00:00:00 · Sebastian Johnson, Neil Daly
[00:00:00] S0: Hello, and welcome back to Scaling Europe show. I'm Sebastian. Today on the show, we've got Neil, founder and CEO of Skin Analytics. How are doing today, Neil? [00:00:07] S1: Very well. Thanks for having me. Really looking forward to having a conversation. [00:00:10] S0: The pleasure is all mine. Thank you for taking the time. To kick off. Maybe for those who don't know you and what you've built, could you give us the the the quick pitch? What is it that you're building? [00:00:21] S1: Yeah. Absolutely. So Skin Analytics is a company that has built AI algorithms that are able to identify malignant, premalignant, and benign skin lesions from an image of that lesion. We take that technology and when... We then embed it into various different health care systems to make more efficient skin cancer pathways that with the goal of trying to make sure that patients get better outcomes, but also make sure that the health system is able to generate savings which it can then reinvest into better care for its populations. [00:00:51] S0: Amazing Mission. It's like a really classic, you know, sort of tech AI for good example. How did you get into this? Like, how did you start building this business and why?
00:00:51 · Sebastian Johnson, Neil Daly
[00:00:51] S0: Amazing Mission. It's like a really classic, you know, sort of tech AI for good example. How did you get into this? Like, how did you start building this business and why? [00:01:02] S1: Well, I was, very naive, is the answer, and, thankfully so, I think. But, it was way back in twenty eleven, twenty twelve. I started the business in January 2012, and I spent most of 2011 kicking around the idea, calling up, every professor of computer science across, the country, trying to get someone to believe that we could build this, this computer system to be able to diagnose skin cancer, and eventually found a professor up in Cambridge, the late Bill Fitzgerald, who, said, yeah. Let's do it. Let's crack on, and I think we can make this work. And that was really the the genesis for the company. But I had previous to that just been absolutely captured by the idea of computer vision systems as they were called back then from an article I'd read, in in some journal. I can't even remember which one these days, but, it really just captured me as a huge opportunity to try and solve one of health care's biggest problems, which is that really to be able to treat people for various diseases, we spend the vast majority of our time speaking to healthy people, trying to pick the needle out of the haystack. And it just felt to me like the perfect place to apply computing technology to try and make that haystack significantly smaller and then allow the health system to focus on getting sick people healthy.
00:01:02 · Neil Daly, Sebastian Johnson
[00:01:02] S1: Well, I was, very naive, is the answer, and, thankfully so, I think. But, it was way back in twenty eleven, twenty twelve. I started the business in January 2012, and I spent most of 2011 kicking around the idea, calling up, every professor of computer science across, the country, trying to get someone to believe that we could build this, this computer system to be able to diagnose skin cancer, and eventually found a professor up in Cambridge, the late Bill Fitzgerald, who, said, yeah. Let's do it. Let's crack on, and I think we can make this work. And that was really the the genesis for the company. But I had previous to that just been absolutely captured by the idea of computer vision systems as they were called back then from an article I'd read, in in some journal. I can't even remember which one these days, but, it really just captured me as a huge opportunity to try and solve one of health care's biggest problems, which is that really to be able to treat people for various diseases, we spend the vast majority of our time speaking to healthy people, trying to pick the needle out of the haystack. And it just felt to me like the perfect place to apply computing technology to try and make that haystack significantly smaller and then allow the health system to focus on getting sick people healthy. [00:02:18] S0: And how has it changed since we've seen this sort of explosion of AI? In many ways, you're very, early trying to use the the algorithm of computer systems before AI really exploded. How did that moment change things for you in the business?
00:02:31 · Neil Daly
[00:02:31] S1: Yeah. I think there's been four waves of AI explosion, if you like, and, the the previous ones have ended a little bit, a little bit sadly. This one feels a little bit different, I would say, and I guess the markets would say as well right now. But, the, the truth is that we were so early on the technology, the capability wasn't there. And so we've been both unfortunate to be that early, but also very fortunate because we've been able to make all the mistakes in building and deploying this technology and figure out how to solve them, which is really the key part of why we've been able to to build something that has so much utility right now is is sort of being there at each of those big jump points as the technology matured, and knowing knowing its limitations and knowing how to build around it with real world data. But what I would say is that that actually we've been very fortunate in the last little while. Each time that AI starts to become something that people are believing in again, we've seen a corresponding jump in their belief in what we're doing go along with that. So, specifically, when ChatGPT exploded on the scene, we had been pushing very hard for hospital systems to adopt our technology and and we're finding it slow going. And immediately, we saw an acceleration as people started to believe in what AI could do and and the power of the technology. And suddenly, it didn't seem so fantastic that you could diagnose skin cancer with these technologies because people were starting to see all the crazy things you could do with these technologies.
00:03:56 · Sebastian Johnson
[00:03:56] S0: That's really interesting. So it's it's sort of like the the market has caught up with where you were in in many ways. Can you talk about, some some of the interesting stuff that's happened recently? Like, I... You know, there's an announcement in June this year about DermZero, which I think was, a real milestone for the company. Can you touch on that?
00:04:13 · Neil Daly
[00:04:13] S1: Yeah. There's been a couple of really big milestones for us in the last little while. I mean, firstly, if... Just to give a little bit of context, it'll make a little bit more sense if I explain. We started the business focusing using a dermoscopic image, it's called. And that's a relatively low cost lens, cross polarized lights, and a magnification that can clip onto a smartphone, and you can then capture a high quality image. And we focused on that because that was the gold standard of what dermatologists would be doing, and there's just more information in that image to be able to identify the difference between malignancy and and very complex benign lesions. And so that formed the basis of our business for for a good amount of time. But all the while we while we were doing this, we're also collecting images from just the smartphone and constantly comparing, can we get the performance from just a smartphone close to the dermatoscope or the dermatoscope depending on which part of the world you're in, and always finding that there was a a gap that was that was huge and not sort of acceptable in clinical practice. So the first thing that we achieved, was that we managed to get a European clearance for the dermoscopic version of what we have, which allowed us to be able to sell our technology into different European markets as a decision support tool. And that was something that we decided we weren't gonna prioritize as a business. We're gonna focus on on what we're doing in The UK. And then we got to an autonomous level where the AI was allowed to make the decision with the dermatoscope on its own without a clinician in the loop, and that really accelerated the things that we could do in The UK, and we started to look again at Europe. And then probably the most exciting step was one that happened just recently as you you mentioned. We we launched it in May, and that was that we were actually able to make a huge technical breakthrough to get the smart only version of the diagnostic tool to work at an incredibly high level. And so we now have regulatory clearance across the entirety of Europe to turn every single smartphone or the vast majority of smartphones into a diagnostic tool that's allowed to run autonomously without a clinician in the loop to try and find and rule out cancer across, the entire European population.