple that with imaging. Couple that, with other molecular data that we can derive. And this really allow us to, to come up with, the shift right from reactive care to proactive, preventive care. I think, all this allow us to really have, this multi-scale understanding of our brain and, you know, and the combination of molecular biology, AI imaging, allow us to to really understand, you know, from molecules to network to clinical outcome. So all these important breakthroughs in the, in the technologies now allow us to understand, neurodegenerative diseases, better. I mean, we have to be mindful that actually for aging population that we are now facing neurodegenerative diseases have the have the higher prevalence. And this impose societal economic burden on society. So as scientists, I think all these important breakthroughs in the technology allow us to do things that we previously we would not be able to do. So, we really look forward to more technological advances, you know, in all the areas that we feel so passionate about.
Chris, from your perspective, what are the big discoveries?
Yeah, there's nothing more, devastating to brain health than something like a stroke or, a ruptured brain aneurysm or trauma. Right. When that happens, almost everything goes off. Whether it's sleep, you know, consciousness, things like that. And we've discovered over the past eight or so years some, some reasonably good treatments for these diseases, like coiling, an aneurysm, stenting, aneurysm, removing a clot from inside a vessel called a thrombectomy. And those treatments are fantastic if they're applied in a guideline directed, timely manner. And so my answer is actually going to be, artificial intelligence because of what it can do to standardize care, to reduce variability in care, because every patient who has a stroke in the world, ideally would be having that clot removed from inside their blood vessel as quickly as possible. But human healthcare is challenging, right? The the steps to get a patient from the emergency room to the o.R. Can can be very complicated, but AI based care pathways that we work on ensure that the information gets to the right specialist immediately and allows them to drive care. And it means that patients who have strokes can have that that blood clot removed and can walk out of hospital versus ending up in a nursing home. And so the thing I'm most excited about is trying to make a dent on these devastating diseases that really, really impact brain health.
Fantastic. Thanks, Chris. So let's talk about a little bit how to have healthy brains, because we're hearing this amazing discoveries coming out. But there is this well, an estimate by the Brain Council that says that the cost, the burden, economic burden of brain disease is actually over $1 trillion, not to mention what it means for families and people, right, to have Alzheimer's or stroke or dementia. So let's talk a little bit, Nancy and Irene, how do we repair our brains? So, Nancy, concretely, what can we do to repair our neural circuits?
Well, I do think that, you know, the the discovery is actually, give us new insights on how to repair our neural circuits. So we take Alzheimer's disease as an example. But at the time, you know, the clinical symptoms showed up. Actually, there has been, you know, massive neurodegeneration and the neural circuit, you know, it would be very challenging, to, to reverse the damage. But so now the shift is to go earlier, so that, you know, in the earlier stages, the neural circuits are impaired, but they might be salvageable. So, so, you know, how to come about doing that? Since the cognitive decline actually correlates more with the synaptic, deficit, rather than, reduction in number of neurons, the focus is more on how to, how to repair the neural circuit. And so, the approach taken, one of the approaches taken is, is really to look at, a type of brain cell called microglia. This is the, the resident immune cells in the brain. And emerging studies actually show that the microglia plays a very important role in synaptic modeling. So microglia, when it becomes, when they become dysfunctional, what happens is that they would they would prune the synapses, so it would lead to a reduction, in, in synapses. And so that opened up the possibility of ways to, to stabilize the circuit. So just now, I mentioned, FDA approved a blood test using a single protein, phospho tau to 17. But advances in the in this field led to multi protein, you know, studies, including my own work. So we found that actually, if you have a multi-protein, profile, it actually expands, you know, the, the scope so that, you know, it now becomes a systems level, approach that you mentioned earlier. So, you know, this systems level approach will allow us to integrate, you know, other markers, those from, you know, I mean, those vascular markers or immune markers or metabolic markers. So then when we use the Multi-protein approach, we can evaluate actually what are the pathways that have been affected in the in the early stage of the disease. And that would allow you to come up with approaches to, to, you know, repair, the circuit that.
How close are we to a pill or a treatment for Alzheimer's? That's the question, I guess, that a lot of people.
Here have everyone will be very interested to, to, to know that. But I, I am a firm believer that now that we are able to move up to earlier stage, actually the chance will be much better than if we wait till the clinical symptoms occur. Because in the early stage, you know, now we have ways to identify the individuals that are afflicted, right. So we can predict, you know, will they have a high risk to get the disease 10 to 15 years later? And so we have a much better handle in how to repair the, the impaired. You know, circuit.
