Erez Naaman ADT podcast cover
Episode: 64

Erez Naaman - Digital transformation in diagnostics

Posted on: 25 Aug 2022
Erez Naaman ADT podcast cover

Erez Naaman is the CTO and co-founder of Scopio Labs, a company specializing in hematology that's revolutionizing diagnostics through artificial intelligence and full-field morphology.

In this episode, we discuss the topic of digital transformation in diagnostics, with a special focus on the impact and the future potential of artificial intelligence. We talk more generally about laboratory medicine and the role of diagnostics there before diving deeper into the obvious impacts of COVID and the accelerated digitalization (not to be confused with digitization, which Erez also points out and explains).


Links & mentions:


“Together, I think technology and AI will transform the way we diagnose and we treat in the coming years. And this is really enabling clinical care to become very tailor-made, individualized. But even more than that, it enables the patient to get access to the information and the doctors to make better decisions.” 

Welcome to the Agile Digital Transformation podcast, where we explore different aspects of digital transformation and digital experience with your host, Tim Butara, content and community manager at Agiledrop. 

Tim Butara: Hello, everyone. Thank you for tuning in. Joining me today is Erez Naaman, CTO and cofounder of Scopio Labs, a company specializing in hematology that's streamlining diagnostics through artificial intelligence and full-field imaging. Today we'll be discussing how digital transformation and all the advancements in the field of AI are impacting diagnostics. Welcome, Erez. Thank you for joining us on the show today. It's great having you as our guest. 

Erez Naaman: Hi, Tim. Thank you for having me. I really appreciate it. 

Tim Butara: So, before we dive into the significance of digital transformation in diagnostics and all that, can we first clarify and talk a little bit more about the role of laboratory medicine in patient care? 

Erez Naaman: Yes. So lab medicine is critical and plays a major role in clinical care. It's in charge of providing the objective data for accurate diagnosis, prognosis treatment, monitoring of patients, and that ensures a safe, appropriate and effective clinical decision making. In fact, not many people know, but over 60% of the decisions taken in patient care, both in the hospital setting and outside of it, are accredited to the findings of lab tests. So essentially, how we like to say it is, you can't treat what you can't see, and labs do the work behind the scenes that brings the relevant information to life. 

Tim Butara: I love that phrase, you can't treat what you can’t see. And I suspect that will be even more important as we progress through this interview. So, the next question, obviously, we've just been through COVID, through the pandemic. How has all that transformed the field of diagnostics? 

Erez Naaman: So I think it had a great impact. The COVID pandemic posed an unprecedented challenge for modern healthcare systems. And really, I think we're seeing change that we expected to happen over 10, 15 years even, happening rapidly in two or three. Suddenly everyone around you is able to speak to– in clinical jargon and is aware of lab diagnostics and everything. 

So I think, for example, the healthcare industry really started adopting telehealth services and diagnosing, treating and controlling diseases during this outbreak. The World Health Organization started an initiative called T3 – Test, Treat and Track, which is meant to prevent the spread of the pandemic. And it's put diagnostics in the spotlight. So it's really highlighted an increasing need to deliver fast and quality test results. 

And it's also highlighted the necessity for lab professionals to work remotely. They need to still provide real time, reliable diagnosis and providing results when part of the staff is suddenly sick or is not allowed to come to the lab. And it's also highlighted a need for labs to start collaborating and working together between different areas and different geographies. So it's really changed the way we look at diagnostics in the way things are done. 

Tim Butara: What's the approach here to kind of tackling these issues? So, you know, lab workers having to have the ability to work equally adequately remotely and more, several labs having to work together, how have these transformed throughout the pandemic? 

Erez Naaman: There are many different ways that it's happened and I think it's also different in different places. But some of the lab work obviously requires being physically in the lab. You have to handle samples. But many types of samples either were digital, but were in the past only allowed to be accessed on hospital premise, and some were just not digital. So, for example, the sample of the Scopio deals which were not digital. 

