Loading...
Loading...
we're finishing up this feasibility study and the company is at the point where we are building a device ready for commercial grade manufacture, and then presenting that to the FDA and negotiating what we think a pivotal trial should look like. And it's an interesting time for the field because no company I mean, I mean, you know, there's been a lot of work in academically like with BrainGate. And but they've all been academic iterations of, you know, slightly very slight variations on a theme with use cases in an academic setting to prove some level of performance. So what we're now trying to do is get a base level of performance across a range of patients that's usable for a large number of people and proving out that we can demonstrate benefit in a pivotal study which has never been done in BCI. before. And, you know, part of what I'm going to talk about is, it's not obvious how you measure clinical efficacy. With the BCI. There's a face validity to this. There's like, well, you can see the patient doing something and that's beneficial. That's true, but how you quantify things from a clinical perspective 
is is an unanswered question. And I think whatever metric we get to that we're going to present to the FDA and we we have one, which I'm going to describe to you now is going to have an impact on shaping the field to come after us with how we start to do things. And if you look at all of the like nature papers recently coming out, not present a few of them they're all very different. So So I want to talk about four things. One, what is the actual unmet clinical need? Because that is different to the big focus in the BCI world, which is how high can your performance be? How, How good can it how powerful can it be? It's actually a different question to what is the base level of need that the patient has that can we start to address because they don't always match up to what I was just discussing, which is how do you measure clinical meaningful performance? And then I'll explain how we have approached things from the blood vessel and what we think it's going to take to bring this through through clinical translation. Okay, so in recent weeks, you've seen you may have seen these two nature papers come out from the Stanford group, the brain gate group, with Jamie Henderson, and Hochberg and CO as well as the Eddie Chang group and UCSF both phenomenal work and, you know, bringing up to state of the art in BCI. Really high word per minute rates, but still in a pretty, you know, experimental type setting and if, you know, as anyone who studied medicine you would have seen the pictures when you first learn about cardiac pacemakers, and you see what those first cardiac pacemakers looked like leads coming out of the chest, connected to a fridge sighs bit of electronics in the room. I kind of feel like that's what this early BCI is, you know, engineers in the room cables coming out of the skull training periods that go for quite a long time weeks to months. Like that's, it's incredible, but it's not ready for, you know, Primetime clinical translation. And what I find interesting is the first Nature paper came out in 2006. The first human implant was the Scott Ian Kennedy, who there's that Netflix documentary about him you should check out called Father, the cyborg. It's about a Scotsman called Ian Kennedy, who was actually the first neurologists to conduct human clinical trials. Anyway, that's historical but and then Hochberg publication in 2006. What I think is interesting is from 2006 to 2023. We've used the same system in you know, individual use cases where there's been huge improvement, but why is it that there's still no device on market that's available? to patients, these are still only available in a clinical trial setting at a very low number of patients. And we're still using a very similar system and it just, it speaks to how hard it is to to achieve clinical translation in this field. Now neuro link have come along and your link have already spent around $300 million, and they're still not in a human clinical trial testing and they're going to get there. But you know, does it take $300 million? No, we we think we're getting close but we made a bunch of design decisions to really simplify down the system to make it easy to use but also manufacturable scalable, and repeatable. So, you know, so I want to just speak around
there was a really nice Nathan crone is a neurologist in the US. He's at Johns Hopkins, who's done a lot of BCI work, and Nick Ramsey is in the Netherlands in Utrecht. He's a neuroscientist who published a paper I'll show you in a minute, but the two of them got together to write a opinion piece on how we should think about these latest latest technologies. And I I'm, you know, the way they've said this was I just want to talk about this because it's really well put. So number one, you have to make it fully implantable. They said high bandwidth recordings were taken from hundreds of electrodes which had to be connected to external amplifiers through a pedestal penetrates the skin which is cosmetic typically unappealing. I think that's you know, euphemistic to say, cosmetically unappealing I you know, patients that don't like it, but the biggest risk is that you constantly have an infection risk. That's the more concerning thing with this. So, there's a reason you know, the Pacemakers became fully implantable. Troubleshooting highly skilled researchers were actively involved in the operation of reported BCIs, which remained too complicated for caregivers to operate in home settings without extensive training and maintenance. So I characterize that as troubleshooting. It's just not something that you might think about. But if you have a bunch of engineers having to make this work in the room, which is the case with every single BCI demonstration, that's been reported in the literature, you have to solve for that. And that is there's so many things to troubleshoot, and part of it is the complexity of the needs of the system to start being effective. So you have to remove all of those needs. If you're going to build something at scale. It just has to work and not have to be troubleshot. Because you're you're talking about patients that are severely impaired, they can't do any troubleshooting. And if there's a need to fix things along the way, you've defeated the whole purpose of what you're trying to do. And then stability. So I think mea stands for I can't remember the is it multi unit, I can't remember, they're talking about penetrating arrays. Signals tend to be unstable and require frequent updating of speech decoding models might be limited by degradation of electrode materials, and tissue encapsulation of the devices. So they're different things electrode of the materials is is a question because there has been an increasing introduction of polymers into implants where there's a you know, I was just saying to Andreas and will, there is a question mark over the longevity and degradation of polymers if you put a polymer into the brain. Now, we're seeing that with epilepsy applications, but if you go for devices that need to withstand, you know, a lifetime, and you put them on a polymer polymers degrade. So that's a big question. Tissue encapsulation is different tissue encapsulation is that the if you're going to penetrate into brain parenchyma
