[00:01:41] Aleksandra: I am honored to host Michael Grunkin, the CEO of Visiopharm for a follow-up conversation today. In the last episode, we talked about the 20-year perspective of digital pathology that Visiopharm has after being so long in the market. Today, we will discuss the current and potential role of digital pathology in the research diagnostics continuum.
[00:02:03] Hi, Michael, welcome to the podcast again. Great to have you for the second episode together. How are you today?
[00:02:10] Michael: Thank you very much, Aleksandra. And again, thank you very much for the invitation. I’m excited to be here today.
[00:02:17] Aleksandra: The pleasure is mine. One of the early applications of digital pathology was image analysis on IHC stain tissue samples to quantify IHC marker-positive cells for research purposes. And, at the beginning, it was just single markers, brown cells that needed to be quantified. With time, there was more and more markers used, and this application is still super important. But with the regulatory approvals of digital pathology system at the end of the last decade, and we were already laughing about the last decade, which is just a couple of years ago, in our previous conversation, but with this regulatory approval, digital pathology started entering the routine diagnostics. It became the modality for routine diagnostic. And I want to emphasize the word started, because we are surrounded with this, we are in the area, we are in this business, so this is our daily bread. But in the grand scheme of things, digital pathology is just starting if we, for example, compare it to radiology. So I wanted to ask you, how do you see the current and potential future role of digital pathology in routine diagnostics?
[00:03:31] Michael: I think it’s a very important question. I think everyone in this vertical is concerned with that question. And there is no doubt, of course, that routine diagnostics has been the greater vision for the entire digital pathology community since the birth of this new field. And I think probably what everyone understands, digital pathology and computation pathology are intended to deliver on two important aspects, I would say precision and productivity. And I also think that remains the vision. But if you double-click on both of these things, precision and productivity, there is a lot of detail in there that the entire field is learning and still has to learn a lot about. I think if we look at the field, there’s tangible progress on all solution component, but I think we’re all realizing that the adoption remains much slower than we had all expected even 10 or 20 years ago. We have worked for the last 10 years, and probably become one of the leaders here in Northern Europe in diagnostic digital pathology, with more than 75 diagnostic pathology labs that are customers and partners over the last, I would say decade. And that, of course, have given us a front-row seat to really at a deeper level understand what the challenges are for adopters. What are they facing when they are going through this digital transformation, if we call it that? So, let me start by really stating the obvious. The digital transformation of a pathology lab is obviously, and I am stating the obvious here, but it’s much more than just the investment in significant scanning capacity to digitize a full-slide production.
[00:05:37] Aleksandra: It might be obvious for people who already started educating themselves on this journey, but I think for people from the outside, also outside of the pathology lab who are thinking of implementing this modality for a hospital or for an organization, this is not so obvious. So, thanks for mentioning
[00:05:54] Michael: I think you are right because many labs that are standing on the brink of the start of that journey, they quickly realized that it’s also investment in storage, VNA, digital infrastructure, slide management, workflow management, and of course, connectivity to the LIMS. And that’s, we are seeing these new anatomical pathology PACS solutions, if we call them that. And one thing that’s important to remember is also the organizational change management, which is really a mission-critical part of the entire exercise that’s often overlooked, or at least underestimated. now that I mentioned all those things, and the problem, I think today is that the improvements in productivity and precision that’s gained by just going digital or going through that digital transformation, is modest at best. At least, when you look at the peer-reviewed literature, the topic where they’ve tried to look at productivity or precision improvements by just going digital. So this is where image analysis and AI are supposed to come into the picture, and they are coming into the picture. Obviously, there is the demand for image analysis apps that can automate and standardize. And this is really becoming a possibility right now. And we’ve seen really great companies coming with new applications that are both robust and very successful in what they do. And I think everyone in this field would agree with me that the regulatory barriers are pretty high. And I’m not saying that this is wrong, and I think we all believe that patient safety comes first. But still, this is the primary reason that the available, you’d say IVD that are available on digital and computational pathology platforms remain limited. And that also means, unfortunately, that the business case for these large enterprise solutions for digital pathology is challenged, to put it bluntly. And this is why we believe that more targeted solutions is what’s required to create value here now for the diagnostic pathology labs, without having, you could say, to boil the ocean, so to speak. And this is something we’ll be talking a lot about in the very near future.
[00:08:37] Aleksandra: I very much respect you saying that as a vendor, this is an approach that is very much grounded in reality. And I appreciate this point of view, because usually you hear people advertising this as something seamless, and maybe not anymore as seamless, but easier than it is in the end, without pointing out, okay, you need to know what you’re gaining from this. And you mentioned at the beginning, the precision or the increase in efficiency, probably a combination of both, and the combination of different other factors, but it’s not a straightforward value proposition. I very much respect you mentioning that.
