The future of retinal implants
Professor of ophthalmology Daniel Palanker is a physicist who has combined his skills in optics and electronics to create PRIMA – the Photovoltaic Retinal Implant.
Inserted beneath the retina, it restores vision to patients blinded by retinal degeneration, allowing them to read and write – and with the next-generation software, to recognize faces. PRIMA’s photovoltaic pixels act like tiny solar panels, converting light into electricity to stimulate the remaining retinal neurons. Better yet, the growing field of brain-computer interfaces may have implications beyond ophthalmology. “Unlike medicine, where the road ends with curing a disease or restoring lost function, the prospects for brain-machine interfaces may be infinite,” Palanker tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.
Transcript
[00:00:00] Russ Altman: This is Stanford Engineering's The Future of Everything, and I'm your host, Russ Altman. Since we started this show eight years ago, it's become an archive of amazing and impactful work by my Stanford colleagues. Research is not something that just happens in the lab, and as you'll hear on this show, the research at Stanford can impact areas like health, technology, law, and business, and many other topics that can affect everyday life.
[00:00:23] We hope you'll tune in to learn more about how research has the potential to help your life and to help the lives of people you care about in your family and your community.
[00:00:32] Daniel Palanker: So PRIMA does stand for something. It stands for photovoltaic retinal implant.
[00:00:37] Russ Altman: Okay, good.
[00:00:38] Daniel Palanker: And, so what it does, it basically tries to replicate the function of lost photoreceptors. So it's just a photovoltaic array, so it's a little, you can think about it as little solar panels, basically-
[00:00:53] Russ Altman: Solar panels
[00:00:53] Daniel Palanker: converting light into current. So little pixels, so we have, pixels in this array, photovoltaic array, that convert light into electrical current. The current flows in front of the electrodes from active to return electrode in each pixel and polarizes neurons sitting just in front of it.
[00:01:09] So, the only, you know, requirement is proximity. As long as you're close enough and the current is strong enough, you polarize the nearby neuron.
[00:01:24] Russ Altman: This is The Future of Everything, and I'm your host, Russ Altman. Thank you for listening. If you're enjoying the show, please rate and review it. We like to get a good rating, and we'd love to see your comments. It helps us form the show and make sure it's as good as it can be.
[00:01:37] Today, Daniel Palanker will tell us that he can restore the vision of those who have lost it with electronic arrays that are implanted into the retina. They're light sensitive and they talk to the brain. It's the future of retinal implants.
[00:01:53] Today we're gonna continue our feature called The Future in a Minute. At the end of my interview with Daniel, I'll ask him a few quick questions and he'll give me a few quick answers. Also, thank you for listening and please rate and review. Give us a five if we deserve it. That helps the show
[00:02:14] So the loss of vision can be life-changing for individuals who it happens to. This can happen from diseases of aging. You may have heard of macular degeneration, which affects older people and can lead to loss of vision. There are also genetic diseases where children lose their vision early in their teenage life.
[00:02:33] So this is a terrible problem for many people and something that needs to be addressed. Well, in the past, there have been retinal implants, but they really only led to flickering light that allowed you to see light and dark, but they didn't really allow you to get to things like reading, writing, maybe even facial recognition.
[00:02:51] Well, there's been some breakthroughs, and today I'm speaking with Daniel Palanker from Stanford University, where he's a professor of ophthalmology and electrical engineering, and his group has developed an implant that actually allows people to read and write. And they're looking at clinical trials that may advance to not just grayscale, but color, and also to the ability to see faces.
[00:03:17] So Daniel, to get started out, how did you decide to devote your career, you're an electrical engineer by training. How did you decide to devote your career to vision and ophthalmology and all things about eyes?
[00:03:29] Daniel Palanker: Well, I'm physicist by training. I, was torn from the very beginning after high school to be, to go to physics or medicine. And it turned out that I went to physics and then, decided to apply to medicine. So that's a full circle, and I think it was the right decision.