with eye gaze couldn't use eye gaze outside. And eye gaze has its own issues with constant recalibration. And so this system has become her she has been using this now for seven years. And the eye tracking has you know, been there at times but it's not always her full back and this now has become a fullback and she can, as you see, go outside with the system. So I think this was you know, it's not really talked about this paper very much because it doesn't have the flashy 50 words per minute rating, which is what the whole world is fixated on is words per minute, or like how powerful the system can be. This is the only BCI paper that's in New England Journal of Medicine and it's because it's actually focused on what the patient need is. So for me, this is my most inspiring paper and what we're trying to build towards Tim Dennison. I don't know if he's on the call, but Tim Dennison was on this paper as well. This was actually the Medtronic system that Tim, his team built at Medtronic when he was there. And so Tim was a
very early inspiration for my team and worked closely with my team as we're thinking about this sort of solution case as a design inspiration. Okay, there's more to come on this by the way, like we are still working on the patient need one of my close collaborators and other Australian who's here in New York called David Petrino, who is a physical therapist, physiotherapist, PhD, who works with patients a lot. He's doing a lot of the work on thinking about the patient need and starting to build a scale that we think is going to be useful. But you know, this is an area that is kind of I think neglected but it's really important for BCI to make it into the clinical domain so that physicians can start discussing what matters and what doesn't matter. Okay, I've kind of talked about this a little bit, but I'm now going to make an argument for how I think how we came to a clinical metric, which is not what you would typically see with BCI and so part of that is the burden is on us to describe how a motor BCI restores a bodily function. And so that, you know, you guys have used the term neuroprosthesis I think the term neuroprosthesis is really interesting. I think it's not necessarily synonymous with brain computer interface. neuroprosthesis means that you have a medical device that restores a brain function. brain computer interface means that you have a device that connects the brain to an outside device, an external device and perform some function. The difference there is that neuroprosthesis infers some restoration of a bodily function, which is not inferred in BCI. And that's really important for I think, from a clinical science perspective, because it's good to point towards how you're what function you're restoring. So the way I'm thinking about this is the FDA used the term motor capability. So you know, as a neurologist, we don't really talk about the motor system in you know, this simplistic term, but I think it's been a really important way to think about it. Motor intent, which again, I don't really talk about much as a neurologist because it's just the function of the motor cortex. So if you have a cortical stroke, you have motor impairment, like you have, you know, a spastic paraparesis Am I speaking like an American now Hemi presses, power presses I'm seeing like an American but motor intent is captured through function in the cortex, motor transmission is is conducted by the the motor neurons, secondary second order and that tertiary auto motor neurons which run from the cortex, brainstem, spinal cord, peripheral nerves, and then eventually they innovate a motor, a motor complex, which then activates control over the joint and you eventually then click on Google Maps on your screen on your iPhone. So, you know, I'm kind of incorporating the iPhone almost into the motor system because what we're talking about is a bypass. Well firstly, just talk about the conditions that can cause this but you know, we're looking at the end use not necessarily of restoration of the joints and muscles, but the restoration of a digital system. So we're thinking about the problem and how does the motor system control a smartphone because we know that this can deliver so much of what your life needs, which I'll get to in a sec. 
own shopping or because they can, you know, communicate with communicate their symptoms. You're starting to see how the use of the DMO in a meaningful in a health economics meaningful way. Really Matters for clinical trials success. Okay. You Yeah, I might just keep going here. But you know, I do recommend this Petrino paper that came out in Journal of neuro dimensional surgery this year is he's done a really good job of mapping out how to think about a digital motor output. Go and have, check out that paper so I think we spoke about that. So, you know, I think just to make the point we've missed you know, with a low output system so if you know where we'd like to get to is complete point and click like a mouse moving a cursor around the screen and then a click. We have not gotten to that yet. We've got to a low number of clicks. But not we haven't, we haven't solved two dimensional control. So So we've calling our system a synchronous switch because it's kind of built around these discrete key press outputs. But because it's simple and stable and easy to 

use and work straight away for the patience, we're now building these layers on top and this is just an example where as distinct from, you know, moving the cursor around the screen to make selections of letters, using something like chat GPT or an LLM to start building out predictions of like sentences and phrases. That's context dependent. Our patients love this because they're able to have much more rich conversations and they what they were having before and it's just been a really simple merging of our kind of simple, dependable output with a really high you know, output model that uses LLM. So I think the LLM are going to be this is how LLM 's are going to impact our life. The LLM 's are impacting everyone's what everyone's doing in the world. For us. It's hugely meaningful because it is this great leveler where it gives access to our patients. To really complicated outputs. Okay, so here's one of our patients in he's in New York. This gentleman was told he would have not been with us 10 years ago. He's got ALS. He's had ALS for I think 15 years and he was totally dependent on other people all the time. He can only he can move his eyes a little bit and you can set your same smile at the end of this. This was the first session he turned on he started using the iPhone with his low number low click System. Why this is so meaningful for him is because he has this man has zero privacy. If he ever needs anything someone has to come in and try and interpret what he's looking for. So I'll hit play here. But what you're going to see is him sending these key
presses to make selections on this app which is going to report pain for him. So this is one of the applications of the system where users are able to navigate their way through, particularly an iPhone you use it on their own
show this is our second patient Phil. He has ALS you'll see you'll see him move his hand he still had some degree of movement, which has deteriorated since then, but this was also his first session and he is using eye tracking. Actually you can see the eye tracking bar here. I show this because it shows what it feels like for him to restore control over the computer where he started to lose that. And it's that feeling of autonomy or the agency piece that I was speaking about. You know what it feels like to lose it but getting it back is a really powerful feeling. And this was his reaction in this first session to see the file. 