So I think that part of the change is that hospitals are very willing to adopt solutions that enable remote diagnosis where possible, allowing access from, of course, secure access from home or from external facilities. A lot of the change actually happens in the IT world where hospitals just need to be able to open to the cloud and internet access purely. And that sped up a lot of cyber aspects around healthcare and informatics in general. 

Tim Butara: So the main impact of all the accelerated digitalisation, the kind of all round digital transformation has mostly had so far a more kind of basic effect of getting the industry or so diagnostics, healthcare kind of up to speed with other more digitally native industries. So you mentioned one of the most significant things was the move to the cloud, right? 

Erez Naaman: Yeah, I agree that these are mostly revolutions that we're seeing in other industries, but the healthcare industry is naturally want to be careful with adopting change because it literally deals with human lives. And so there's regulation involved. There are processes of making sure that the quality stays up, there are no mistakes involved, and if someone hacks the database with private information of patients, that can be devastating. So there are a lot of aspects around it that are, while they exist in other industries, they are more severe and therefore are taken into deeper account. And the pandemic just sped this process up to start matching the places that have– like the revolutions that happen in other places. 

Tim Butara: Yeah, that makes a lot of sense. I think that was exactly what I was getting at. So, yeah, awesome clarification. So now we're already moving– we just said that it's been more of a basic, getting up to speed, but the next question actually moves a little bit forward from that. So we're going to talk a little bit about AI – artificial intelligence, which has become a bit of a buzzword across pretty much every industry, that includes healthcare. So what are the roles or the applications of AI in this field, so in diagnostics and in laboratory medicine? 

Erez Naaman: So indeed, AI is being worked on across almost scientific disciplines and of course in healthcare, and specifically, it's also changing diagnostic approaches. And I'll give examples from hematology in this discussion, since it's my field, but AI is already entering the market and it's mainly as part of decision support system, meaning the current state of where AI is predominantly is in augmenting, laborious and often tedious tasks by combining the best of both worlds. 

So computers, we say artificial intelligence, but computers have no actual intelligence. They can be trained to quickly process vast amounts of data and extract important information and organize it in ways that a human can never do. Right? A person cannot count 1000 cells repeatedly, maybe not even once. And for a computer, this is a very simple task. And the human brain has an incredible ability to integrate information from various sources, make decisions, understand importance, and it can also show empathy. 

So this combined effort really holds a promise for performing tests faster and more accurately and with less effort and extracting new findings from the information by combining the abilities of each. And that has the promise of better diagnostics than we could ever do before. So, as time passes, I think we will likely also see automated testing coming into play with AI without a person in the loop. But it would require a process of learning to use it wisely, defining clear procedures and developing higher trust in the results. 

And as an example, from hematology, at Scopio, we deal with the peripheral blood smear test, which is a very common test done 600 million times a year across the world. And we've successfully introduced an AI-powered decision support system into this very common and routine blood test, which enhances the time you review and facilitates real time diagnosis and accurate treatment decisions directly from blood. So our AI-powered platform allows experts to review and collaborate and consult from anywhere and at any time, while significantly reducing the turnaround time and the workload in the lab. 

Tim Butara: So this actually ties back to what we said previously about how different labs have to work efficiently together, have to efficiently collaborate. And I assume that this also empowers the specific lab workers of a particular lab, I guess at Scopio or wherever, to kind of be better positioned for this hybrid, remote, fast paced environment. 

Erez Naaman: Right. Our test is naturally digital and so it lends itself very well to what we started kind of naming telehematology, which is a field that didn't actually exist until now, but it's joining a trend that started in other places in the healthcare industry. It's just there were no tools until Scopio to do this. You're very right in your description of this. 

Tim Butara: So the way I see it, also with healthcare, it's been very similar to what other industries have been experiencing. It's mostly been implementing AI so that it can use its own capabilities – so better data management, faster completion of tasks, that would require a lot of time and effort for humans and they wouldn't be able to do it reliably, combining that with the intrinsic skills of humans, of lab workers in this specific sense, to kind of get the best possible result, to kind of enhance the human work through AI. 

