Diaceutics PLC (AIM:DXRX)

CMD 2021

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Jun 16, 2021

Hello, everyone, and welcome to Diacetics Capital Markets Day. My name is Deborah Davis. I'm Non Executive Chair of Diacetics. In the next couple of hours, we're looking forward to sharing with you the opportunity that we see for Diacetics and our DXRx platform to play a pivotal role in the rapidly growing industry of precision medicine. In the next couple of hours, we will cover a number of things, I'm joined today by 4 members of our Board and Executive team, Peter Keeling, Ryan Keeling, Susano Mengstad and Philip White. Our agenda for today will start with Peter providing an overview of diasthetics and the precision medicine diagnostic landscape. He'll be followed by Ryan, who will take us through a series of demonstrations of DxRx capability. We're delighted to be joined by 3 experts from the Diagnostics and Precision Medicine World. And Susanna will introduce our special guest when she facilitates the panel discussion before opening the floor to questions. If you do have questions on the DxRx platform or the topics raised during the panel discussion, Then please raise them here in this first Q and A session when Ryan and the experts will be present. In the second part of our presentation today, Peter and Philip will take us through the strategy, the business model and the key performance indicators we will use to measure our progress. We'll then open the floor up for questions to Peter and Philip on these topics. Of course, while there are just 5 of us here from the business today, We do have a far larger team behind the scenes with over 100 staff across 3 continents, together with an experienced Board an expert advisory panel, all helping to drive the business forward. Now I was asked in this introduction to provide some insight into why I joined Futics as chair in January of this year. Essentially, there are 5 key reasons I was drawn to this company. Fundamentally, it has a compelling purpose to get every patient the precision medicine they deserve. It's developed a well engineered core platform and data capability that can transform the diagnostics commercialization industry. There's a strong leadership team in place led by Peter. It already has an impressive client base comprising many of the world's largest pharma companies and is operating within this super exciting growth market of precision medicine. I also thought that I had some experience that could be additive to the team and to the company. I spent the last few years of my full time executive career in global leadership roles in the pure play Internet platform businesses, PayPal and eBay. I've experienced the growth and the complexities of developing platform ecosystems and the need for compelling propositions that engage and delight platform participants. I've also spent my entire career in technology related businesses, Spanning Software Telecoms Technology Based Data and Systems Solutions, which required a well versed understanding of scaling platform businesses, developing data assets and data insights, building strategic product roadmaps, evaluating and implementing software business models, including subscription and recurring revenues and managing essential human capital across the globe. So I'm sure you're asking how should diacetics approach this massive opportunity and take itself forward? I'm reminded of the time when I was at PayPal some 8 years ago now, when it had a market cap of circa $3,000,000,000 Today, that's over $300,000,000,000 The company was enjoying high double digit growth, was faced with a huge raft of opportunities, new products, new geographies, different customer types and the ability to enter adjacent markets. It's very easy for us to become distracted and dilute our efforts and end up being suboptimal in many areas. Our approach to avoid that was to ruthlessly prioritize and focus our relatively constrained resources on the critical few areas that were fundamental to our success, While experimenting and piloting in areas that would allow us to test and learn, but not detract from the delivery of our key priorities. I control parallels to our business. We launched our DXRx platform on time and on budget. Our key performance indicators are tracking ahead of plan today. We have a solid runway upon which we can build. We still have significant scope to deepen our relationships with our current clients and increase customer lifetime value and also to attract new clients to the network and the propositions that are already launched. We then have more to do to build out the ecosystem to attract new participants with propositions that will engage and delight them and that will stimulate that flywheel effect. This challenge reminds me of eBay's platform ecosystem as we transition from a consumer to consumer auction platform to face off against the competition by opening the platform to business sellers, including large scale merchants, and then balancing engagement, monetization and customer satisfaction across all platforms, such and customer satisfaction across all platforms such that we could benefit from that virtuous circle of buyers accessing long tail inventory from a full range of sellers, thereby attracting more buyers and in turn attracting more sellers. I've moved SORUS Tech our share price from its lowest point to a 500% increase over 5 years. I think the takeaway is that at this stage of our business, we plan to employ our resources to build critical mass at a strong base from which to expand. We believe we have all the right ingredients to accomplish this. And I hope that by the end of this session today, you'll believe in our ability to deliver I want to come on this exciting journey with us. So without further ado, I'd now like to hand over to our Founder and CEO, Peter Keeling, who will start today with an overview of diastutics and the diagnostic landscape. Thanks, Peter, and please all enjoy. Thank you very much indeed, Deborah, and indeed welcome all of you to today's meeting. And as Deborah suggested in the agenda, I wanted to use this next session to provide an overview of Diacytics and our business model. I'm aware that most of you joining us today are existing shareholders, but our audience also consists of followers of what I would describe as the diastolic So I want to provide an up to date perspective on our business as it sits today, whilst refreshing on the key investor economics underpinning our business. As Deborah showed in her earlier slide, our goal is eliminating the many diagnostic hurdles to precision medicine for treatments. This is a largely unmet need within the precision medicine ecosystem. And to deliver on this, Diastudix is in its 1st year rolling out a purpose built diagnostic commercialization platform. Development of this platform and the proprietary business method from which it is based It's the endeavor of a decade of on the job experience with the world's leading