so this is Phil now I just I liked this because we got him on to I think is this messenger. I think it's a messenger on Facebook and that's what him and his wife use and his wife was, you know, normally around and having to you know, keep checking in on him. But once you restore text messaging, the caregiver can actually is emancipated can leave the house can do other things. So, you know, that's the sort of impact on the life that comes with that digital autonomy piece. And I think that's really what we're trying to deliver for our patients. All right, I've really been dribbling on a bit here, so I'm gonna try and get through this. Okay, so this is the concept is that we build a stent. We put those sensors on the stent, it gets incorporated into the wall, it sits in the in the dural venous sinus, the superior sagittal sinus which sits between the left and right motor cortices, and it picks up activity. So you know, you know where we are right now, like the motor cortex runs all the way down here. We're primarily recording activity along here but the vision for us and you know where our technology is heading is into the smaller and smaller blood vessels to get to deeper and deeper regions. But we the risk with research and engineering is that you never you know are satisfied with what you've got, and you keep striving for the next thing, but with class three medical implant, you just have to draw a line in the sand and say, we're starting here. So you know, we know what our constraints are, we kind of know what our system is able to do. And we're 
now building a social software platform around the active activation of activity that we get from this particular region of brain. So I'm stents normally anyway, we there was a big huge manufacturing challenge to create an insulation layer between the two metals layer, that's our sort of secret sauce, which no one's done before. And then, you know, for the physicians during the implants, they have to land the electrode right over the motor cortex. So the targeting that has existed in neurosurgery for functional neurosurgery over a long period of time, it doesn't yet exist for Neuro intervention. So we're having to bring in a lot of the technology to enable brain targeting from within blood vessels which normally you don't have to worry about. Different to the gliosis reaction. I told you about earlier, you have a a reaction, akin to skin scarring, so you have a small layer of scarring that occurs, the device gets incorporated in and then it stops. So it stabilizes and that's really important from a signal perspective because what you have then stays the same when the tissue interface stops changing, which is really important from a from a decoding software 
development perspective. And you know, that's what we are excited about because we think that is a critical feature of our system is stability. So we showed that we published our Australian data in JAMA neurology recently and part of that was showing the stability on bandwidth over a long period of time. You could see it was starting to get a little bit of fluctuation there, but that's on I think, on account of manufacturing challenges that we've had to tighten up on. It Yeah, I mentioned the targeting issue, we have to sort of localize the area of brain relative to the blood vessel and then create an X marks the spot for the physician. This is what a 3d angiogram looks like. Everything's subtracted except for the veins. So we come up here, up here, up here, up here, up here. And then drop it in there. And this is what it looks like in the angio suite. So there's a catheter coming up around here and you can't really see the patient. The physician right now is pushing the device in. The catheter head is coming back. I'm just going to jump forward here you can see the catheter tip is coming back. What you can't see because it's not very visible and X ray yet is the central opening up here kind of like a 
we'll keep going. And then this is a CAT scan afterwards. That's what the device looks like sitting under the skull inside the brain, kind of inside the folds of the brain not sort of inside the brain itself but inside the sulci within the brain. Okay, almost done. So you know we started out 2012 2016 In in animal preclinical work 2016 and 2017 to 2019 we were preparing for that first inhuman device. We really just published that work 2022 We got our first then we were working on us approvals. So we got our FDA approval for our first study, we launched that. That's now closing up. And then what we're now doing is preparing for our pivotal study and that's going to be I don't know, 2030 sites around the US. I might stop there. So it's been a long journey. We've had lots of support along the way the support early on before we switched into company mode in research mode was so important and you know we wouldn't be here without it. This is a reaction of Graham, our first patient when he was first typing in the sense of achievement and closeness between him and his wife and his wife was able to now leave the house. It's sort of that's what it was all about. And these are the moments that are driving us all to keep working our butts off and make this make this into reality. Thank you and I'd love to take any questions.