Early diagnostics are.
Early diagnostic is really the, the key, in my opinion, I think, you know, early diagnostic tool. And also now we can figure out which particular pathways are dysregulated. Then you can come up with a more, specific ways to, to intervene the progression of the disease. And that's a topic I can discuss later on because we our recent work actually showed that, you know, just changes in lifestyle can already slow down the progression of the disease. And, Irene, you mentioned about the UK Biobank and this is exactly how we did it.
Yeah. Nancy. So which are these changes in lifestyle if you have to give an advice to our audience here?
Well, I think the answers would be, those lifestyle changes that you are all very familiar with, you know, diet, exercise, use of computers, etc. but what we have done is to leverage the, the vast data sets in the UK Biobank. I think this is so valuable. You know, by analyzing the data, I mean, because they have longitudinal, studies and we're able to provide evidence. And this again is using AI. So generative AI will allow us to draw those conclusions. And I can discuss that later.
So Irene, how close are we to treat chronic pain and get a pill for Alzheimer's.
Let me, let me, compliment, you know, so there's something different. So I completely agree with what Chris was saying about the improvements in procedures for just managing acute injury to the human brain. And time is time is essential. And that's and that's the most important thing to value. So I guess the first thing to say is we shouldn't beat ourselves up. I think in the neuroscience community we're often challenged at how can we haven't got a cure for Alzheimer's, stroke, rehabilitation, epilepsy, etc.? It's a young field. We've only had these techniques to look at the human brain in the past couple of decades. So we're not as advanced as cancer or cardiology, but actually we're making very, very rapid progress because actually it's one of the coolest areas for bright undergraduates and graduates to want to go into. And that's great. And it draws in people not just from the biological or medical sciences. It brings people in from physics and engineering and mathematics as they drive computational neuroscience. So that's great because we've got a really growing population, a very bright minds. Now on the problem of what makes us who we are. And that's good news. So so with that, you know, I'm an optimist, but we are making extraordinary progress, not just around just better healthcare. Yeah, reality. But there's a pipeline of novel therapies coming through, which is super exciting. Let me say something different though, and I will answer the question of chronic pain. There's two things. Basic facts about the human brain. You've got gray cells and these glial cells, which are called glia, the Latin for glue. They were thought to just glue all the neurons together and they were just there. We now realize they do a lot more than just a support structure, but the neurons are the ones you'll be familiar with, and they talk to each other and they do all the work through chemical transmission and the connections between that. To have that conversation between different bits of the brain, we have these sort of white matter connections. So one of the textbooks, ways that we all understood the human brain is that once you've lost your gray cells, right, which I'm sorry to say, but from this age onwards, it's just downhill. You're done. There is no way to get them back. There's little bits of the brain that we know generate stem cells you've probably heard of will generate new neurons. But the basic textbook thing is your brain grows from birth to about 20 years old. It gets bigger and it folds and it creates all the connections. So your brain's shape and structure and neurochemistry and wiring and content of gray matter is an absolute product of your life journey. And if you don't appreciate that we're missing a major part of the puzzle. And that's why these big data sets that link it to your whole lifestyle are so important, because that tells you how your brain is shaped and sculpted. And it is a it is a reflection of your life's journey. And this is really important because I think what we're realizing from these brain data sets is whether you have a resilient or a vulnerable brain becomes really important for then as you go from 20 to hopefully 100, all the other challenges that your brain's going to have to deal with are stroke, maybe getting an infectious disease, maybe having a disease like Alzheimer's, how well equipped you're going to be, or chronic turns out probably to be vitally important about where your brain was at in that vulnerability. Resilience. Do you have the networks? Do you have the capability to repair? Do you need help with that repair because you just don't have a particularly resilient or very good repairing brain. So that's why some of these data sets are actually quite politically explosive, because they reflect that many things that governments and politicians should be intervening in educational background, opportunity, good nutrition, you know, all these good things that we sort of intuitively know is probably good for you. Now we have the evidence to prove they make a difference, and you're going to end up with a brain that's just not going to be