[00:03:49] It also happened that, I did, my PhD in, Hebrew University of Jerusalem in the field of applied optics, with applications to, ophthalmology, in particular retinal, lasers. And that, when I came to Stanford as a postdoc, I, was in Department of Physics, but, we met, on occasion with a new chair of Department of Ophthalmology at Stanford, Mark Blumenkranz, and he was looking for a physicist who can help him develop the field of, of ophthalmic lasers, and so he hired me in that capacity. So this is how I came back to ophthalmology at Stanford.
[00:04:33] Russ Altman: Fantastic. So we have a lot to talk about and including some recent work that's just quite amazing. But before we even get to that, for people who don't think about eyes and vision, I wonder if you can just give a summary of, like, what the key things we need to know about how the visual system works and, and the kind of the key vocabulary that you might be referring to when you describe some of your recent work.
[00:04:56] Daniel Palanker: Yeah. Eye is a beautiful combination of optics, which projects the world onto the retina down to diffraction limit of about three micrometers, and neural tissue, the retina, that converts this image into neural signals, and it encodes it eventually in a, a digital format that propagates to the brain.
[00:05:17] So the retina itself is a three-layer neural tissue. The first layer of photoreceptors convert light into changes in cell potential, hyperpolarizing or decreasing potential of photoreceptor, basically proportional to light intensity. And this is in the language of electronics you would call analog electronics. It's basically a signal proportional to the input.
[00:05:39] And then, there is a second layer of integration of that signal in, bipolar cells primarily, also regulated by amacrine and horizontal cells that keeps it still in a domain of analog electronics, but it is, it enhances edges, it, kind of splits it into on and off pathways, and this adds complexity, but still it's analog electronics and this is where we are hacking into, by the way, into that second layer when photoreceptors are gone.
[00:06:06] But then on a third layer of the ganglion cells, the, the signal is converted into digital format of binary spikes, and called action potentials. And this is much more complex code. It spreads into multiple types of ganglion cells, about two dozen, each of them specializing in different features of visual scene.
[00:06:29] Some sample with, high spatial resolution and low contrast, midget cells these, some, these low resolution and high contrast parasol cells. Some are responsible for color, vision. We have three, you know, sensors of color, we can call it red, green, and blue, and, direction sensitivity and so on.
[00:06:50] So all these two dozen, streams, propagate in parallel. They sample the whole visual field in parallel with mosaics of cells covering completely visual field.
[00:07:01] Russ Altman: Yes.
[00:07:02] Daniel Palanker: And all the parallel, streams propagate through optic nerve, one million wires, axons to the brain, and then it spreads further into areas which specialize in different aspects of visual scene until it all converges into percept.
[00:07:17] So the code, as we go further and further away from the origin, from photoreceptors, becomes more distributed, more complex, and more abstract, like in any neural network. And therefore, if you want to hack into the system and reproduce it, it becomes more and more challenging the further away you are from the origin.
[00:07:36] Russ Altman: Yes.
[00:07:36] Daniel Palanker: And that's why when photoreceptors are lost and the disease is called retinal degeneration, we address it by introducing something that just replaces photoreceptors and stimulates a second layer of neurons, which is still analog, you know, a, a kind of electronics analog processing of the signal. And code is relatively simple.
[00:07:55] Not, you know, very simple, but it's doable. We managed to replicate it pretty well. But going- Right ... further away is more complex.
[00:08:06] Russ Altman: Okay. So a few pieces of anatomy that I wanna make sure we... So of course, everybody knows that we have a lens in the front of our eye, and it goes through a, it goes through a, transparent material, the vitreous, what we call it.
[00:08:17] Daniel Palanker: Right.