But I also assume that in the future we'll probably see more advanced use cases for AI and for digitalization. So what do you predict or expect to have, to happen in the future for diagnostics in this field in general? 

Erez Naaman: So, I think that in the coming years, we're going to see AI radically transforming healthcare. It will empower health care professionals with more digitization and digitalization. So the two are important to distinct because digitization is turning data digital and digitalization is turning a process digital, and that's moving the workflow and really embracing the revolution that's happening. 

So we're going to see that in digitization, digitalization, in automation, improvement of accuracy, new insights from data. And we'll actually make, I think, the clinicians themselves more available to spend their time on the things that they care to do and where their time is most valuable, and spend time with the care team and their patients. So I think AI will impact most aspects of care. It will close gaps in the quality of care based on gender, race, geographic location, financial ability, but it will also create new tests and be able to also utilize the existing knowledge to its fullest potential. 

So it will introduce new levels of quantification as the industry learns how to unlock this new data, provide better actionable insights for better diagnostics. And if it's okay, I can elaborate a little bit on each of these and give some examples of how this will happen. So, platforms will be introduced and also adopted that effectively aggregate data from all patient records and process the data. 

So you will use your imaging information, the patient records, the pathology reports, the lab reports, patient generated information, genomics, et cetera. And this information will all be aggregated and then analyzed together to produce new knowledge, new understanding, new context, and ultimately better decision making. It will also break down decades of entrenched data that sits in silos across hospitals. 

Also, I think we will start seeing how AI enables actually less invasive methods for detection and diagnosis and sometimes even treatment through use of advanced imaging, scanning, diagnosis with less suffering. So for example, with AI, it's been shown already that you can reduce the amount of radiation that is needed in a CT scan. So you can already start seeing how AI will impact things and of course things like what Scopio does, right? AI reducing the time, improving accuracy, and changing the way that medicine is done. 

Apart from that, I think that real time diagnostics will also be involved in continuous monitoring devices. So you'll start looking not just at the test, but the complete history and trends and vectors that are happening in the life of the patient and similar patients. So you can start predicting for the future based on information from the past. 

And like we said before, we talked a bit about remote, so remote diagnostics, I think will be a huge thing and it will break down a lot of barriers. The ability to remotely analyze anywhere without the connection to where the patient is means that the same quality of care can be given to anyone. And I think this connection to expertise, both using the AI and connecting to remote experts who are needed, will really revolutionize things. 

So together, I think technology and AI will transform the way we diagnose and we treat in the coming years. And this is really enabling clinical care to become very tailor-made, individualized, but even more than that, it enables the patient to get access to the information and the doctors to make better decisions. In essence, I believe that they will lead to the healthcare expertise making a real difference in how we see the future of healthcare and ultimately leads to better patient outcomes. 

Tim Butara: It certainly sounds like healthcare is one industry where AI has a lot of potential that's still untapped. And as you just elaborated right now, Erez, hopefully all of the advancements that you were talking about will come to fruition, not at some super indefinite point in the future, but quickly enough so that we can start making use of them. 

I really like the bit about using AI to reduce radiation during a CT scan, that's like something that I would never have expected to hear. So, some really awesome insights in this conversation. Thank you so much. It is so just before we wrap it up, if listeners would like to reach out to you or maybe learn more about you or learn more about Scopio, where can they do that? 

Erez Naaman: You're welcome to go to our website,, and there are methods of contacting us through the website easily and we'll be happy to answer all questions and get back to you. 

Tim Butara: Okay, awesome. Well, thank you again for joining us. Thank you for the great conversation and it will be exciting to see how the field and all the advancements will progress in the future. 

Erez Naaman: Thank you so much for having me. 

Tim Butara: Well, to our listeners, that's all for this episode. Have a great day everyone and stay safe. 

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