very well equipped to deal with life's things. And that even goes to things like addiction, propensity impulsivity with nicotine addiction or alcohol addiction, etc.. So so this resilience vulnerability question is really important. The growth of the brain and it's life's journey is really important. The ability to see how it's built and structured. The textbook was once the neurons are gone, they're dead and you can't rewire the brain. But new techniques and I won't bore you with the name, but they allow you to look at the white matter connections, the motorways that send the signals around the brain. Some very simple experiments proved because we had a technique that that wasn't true. So hundreds of years of just assumption about the human brain was just this thing that then just degenerated. We realized, actually, you can rewire the brain. There can be changes in its complexity, which means some of these lifestyle interventions of doing Sudoku or crossword puzzle, getting a good night's sleep, keeping active mentally, learning, learning a new skill, learning a new instrument. Just keep doing it. Because it turns out we've got these techniques that can look at your white matter connections. And you know what? You take a bunch of students and you teach them to juggle. You can see a measurable statistical change in the wiring of their brain over the course of several months because they've learnt a new skill and the brain will react. That was revolutionary. And that was only just in the past two decades that we realized the brain actually does have the capacity to rewire itself. Yet to be said. Whether you've got neurons that we can self-generate, we know there's a few places in the sort of smell area that can do that in memory. Generally, you'd have to put stem cells in, but who knows? There's still things to discover. It could well be there's other parts that can generate new neuron cells. Let's not assume that's not the case, because we've been completely wrong about this other matter. And it turns out the brain has got this incredible what we call plasticity to adapt and change. So so I just want to give a little mini tutorial for those of you who are not neuroscientists, about sort of where we've been in the thinking vulnerability. Resilience is key. Your brain is on. It's a reflection of your life's journey. The bumps and scrapes that you've had will shape whether your brain is resilient or vulnerable for life's onslaughts. And then the question is, how do we how do we deal with it and what the techniques are?
And I think one sentence.
In one.
Sentence.
Harnessing plasticity. Harnessing plasticity is key. And one of the things you can do which say some of my colleagues who work in stroke is if people are not naturally rehabilitating way they've lost, say, paralysis, they can't move. Some people will naturally regain motor function, others just not well. If you take brain interference device, attach it to the cortex and just stimulate it a little bit. Nine volt battery pack. Very easy. Combine that with physical therapy. You can just encourage the brain to drive a bit more repair and plasticity than they would naturally be able to do. Because of that, whatever their genetics are, and that can improve outcomes. So again, you've got to always start with the basic science. I mean, I'm a big proponent that you've always got to have something to translate. We're not going to be able to make the impact on these brain diseases if we still don't understand the fundamental mechanisms, because they're going to give us the ones to go through. And in my own field of chronic pain, you discover basic neuroscience about just how the human brain encodes pain. You touch a candle, it hurts. Where does that evolve in the brain? Once you've worked that out, you can start to translate that into chronic pain patients. Then you've got new targets for neurosurgeons to go in and start to network, disrupt and stimulate. Then you can take things like phantom limb pain and completely change the way you're going to treat that, because you've understood the basic science of the brain, and that's the area we're on. And I think we should not beat ourselves up that we haven't got the solutions yet because it's still very young. But you see those as great examples that you can actually have measurable impact in patients built on the solid basic neuroscience.
Thank you, Irene, for basic neuroscience. So I Carolyn, let's talk about sleep. We certainly don't get enough of it here in Davos. Yes. , us.
Me included.
Are memories to our emotions, to our well-being. How important is sleep?
Of course. I mean, I'm probably not objective, but I can say it very confidently. Sleep is the single most important behavior we have. And I think we touched upon many important things, including timing, healthspan and so on. You know, the silver tsunami is coming. I think we are getting older, but getting more years of life do not automatically mean more healthy years, right? Actually, gap is increasing between healthspan and lifespan and we need to close this gap. And sleep is a fundamental part to be able to do that. Because sleep is the most important regenerative process we have point. It's non-negotiable. It's biology. It's not about is it just six hours or seven, you know, I mean, why do.
Sleep actually, why do people sleep?