[00:08:17] Russ Altman: Then it hits, then the light hits what you're referring to as the retina. And, and in, and in case it comes up, I just wanna make sure that we talk about the macula, which I, as, as I understand it, is the center of, of the retina that is kind of the most sensitive to, to light. And I know we're gonna talk about diseases of the macula in a second, but that's the part where you get your, tell me if I'm wrong, your highest acuity vision and your ability to detect small differences. And then as you said, there are these layers of cells. They go to the optic nerve, which goes to the brain, which is, complex.
[00:08:50] Okay, so that's great. I- so now I wanna talk about, the things that go wrong, in the eye that require the kind of, amazing technologies that you're working on. So I know macular degeneration is one of the diseases that many people have heard of. Can you just give us a summary of what, what is going on in these key diseases that you're targeting?
[00:09:13] Daniel Palanker: Yeah. So we target the, diseases called retinal degeneration, and there are several kinds of them. The most common one is age-related macular degeneration. In this disease, patients gradually lose photoreceptors in the very center of the macula where we have highest resolution. And that's a very important and peculiar feature of vision that we aren't aware of, that acuity drops with eccentricity. So we are-- we have highest acuity right in the center of the visual field within a few degrees, but 10 degrees away, and we are legally blind. Acuity is 10 times worse than on axis. And then, you know, 40 degrees away, we cannot even count fingers.
[00:09:53] So it's, it drops very quickly. We are unaware, unaware of that because we scan and we, you know, look at what we want to pay attention to, reading and so on. But we become acutely aware of that as soon as we lose it. And patients with the disease of, age-related macular degeneration, when they lose central vision, they cannot read, they cannot even recognize faces.
[00:10:15] And, the, so the reason for this deficiency is that, a supporting layer of photoreceptors called retinal pigment epithelium, that dark layer under the retina that actually is visible, retina itself is very transparent. But that dark layer with age becomes less and less functional and cannot support metabolism of photoreceptors, and photoreceptors are metabolically the most active cells in the body.
[00:10:43] So as a result, this, our retinal pigment epithelium starts, you know, dying off and photoreceptors as well, and the, the gap of that, it's called scotoma or blind spot, is growing over time, expanding over time, and people basically, at some point cannot read, recognize faces. That's one kind of disease.
[00:11:04] Another, class of retinal degeneration is inherited. There are, many, you know, tens of or hundreds maybe even, versions of genetic, you know, mutations that cause, various aspects of, loss of visual function of photoreceptors and that kicks early in life usually. So, very often it begins in teenage, you know, or, in college and, that's even more devastating because basically your productive phase of life is, really blind.
[00:11:39] And so, we've started with age-related macular degeneration because for two reasons. So the first of all, it's a, bigger market and for companies it's important. And second is that retina because it starts late in life, retina is relatively well preserved unlike the diseases that kick in earlier and retina rewires. And it's very important for us to maintain retinal structure because we want to retain retinal encoding. We want to stimulate the second layer of neurons after photoreceptors, but we want the rest of the retinal network to do its job.
[00:12:13] Russ Altman: Yes.
[00:12:13] Daniel Palanker: And that was our assumption from the very beginning, and I think it paid off because it shows that we retained many features of, normal retinal processing with our implant. And that I think is the reason why our patients see form vision unlike all previous attempts of restoring sight. All patients saw were flickering lights, not really-
[00:12:34] Russ Altman: Yes
[00:12:34] Daniel Palanker: Form vision.
[00:12:35] Russ Altman: Yes.
[00:12:36] Daniel Palanker: That I think is due to preservation of code and that is in large part due to preservation of inner retina.
[00:12:43] Russ Altman: Great. Okay. So we're gonna get to your, implant, and this is great, and you've given us a little bit of a clue. just to say that under normal circumstances, these, these, retinal receptors that you're talking about, if, I know this, that they're able to respond to single photons, so they're extremely exquisitely sensitive to light.