[00:09:26] So, thanks for this point of view. I hope it’s going to grow, it’s going to spread. I know it will because we need more precision and we need more efficiency. So, how do you think the spread of digital pathology for reaching diagnostics will affect
[00:09:45] Michael: I think it will require some breakthroughs before it really will have an impact on the routine diagnostic market. And I think maybe a good place to start talking about the breakthroughs. And I understand breakthroughs depends a lot on perspective, and as our perspective is really precision pathology in the entire research diagnostic continuum where we work today. And that means, on one hand, precision pathology for developing of new therapies or discovery and development of new predictive tissue biomarkers. But it also ultimately means effective deployment in routine diagnostics. And I would say that one of the large unmet needs today standardization in the application of tissue diagnostic assays. And standardization is in two areas. It’s in staining, and it’s an interpretation. And if you look at where image analysis and the entire AI field goes today, the focus is really on the interpretation aspect, which is, of course, extremely important when we are looking at increasingly complex tissue biomarkers for companion diagnostics, for example. But the lack of standardization when it comes to management of stain quality is really significant. For some tissue biomarkers, the external quality assessments, organizations like CAP , NordiQC and UK NEQAS, they are still reporting failure rates as high as 30% for routine diagnostic pathology labs in their proficiency testing programs. So over the last several years, we have worked on an entirely new application of AI, which is stain quality management. And we are actually going to release over the next few months, this new service for stain quality measurement management and documentation, we call it Qualitopix. We’ve already talked a little bit about that. And we’ve seen exciting results from the test programs that we’ve been running. And we think this will help pathology labs manage their stain quality, pinpoint problems with assay performance, pinpoint protocol issues, and help problems with instrumentation, things that are all manageable if they’re discovered in a timely fashion and the labs can intervene. And of course, it will also help them with an efficient tool to support accreditation that, of course, have to be compliant with ISO 15189 So I think this standardization aspect is so important to manage before digital pathology really can, I would say unfold its real potential. And until all of these problems are solved, I think that the adoption of enterprise solutions and the full digital transformation will be slow. But once we’ve achieved these things, I also strongly believe and I think that’s where we all want to go, that we can demonstrate a convincing business case for labs that are undergoing this full digital transformation. And of course, there are many ways this can happen and many ways this will happen, but we think that more targeted solutions will be able to accelerate that development.
[00:13:38] Aleksandra: So you say the standardization and targeted solutions, would you agree that these two breakthroughs would help make researchers new discoveries? Or do you have any other things that are important there?
[00:13:55] Michael: I would say that the targeted solution is not even just for research. If you are looking at the digital pathology market as such, I think in most places it’s still stuck in what technology marketeers would call the chasm, which means that we’re really just able to work with the early market, the visionaries, the technology enthusiasts, and really the front runners. But I think that the main market, the pragmatists, they’re still looking very much in this and saying, really want to see a business case, but if the business case is built on us going through the full digital transformation, then the business case is really challenged.
[00:14:43] And this is why we think that even in diagnostics, we can accelerate the digital transformation by providing targeted solutions that allow pathology labs to go digital in an incremental fashion, instead of doing everything at once. And that can be very challenging to a diagnostic pathology lab. And they’re responsible for a significant diagnostic production and, of course, they cannot necessarily risk to disrupt that. So that’s why we think these incremental and targeted solutions will accelerate the general adoption by proving the business case to the pathology labs.
[00:15:30] Aleksandra: Yeah. I’m smiling again, when you say that, because this is the same aspect of being grounded in reality, and doing things in an incremental manner, which is not so sexy when you try to market it, but this is life and life is happening. While you’re implementing digital pathology, you cannot a whole system shut down a pathology lab to implement stuff and troubleshoot. And doing it in an incremental fashion is the way to go if you want to enter, like you said, the main market, the pragmatic people.
[00:16:09] Michael: I think it’s a combination of both things because we have worked for the last 10 years deploying enterprise solutions. As I mentioned, we’ve done that with 75 labs. And I think it’s that close encounter with reality, as you put it very appropriately that have shown us that not everybody is ready for that full digital transformation. Of course, many feel compelled to do that, because most of the operators the digital pathology market are really providers of enterprise solutions, and they need pathology labs to go fully digital. Otherwise, they cannot use an enterprise solution. But there is a middle ground that will help the pathologist labs on that transformation journey and ultimately that will also help providers of enterprise solutions.
[00:17:10] Definitely to provide
[00:17:12] Aleksandra: value. Because to those who go fully digital, you can provide the full value immediately, but if you want to provide value where the value is needed, but where people are not ready yet, then that’s the second model, the more incremental model. So you’ve been there for 20 years. What do you think the trends will be for the next 20 years? What you imagine digital pathology will look like in 20
[00:17:38] Michael: I really think that the next years-
[00:17:40] Aleksandra: Or what you hope for it because-
[00:17:42] Michael: Yeah, maybe, I do think that we will see that vision become a reality. It will happen over the next 10 years. And I think it will happen when we have achieved standardization and when we have built that whole solution, if you will, that help the pathology labs realize they call compelling reason to buy the system. And that’s not just scanners. It’s the ability to really have that seamless implementation, deployment and a sufficiently large diagnostic menu that they can automate a significant part of their workload and they can achieve documented improvements in precision. think we are seeing this, but not going as fast as we hope, but it is happening as we speak.
[00:18:43] Aleksandra: I hope that something happens that will help accelerate it. And by something happens, it’s something like we had recently, the access to deep learning totally changed the landscape. So I hope something that we are not yet aware of is going to enter the scene and that’s going to help accelerate this vision. Thank you so much, Michael, for being my guest again, and I wish you all the best for the 20th anniversary of Visiopharm.
[00:19:11] Thank you so much, Aleksandra. And thank you for inviting me to participate. It’s been a pleasure.
[00:19:17] Always a pleasure. Thank you so much. Bye-bye.
[00:19:21] Michael: Bye.