I mean, for for many reasons. And of course it depends the species you look at. But I think that generation and is is a key aspect of it and thinking of it from an evolutionary way. Right? I mean, for many species it's actually a vulnerable state. So it's very risky and it's costly. So it means it needs to be absolutely essential and it is. Right. But maybe to just give two concrete examples, for you. So sleep is actually important for all core neurological and physiological functions, not just for the brain, also for the body. And yet, one of the most recent findings about its involvement is you can think of sleep like a housekeeper for you. You know, one part is that it's basically trims your synapses down, allowing new things to learn the next day. This is already a theory that is longer time going on, but it's also like a washing machine to your brain, literally. I mean, the idea that when we are awake, one consequence of using our brain and our neurons is that we build up waste, metabolic waste products, and they are toxic. So we need to get rid of them at one point. And recent studies have shown this is most effectively happening when we are in deep sleep, right? If we hamper that process, if we actually don't allow it to happen, we actually start to have problems and pathological processes increase. There is a huge bidirectional relationship to Alzheimer's disease, right, because of that. So neurodegeneration is one key aspect of it. And I also believe when we talk about healthspan, we often imagine a conversation of 40 or 50. It happens in the prevention starts and life starts, right education in the beginning. And we have to have that as part of education. Understanding sleep. The second part is timing that we completely underestimate. Also in sleep, you know, we always talk about how much sleep, how well you slept. But one fundamental process that shapes our sleep is our circadian clock, our inner timing system. Actually, we are time. Every single cell in our body has a clock, and it decides not only when we're awake and asleep, but also all metabolic processes, biological processes turning on and off. And it's completely underestimated in our society because it even shapes how treatments work. Depending on the time you give certain treatments in the circadian time, it has a different effectiveness and side effects. And so we already have a lot at our hands, but we don't use it wisely enough. And I think the key is not only chasing the next new thing, but using the knowledge we have now and translate it into society. If it's just knowledge, it will not have impact. And I think that's also something we should really much.
So what's your recommendation? How long should we sleep or is that all individual for everyone?
Absolutely individual. I think the key question everyone has to ask is how much do I need and when is the right time? And of course, most of us are between 7 and 9 hours. But this is just an average. It's like a shoe size. Not everyone has a 38 as a woman, even though it's the average, right? And more important is that you understand it and to be honest, reflect on yourself. If you fall asleep in all presentations, if you cannot stay awake, if you have to catch up on weekends or free days, you don't get enough sleep point. So try to to get that. And I think what we also said, I mean good sleep starts during the day. It's not about how you sleep, it's how you spend your day with your lifestyle, socially engaged. Use your brain. Use your body until old age. Sleep looks younger in people who stay young during the day. So we can actually do that, right. And we should do that.
And is there anything that we can do to improve our sleep patterns?
Yes. So I think what I mean, of course, it's also individual, what works and what doesn't work. But I think the biggest sleep culprit we have in modern society is stress. Stress literally keeps us from sleeping. And this is something that affects all because, you know, for for the brain to be able to fall and stay asleep, the arousal systems need to go down. And at the moment we are under constant stress. We basically take our workday into our bedroom with the digital devices. This is something that happens with this. We don't have this classical end of the day anymore. It doesn't end for our brain. It doesn't end. So what I always recommend is like, do a deliberate downshift, do a disengagement. I mean, take the time off your devices, off duties, and just be in the moment. Relax to breathing. And if you practice that not just before sleep but during the day regularly, you will be able to easier fall asleep and stay asleep. Maybe one of the most important recommendations today.
Thank you. That's great. So from relaxing taking a breath back to artificial intelligence. So Chris. Let's say I doing to stroke to the diagnosis of stroke. And how is it helping us to treat it.
If a stroke in many diseases? I think the biggest impact of artificial intelligence on healthcare today is reducing variability of care. So it can do lots of different things. It can speed up, you know, the processes that doctors have to do, writing notes, the administrative things. The thing I'm most excited about, though, is reducing variability, because if every patient got treated by guidelines, the outcomes would go up so significantly and costs would go down so significantly that we could live much longer. We could afford healthcare, right? And it would be an amazing state. AI works the same at two in the morning as two in the afternoon. It works the same in a rural setting as a major academic setting. So as long as the AI is able to look across the entire care journey from when that patient first touches healthcare, has the heart scan and the head scan, whatever it might be, all the way through to definitive treatment, and ensure those steps are happening efficiently and effectively. It can dramatically reduce variation in stroke. For example, in stroke, every minute 2 million neurons die. That's approximately equivalent to a week of disability, right? And so, you know, every minute really, really counts. We say time is brain. With a pathway that we launched back in 2018, we were able to reduce the time to treatment dramatically by around 84 minutes. That was very important. But what really caught my attention in the FDA study was the standard deviation measurement of variability dropped from 120 minutes down to seven minutes. So now all of a sudden, these patients were getting treated consistently no matter where they showed up, what time of day, what doctor was on. Because there's so much variability in expertise in medicine that that can be a big factor. So I think the future is one where AI care pathways act as a safety net, ensuring for every disease that we have consistent care across the board.