[00:13:00] But as you've described, we lose those, and so you have to ... they are the ones who, who begin the electrical signaling, and you're gonna have to bypass them. So now let's get to the exciting, work. It's a, it's a, it's a system called PRIMA. I don't actually know if PRIMA stands for anything. You can tell me that in a second.
[00:13:18] Daniel Palanker: It does.
[00:13:18] Russ Altman: So tell us what is PRIMA? How does it work? And then we can back out some of the problems and the challenges and also the victories that come from it.
[00:13:28] Daniel Palanker: So PRIMA does stand for something. It stands for photovoltaic retinal implant.
[00:13:33] Russ Altman: Okay, good.
[00:13:34] Daniel Palanker: And, so what it does, it basically tries to replicate the function of lost photoreceptors. So it's just a photovoltaic array. So it's a little, you can think about it as little solar panels basically,
[00:13:48] Russ Altman: Solar panels
[00:13:49] Daniel Palanker: ... converting light into current. So little pixels, so we have, pixels in this array, photovoltaic array, that convert light into electrical current. The current flows in front of the electrodes from active to return electrode in each pixel and polarizes neuron sitting just in front of it.
[00:14:05] So the only, you know, requirement is proximity. As long as you're close enough and the current is strong enough, you polarize the nearby neuron. And-
[00:14:13] Russ Altman: So let me ask you before you go on, many of us know about pixels because we have cameras in our phones, and, they, they're getting bigger and bigger. For this first generation, how many pixels are we talking about?
[00:14:24] Daniel Palanker: Right. So the first generation in humans, have pixels of 100 micrometers, and our implant is two by two millimeters in the first generation, so it's basically 20 by 20. It's about 400 pixels.
[00:14:37] Russ Altman: Okay.
[00:14:37] Daniel Palanker: But relatively small. Now we have implants with 10,000 pixels and more in rats, not yet in humans, but-
[00:14:43] Russ Altman: Right
[00:14:44] Daniel Palanker: uh, but in humans, we started very conservatively with 100 microns, and I'm glad we did so because it works well, and you want to start, you know, with success.
[00:14:52] Russ Altman: Of course.
[00:14:53] Daniel Palanker: And then take it from there.
[00:14:53] Russ Altman: And do these, do these pixels, do they detect, a, a black and white light or color or, and, and is it yes, no, or is it a continuous range ofintensity?
[00:15:05] Daniel Palanker: Right. So the way we encode information is continuous. It's not just black and white. But software, so let me explain how the system-
[00:15:13] Russ Altman: Yes.
[00:15:13] Daniel Palanker: Works and where software comes in. So photoreceptors, as you mentioned, are amazing cells. They can amplify light, or signal in terms of ratio of photons per second per cell to ions flowing through the membrane per second, per cell can amplify by a factor of up to a million.
[00:15:32] That's why we can see single photons looking at the stars. And, our photodiodes have no amplification, so the maximum, all they can do is convert one photon into one electron hole pair. So we, to generate enough light, enough current, sorry, to polarize cells, we need much more light. And that's, this is where augmented reality goggles come in. We cannot just convert ambient light. It's not enough. We amplify it.
[00:15:59] And so we put augmented reality glasses. there is a camera that captures an image. We can process it and project back into the eye, using more intense light. But we don't want this light to be visible by remaining photoreceptor, photoreceptor surrounds the implant in the periphery, so we make it invisible. It's 880 nanometers. It's near-infrared wavelengths.
[00:16:21] It's not visible. So it's like your remote control on TV. You don't see it, but TV set does, right?
[00:16:27] Russ Altman: Yes.
[00:16:28] Daniel Palanker: So that, light is much more intense. It's still, you know, safe, but it is, much more intense than normal, and that's how we compensate for the amplification that photoreceptors were providing.
[00:16:39] Russ Altman: Gotcha.
[00:16:40] Daniel Palanker: There's another feature that photoreceptors, together with the layers that right on top of them, horizontal cells, provide, some initial signal processing, contrast enhancement, edge enhancement, and that is also lost because horizontal cells are disconnected, there are no photoreceptors to regulate them.
[00:16:58] We do it by software. . So between the camera and projector, we can do pretty much anything. So we can do contrast enhancement. We can do obviously auto-focusing, adjustment to A wide range of dynamic range of illumination. That's what also photoreceptors do, that's what diodes don't do well. And so camera does all, and image processing does all of those features.
[00:17:22] Now, when the image is optimized for the range where photo, where implant works well, we project that image onto the, into the eye. Part of it which, falls on the chip is converted into image, and this is how patients see. So basically what patients do, they look at the little screen on augmented reality glasses like Google Glass, right?
[00:17:42] Russ Altman: Yes.
[00:17:42] Daniel Palanker: Or any other augmented reality glasses, that are many now on the market. And they see an image, and it is grayscale. It's not color. Because we stimulate, to, to provide color vision, you need to be specific to each bipolar cells that carry specific color information, and we don't have that resolution.
[00:18:01] Russ Altman: Yes.
[00:18:01] Daniel Palanker: We stimulate several of them at once. So what patients see, they describe it as a sun color. It's kind of white-yellowish color. So it's basically response to mixture of all colors. But it's not black and white, it's grayscale. We can modulate brightness.
[00:18:16] However, in a current clinical trial, all the company did was to show that they can read and write, and that requires just black and white. So our software currently basically delivered black and white, you know, images of letters, you know, patterns and so on. And our next step will be actually to utilize grayscale capability of the system. And why it is important, because, the top, on a wish list of patients is reading and writing, but the second right after that is face recognition.
[00:18:48] Russ Altman: Yeah.
[00:18:48] Daniel Palanker: They want to see faces, and faces do require dynamic range.
[00:18:52] Russ Altman: Yes.
[00:18:53] Daniel Palanker: You cannot present faces well in black and white. So our next trial that we actually started is optimizing, software for grayscale representation. And in prosthetic vision, it's not as wide as natural, so we optimize it towards a range that they can see. So we measure that contrast sensitivity curve and optimize software to fit all the information within the range that they can see in a grayscale.
[00:19:18] Russ Altman: This is The Future of Everything with Russ Altman. We'll have more with Daniel Palanker next.
[00:19:35] Welcome back to The Future of Everything. I'm Russ Altman. I'm speaking with Daniel Palanker from Stanford University. In the first segment, we got a beautiful lesson on how the eye works, and we heard initial description of this amazing implant that allows people to read and write and see for the first time after losing their vision from diseases.
[00:19:56] In this segment, I'm gonna ask Daniel about the limits of that technology, how good can it get, and also some of the details about how those implants get in and how they're powered. And we'll end up with the clinical outlook. When will this actually become available to patients? Don't forget, at the end of this segment, we'll do a Future in a Minute where I ask some quick questions and get some quick answers.
[00:20:18] So Daniel, like how do these things get inside the eye of these patients in the human trials, and how are they powered?
[00:20:24] Daniel Palanker: Yeah. So, the device is completely wireless. It's powered by light. And so pixels just convert light into current, and there is no power supply, no wires, nothing.
[00:20:34] Russ Altman: Wow.
[00:20:34] Daniel Palanker: That's what makes implantation very, straightforward, much easier than any other implant, in retinal, you know, prosthesis domain. It's just a little thin, a two-by-two millimeter panel, or array that, is inserted under the retina. The way procedure goes is that, you inject fluid under the retina to lift it, and that's a standard beginning of subretinal surgery, which is done for many reasons like removing membrane and so on.
[00:21:03] Then you make a cut of two millimeters, usually peripherally so it doesn't affect central vision, and it's called retinotomy. And then you slide or inject, we have an injector, of that little panel under, and then surgeon pushes it gently until it lands exactly where he or she wants it in the central, part of the macula.