And how does that care look like? How do we need to think about that? Is there a doctor that works with an AI, or is it a patient that wears a device and the two talk to each other? How do we need to think about this?
So it's it's certainly not fully autonomous, right. Today we're probably treating about, depending on the disease, 5 to 20% of patients per guidelines, like kind of what we'd ideally want to treat every patient. So 80 to 95% patients are not getting the ideal pet care pathway. And so there's a huge way to go. And so today we need to work together with artificial intelligence to augment human intelligence to make sure that we're treating these patients more effectively. So what does it look like? It looks like us adopting as quickly as possible across the developed world and the developing world, as many tools that can shortcut pathways to better diagnosis and treatment. I think what.
Are these tools? For example.
The tools AI that reads scans, right? AI that refer patients to the right specialist, AI that compare what's in the electronic health record, summarizing it so it's easy for the doctor to review with what's in the guidelines and identifying care gaps. So the doctor gets told about the patient, but immediately sees that compared to these guidelines, this step, that step, and that's have not happened yet, nudging them to do the right thing consistently. Right. It could be doing the right test. It could be doing the right, giving the right drug. It could be doing the right surgery. It depends on what the disease is. And these tools can work just across the board in so many different diseases.
Great. And how do you see then, the role of the doctor evolving in this world? We've been talking about this as well. AI taking over jobs versus taking over tasks. And the doctor could maybe have a bit more time to spend, talking to the, to the patient. What's your take on this?
I think that's very true. You know, today, for sure, a health system that uses artificial intelligence outperforms a health system that doesn't. A doctor who uses it outperforms a doctor that doesn't. We see that very, very clearly. AI can probably do now 90 to maybe as much as 98% of the cognitive work the doctors do, you know, reading scans, you know, pulling up guidelines in your head. AI can obviously do that much more efficiently. And so what does it look like for the doctor? It looks like the doctor using these tools as much as possible, so that 5 or 20% number can go up to 80 or 90% number. So we can treat more patients. It doesn't unfortunately, for a long time until we get there, look like the doctors having a lot more time on their hands. So we need.
To give them time.
No, because because there's more patients to treat right. There's exponentially.
More
Treatments for these patients. Basic neuroscience is going.
To get more doctors.
Well I think we may doctors way more efficient. I think that's the first thing we do need to train more doctors, right. Doctors are not going away anytime soon. We do need to train more doctors, but if we can make them more efficient and effective so that that specialist can see three times more aneurysm patients right, than they're able to see previously, because they're spending all their time typing notes. That will be a huge impact.
That's great. Okay, so back to everybody. We've got a couple of minutes left. So do you see a future where we are continuously monitored in order to optimize? That can be a great future right where we were. These devices continuously monitored and with that keep our brains younger and prevent, certain diseases, stroke, Alzheimer's, etc.. Let's start with you, Chris.
I think. Yes, but quite far into the future. I mean, I'm wearing an aura ring.
Yeah.
Quite funny comparing aura ring scores at Davos. So especially.
With the sleep scoring.
How many people have an aura ring in the audience.
Yeah.
Oh not that many.
Similar device I think right now it's a nice tool but it's not directing us to better treatments. I think we've just got a lot more to do in understanding basic neuroscience, how the brain works from there, coming up with treatments and then connecting it to the internet of things. So I think it will have an impact, but maybe a decade or two into the future.
Okay, Nancy, what do you think?
Well, I do think that, you know, having wearables like that will have very important impact because you you can use it to, to monitor, for example, if you have certain lifestyle changes, then you can look at, you know, the changes in the biomarkers and and then, you know, draw a conclusion whether that kind of behavioral changes will have a positive impact. So so for example with Alzheimer's disease, you know we have the blood tests that will allow you to, to sort of predict, you know, whether you have high risk, medium risk or low risk in 10 to 15 years time. And then with the variables you, you also add on top of that to have, you know, continuous monitoring. And our studies show that there are certain lifestyle factors that actually will slow down the progression of the disease. So then with with the continuous monitoring, you can, you know, see if certain lifestyle changes will actually have a positive impact in slowing down the progression. We actually show that for high risk individuals with certain lifestyle changes over time, they will become low risk. And this is based on, actual data from the from the UK Biobank. And, and one of the lifestyle changes you.