[00:21:24] And, then retina is reattached, and, the rest is optical. The, you project light and, you get the... In, in fact, in rats, we measure acuity in the same day. In patients, usually they leave it for a couple months for the eye to, you know, heal-
[00:21:39] Russ Altman: Yes ...
[00:21:39] Daniel Palanker: After surgery. But in principle, the retina is reattached right away and ready to go right away.
[00:21:44] Russ Altman: Wow. Okay.
[00:21:45] Daniel Palanker: What is also amazing-
[00:21:47] Russ Altman: Yes ...
[00:21:47] Daniel Palanker: That you can actually remove the old generation, like we did this in rats. You remove the low resolution first implant. You can slide under a version of higher resolution implant, and it provides higher resolution right away. And that's an, that's another beauty is that it's a replaceable organ, in a sense.
[00:22:04] Russ Altman: I was gonna ask about that because I didn't know if the volunteers who get the early ones are then gonna miss out on, and it sounds like they won't miss out. They'll be able to continue.
[00:22:14] Daniel Palanker: They, they're asking about it. The question whether the surgeons will want to do another surgery in a elderly patient, that's another, you know, issue. But in rats, we demonstrated that, yes, you can slide it out, put another one in exactly the same location, and it works with high resolution.
[00:22:28] Russ Altman: Okay. So this, very exciting. We have our glasses, which are amplifying the signal. We have our amazing array on the retina talking to the neurons and getting the brain going for vision.
[00:22:38] So I, I know you're thinking about the future, and I I was wondering, what's, what's the, what are the limits to this? Because we all know that technology gets better. You've already told us that we had 400 pixels, but it's gonna be I think you said 10,000 already. And, and so I- but I'm sure you're thinking there are physical limits, there are it's only gonna go so far. Tell me how you think about that and, and, and what is, what, what, what does that look like?
[00:23:04] Daniel Palanker: Yeah. So the most fundamental limitations are geometrical, like in all laws of, nature actually. Geometry defines, scaling and laws of nature. And, when you make pixels smaller and smaller, the penetration, it's like little fountains that comes out of the pixel, that current.
[00:23:24] It also shrinks, in height, and it just doesn't go deep enough to stimulate our neurons, which are about, you know, 40 microns kind of, deep and they are often separated from the implant by some debris layer of another 40 microns. So there is a certain height we need to achieve. And when you make pixels smaller than 100 microns, it-- at some point, it basically doesn't penetrate deep enough. And you cannot brute force yourself through that because there is a thermal limit, an electrochemical limit, and so it has to be geometrical solution. That's the most fundamental kind of thing.
[00:24:00] Here that our solution is basically to leave the flat geometry and go into 3D. So we, create a, a three-dimensional electrode of different configuration. Simplest one is the pillars where cells migrate around, and that's an-another very fortunate aspect of the, subretinal space that it is actually very dynamic. If you input, introduce something that provides voids for cells to move, they will move.
[00:24:28] And this way, they actually come closer to electrodes, and our pillar electrodes penetrate this gap that I mentioned, about 40 microns, and get right to the target neurons. So this way, we can actually scale pixels down from 100 microns all the way to 20, we demonstrated this in rats, and provide acuity, you know, corresponding to pixel size So that scaling is, is geometrical-
[00:24:55] Russ Altman: Yes
[00:24:55] Daniel Palanker: ... you know, solution, and, it also basically is the same on all other brain machine interfaces. The question is how close it can get to target neurons.
[00:25:05] And, the great example is cochlear implant, where the electrodes are inserted in the cochlear. They are separated by about one millimeter gap from the target neurons, and that's why making them denser than one millimeter doesn't really help. The field diverges.
[00:25:21] And so cochlear implants exist now for probably 40 years, but they're still in a range of about 12 independent channels, or 20 electrodes, but about 12 of them are independent, and that is because of the geometrical limitation, because of distance. Yeah. And so people are thinking how to overcome it by placing it in other locations, but it's exactly same issue, and we are facing it in retina, and that's why we are moving it to 3D structure.
[00:25:46] And fortunately, in the retina it's possible because cells can migrate, unlike cochlear, whereas it is bone and it doesn't-
[00:25:53] Russ Altman: Right
[00:25:53] Daniel Palanker: ... let cells to migrate through.
[00:25:54] Russ Altman: No, this is a huge... I didn't realize this. There's a huge advantage that, nature is helping you by allowing the cells to reach the electrode even if the electrode can't reach the cells.
[00:26:04] Daniel Palanker: Right.
[00:26:04] Russ Altman: Yeah. And they're functional, I presume they're functional neurons that understand how to process the electrical signal-
[00:26:09] Daniel Palanker: Yeah. It's the same cell, but,
[00:26:10] Russ Altman: and they're fully connected
[00:26:12] Daniel Palanker: That's right. The bipolar cells are connected, but the cell bodies can move by about- ... 40 microns down and reach exactly where we, we want them to be. That's unique feature of subretinal space. If you place it above retina, it doesn't happen because there is a nerve fiber layer which makes it very nerve.
[00:26:28] Russ Altman: Unbelievable. Okay, so as you now, you've talked about your, your... You have some initial trials in humans which were successful. you've talked about the rat work. What is the clinical path for this becoming products that people suffering from blindness might be able to benefit from?
[00:26:44] Daniel Palanker: Yeah. So currently, we have about 45 patients, 42 of them in Europe implanted. And based on the results that we published in New England Journal of Medicine in October, we expect CE mark, which is equivalent, European equivalent of FDA, to be granted, I hope this year, maybe even this summer. That will make it, you know, this low resolution first generation kind of device, available in Europe.
[00:27:13] We are in touch with FDA to see what exactly will be the pathway here. But in parallel, we are actually trying new indications. So we started with this AMD, age-related macular degeneration, but we are, going to test very soon in, Stargardt disease. It's one of the versions of that inherited retinal degeneration that I mentioned, and it affects younger people, so usually people are still in a working age, and they are even more eager to get, you know, vision back. So we'll know soon, within about a month, I think, how well does it work in Stargardt disease. And then from there we may take it to other, you know, versions of inherited retinal degeneration.
[00:27:58] But FDA pathway, I don't know yet. it takes longer because we didn't start clinical trials in US, but hopefully they will accept European data, and, will make our pathway easier.
[00:28:10] Russ Altman: What are the big, concerns in the clinical trials? Is it, is it, scarring? I don't know if there's an inflammation associated or, or a kind of infection or a sensitivity to head knocks. What, what are, what, give us a feeling for what life is like with these devices.
[00:28:27] Daniel Palanker: No, the, the... actually, if you don't damage, blood vessels, there is a blood-brain barrier. Retina is a part of central vision, nervous system, and subretinal space is immune privileged.
[00:28:41] So if you don't break, cause bleeding basically during surgery, you are gentle enough, it's actually very well tolerated, surprisingly well in subretinal space. We have now histology of couple patients who passed away during the trial for other reason, and it looks very pristine, pretty much like a fellow eye. But we also have had couple cases where, surgeons did damage blood vessels under the retina called choroid, and this is where the fibrotic seal is forming.
[00:29:10] Russ Altman: Yeah.
[00:29:11] Daniel Palanker: And that is really, you know, a basically a, a showstopper. It will prevent the implant from working. So in a vast majority of patients, the implant is very well tolerated. We have now six years follow-up. They're still working, acuity is still the same, so it's, it's, holding very well. The clinical trial, obviously in elderly patients everything is difficult.
[00:29:34] Russ Altman: Right.
[00:29:35] Daniel Palanker: This is age-related macular degeneration. In younger patients it should be easier in terms of surgery and so on. And in terms of its use, people use it at home now for, you know, home tasks like cooking. Some ladies-
[00:29:49] Russ Altman: Wow ...