Well, we don't have that much time left, so I will hand over. Sorry to interrupt.
So I think for, for for data gathering, it's going to be fantastic to have more wearables, to just build up those data sets and understanding. And I think it could, for patients, be completely revolutionary in how it would change even the health system. And that rather than having the regulated, you come in every time you're monitoring and you're called in when something AI or a doctor is monitoring that. Now you need to come in because we need to change, something about your your treatment because we're picking up the the changes. My worry would be for healthy living. This is more for you to answer. Is the stress that comes with knowing too much and the assumption that there's norms. So we talk a lot about wellbeing and thriving. And we're always trying to make that good for our students in the university. But let's be honest, we don't really know what the the normative distribution of what well-being is. My well-being is going to be very different to what you would be, and you would be. So the concern would be, how do we responsibly use these wearables and who's deciding what where we're going, what, what you're trying to change in your lifestyle to reach a target? And I think we should just be more confident in reading our own bodies. And I could see where we go back actually to less monitoring and go back to some basic lifestyle habits that maybe our parents and grandparents.
Told us, well, sleep well. What do you think?
Sleep well.
So I think Tracy actually summarized it very well. But I also wanted to say, I think it's not a question whether we do it. It's already we are in the middle of it, I believe. I think we already started. It will just get more precise and we access more of the brain. The question is how we do it, and we have to be very careful that we do more good than harm. I think it will be important for prediction. Absolutely, because prediction is the key for prevention. And I think that's where we have to head. But we have to, as you mentioned, we have to make sure people get the agency and the empowerment to use data wisely. We see now if these trackers already the downside because what happened is people get so obsessed with optimizing their sleep, there is a new sleep disorder.
Or insomnia.
Or dyssomnia. I mean, a new patients because people are so obsessed. So that shouldn't happen. It should empower people to feel better, not to feel worse.
I think.
That's a good last word.
Bravo.
So we have 1.5 minutes left. There is a question from the audience. I let you ask it.
How can stem cell.
Just a second as a microphone coming.
To generate regenerate your brains? I do it with my blood already that I regenerate or I put extra soldiers in my blood every three months and I, they they are my own soldiers who are multiplied. So it's my own blood. And they say that works also for your brains. But the only thing it works. I feel very fit, but my brains are going down, and I feel that because I forget something sometimes. U.S. 87. So it can be possible, of course, but how can we regenerate our brains with stem cells?
Who wants to take this question?
Maybe you should, because there's been surgical studies done with stem cells in Parkinson's.
And and in stroke. I think we are some way away for having an approval for stem cells in the brain, to be honest. So I think it's a very exciting field of study. It's not going to be in the next five years.
Apologies. One last question, Cynthia.
Do we have time for one last question?
Take up an instrument, learn some new skill. I'll be better for your brain.
Very brief. Cynthia.
Good question.
Thanks for this great panel and it's refreshing to talk science and not politics. Just a quick question. As a women's health doctor, and noticing the increased rate of Alzheimer's disease in women and also looking at the interest in hormone therapy, I wondered if you had any comments about the use of estrogen as a protective role for the brain. Maybe alcohol?
Great question. Great question.
That's a good question. I can answer the alcohol.
In one sentence, though. Yes, Nancy, because we're out of time.
Reduction of alcohol is is good for slowing down the progression. We have data to show that.
What about estrogen as a neuroprotector?
I think we haven't appreciated the impact hormones have on the brain. It is remarkable. So if I look in my own field, because chronic pain is quite prevalent in women rather than men, there's a whole set of things. But we've done a lot of studies on looking at the hormonal variation, differences in women's natural background of testosterone or estrogen, and whether it has an impact on just even a standardized temperature input. It is. I didn't think it would have any effect. It is phenomenal. So to not assume that hormones have a powerful influence, maybe I'll just finish with a joke. I remember coming home after the first experience. My husband is saying, do you know what? Turns out that the woman's brain only is like the same as a man's brain. Two days, two days a month, he's cooking dinner and he's like, oh, that's really very interesting. Not daring to comment about that. Go figure. But it's profound. So I don't know what the answer is, but we've got to do a lot more work to understand the influence of hormones on the brain.
Yeah.
Thank you very much. So lively discussion.
We are at the end. Thank you everybody. Thank you.
We get a.