[00:29:49] Daniel Palanker: actually sent me pictures that they, started painting. I, I met a guy who is architect in Rome, and he's now back to work. He's, designing. He wanted to finish his, church design and couldn't do it. He stopped, and now with his implant he is back. It's amazing what people can do with so few pixels. I was very impressed and surprised.
[00:30:11] Russ Altman: Yep, the difference between zero pixels and 400 is a, is a, is amazing. Well, well, thank you very much. And this, congratulations on this work. And, and before we wrap up, I just wanted to, g- move to our segment called The Future in a Minute, where I ask you some rapid-fire questions and you give me kind of short, sweet answers. are you ready to do that?
[00:30:32] Daniel Palanker: Yeah, absolutely.
[00:30:33] Russ Altman: Here we go. What is one thing that gives you most hope for the future?
[00:30:38] Daniel Palanker: Well, the progress in understanding the neural code and engineering around biological constraints, continues to advance brain machine interfaces, and it continues to expand, you know, our possibilities. And, what is exciting, I think, is that the, for medicine, the end of the road and when, when we return the function, restores the function, but in engineering, we can continue beyond that.
[00:31:05] And that is very interesting possibility of expanding beyond our natural capabilities. This road may be infinite.
[00:31:12] Russ Altman: What's one thing you want people to walk away from this episode remembering?
[00:31:17] Daniel Palanker: The thing most important is that, we demonstrated that restoration of form vision is possible. Many groups tried, and until now failed to achieve anything better than just flickering lights. And we have shown that if you respect retinal code and preserve it, to ex- to the extent the brain will understand it, you can restore vision. I think this is a big step forward. And from here, I hope it will evolve, you know, further and further.
[00:31:46] Russ Altman: Aside from money, what is the one thing you need to succeed in your research?
[00:31:51] Daniel Palanker: We need industrial partner to bring it to patients. And industrial partner should be interested not only in making money, but in deep understanding of the technology and the will to work and learn and implement this deep tech. This is not trivial. This is not an easy, you know, to find a partner. Fortunately, we have some, but it's not, you know, maybe as smooth as I wanted it to be
[00:32:17] Russ Altman: If all goes well, what does the future look like?
[00:32:20] Daniel Palanker: Well, in terms of vision, I hope that we will deliver this product to the market, with next generation implant 25 microns, which is 20/100 visual acuity without zoom, and with zoom they, will see even better.
[00:32:37] My goal is to bring that to a state of sustainable medical product where it can evolve from there. And I think the threshold is 20/100 acuity because this will help millions of patients. If we bring it over that threshold where it's sustainable, it will have its own life like cochlear implants and will, you know, keep progressing. So that's my threshold kind of for this product.
[00:33:02] Russ Altman: If you were starting over again and you needed to get your degree or certification in a different discipline, what would that be?
[00:33:09] Daniel Palanker: Yeah. You know, I was torn, as I mentioned, between physics and medicine, and it just happened to be that I have chosen physics, but applied it to medicine, and I thought, I think it is the right choice. If you force me to do something else, I would maybe go to neuroscience because I think it's, one of the most exciting fields these days.
[00:33:30] Russ Altman: Thanks to Daniel Palanker. That was the future of retinal implants. Thanks for listening. Please follow the show. That'll make sure you never miss an episode. You'll get these little reminders that we have a new episode that you can listen to.
[00:33:42] Also, don't forget that we have a back catalog with a ton of conversations that are still relevant and lively, and you can spend hours listening to The Future of Everything. Don't forget that I'm available on some social media, such as LinkedIn, Bluesky, Threads, and Mastodon, where I'm @RBAltman or @RussBAltman.
[00:34:01] Also, you can follow Stanford's School of Engineering @StanfordSchoolOfEngineering or @StanfordENG.