pharma companies and laboratories. A significant part of today's presentation will be given over to demonstrating our platform at work. And subsequently Expert comments from Peter Hone, Head of Commercial Strategy at J and J, Professor of Prunari's Head and Department of the Pathology and Laboratory Medicine at the University of Milan. I'm from Avi Kulkarni, Senior VP and Head of Life Sciences R and D at Cognizant. As you can see on this slide, the 8 plus of time invested as a first mover dedicated to precision medicine Has enabled us to understand and design a method to address a significant diagnostic problem and then use technology to convert what Was otherwise a 50% gross margin consulting business pre IPO into a high growth, high margin, high-tech enabled business. Critically, we have understood the role which laboratory is playing as the change agents of diagnostic practice in the frontline of precision medicine. We've ensured that our platform not only delivers a specialized diagnostic commercialization solution to our pharma clients, It includes a unique way to harness the collaboration of a globally distributed laboratory network. In fact, Today we hold data on over 11,000 laboratories across the globe. And via our work have selected 2,500 of those labs to incorporate into what we believe will be the optimal launch network for precision testing. And our platform adoption can now take advantage of our year on year track the most important companies advancing precision medicine. Today precision medicine itself is a bit like the electrification of the car. It's an unstoppable force to change the way that we are treating patients. The metrics speak for themselves. Only 10 years ago, There was not one precision drug in the world's top 10 drugs. But as we entered into the 2020s, that had already changed, Fueling a $60,000,000,000 market that no one was calling a niche any longer, but it is to the future where the most important message of this slide lies. We can clearly identify almost 500 drugs already within declines where a drug will be highly dependent upon a diagnostic ecosystem. Put that in perspective, in 2020, Diastatix worked on 53 therapy brands. In front of us, therefore, is a 10 fold lift in opportunity. And that is within those same clients with whom we have invested so heavily to build trust and confidence. For the pharma industry, many of these drugs will come to market faster and cheaper than the one size fits all drug they replace. Frankly, The economics driving precision medicine today are now highly compelling. However, the headlines surrounding precision medicine deservedly speak The success of the pharmaceutical industry as it transforms to precision medicine. However, underneath the surface lies a significant fissure In the precision medicine business model, namely that the diagnostic marketplace is not fit for purpose here. In fact, It operates in a fundamentally different set of market principles. It's usually siloed, it's slow to change, and economically, it's the poor relation at the table, earning less than 3% of the global risk of the drug market enables, which is why we call it broken. The depressing issue for pharma launch teams is that that same broken diagnostic ecosystem means that they are losing up to 50% of patients In the first and critical years of launch. As many of you know, our commercial pharma team's success is measured on speed to peak sales. And in an increasingly competitive pharma marketplace, the 1st 18 months are critical. The 1st 36 months determine the lifetime success of that drug. But if that same drug is dependent upon a diagnostic, which like the tortoise is really only getting going after 36 months, the lag on treatment is profound. In truth, our decade plus of experience has helped us here to 1, understand what the real hurdles are at a lab level and 2, Build a commercialization method which can eliminate them. In many ways, the simplest of slide is probably the most important one in this deck. It calls out the real world hurdles diagnostics face as they commercialize. And they span from the test not even being asked for by the doctor, all the way around all the way to the turnaround time on the test taking too long before the doctor needs to make a treatment decision. Sadly, the complexity is considerable here. As each biomarker in each market, in each disease will have a different mix of hurdles. There is simply no one size fits all solution to a broken diagnostic ecosystem entrenched in practice over 50 years. However, our experience and our data have combined to allow us to predict and measure with significant accuracy the loss of patients and revenue in any new drug launch dependent upon overcoming these 6 hurdles. As you might imagine, When you get this right or wrong, the return on investment impact to pharma is stunning. We were the 1st external agency to call this out way back in 2010, When we ourselves reverse modeled the patient leakage and loss of revenue to Herceptin, then called the poster challenge for precision medicine. Experts were already calling out on the front page of The Times the profound patient impact in breast cancer of a broken diagnostic the ecosystem. But our analysis showed that with only a 10% reduction in the hurdles, we could deliver a $3,000,000,000 gain For the lifetime revenues for that drug. Anecdotally, we did of course speak to our friends at Roche before we published this. However, they told us that our numbers were wrong. They had done a separation and their estimate was the loss was closer to $7,000,000,000 We continue to update the investment impact on key therapies of fixing diagnostic ecosystem. You can see here on the slide That we continue to see smart investment will eliminate a lot of the patient leakage and loss of revenue, which for the brands mentioned here Could be worth up to $8,000,000,000 per year on those products alone. But what is different today for Diastidics Is that now we're no longer just pointing out to our clients the predicted loss of revenue, but rather we're showing them how we can take $1 of their drug launch budget and via our platform turn it into $30 to $60 more treatment revenues and to do that from multiple therapies at the same time. So at this juncture, I'm going to hand over to Ryan to showcase the DXRx platform through the lens of 3 use examples. And he will introduce a high level explanation of the model underpinning the platform. And I will chat again to you later. Good afternoon. My name is Ryan Keeling. I am Chief Innovation Officer for Diastudics. And my intention today is to walk you through our DxRx platform and demo some of the capabilities Of the platform as it exists today. I wanted to start by walking through this schematic How we think about the data flow, the network effects and indeed the revenue cycle within the platform. DxRx provides digital services that streamline the commercialization of diagnostics. That's the primary reason why a pharmaceutical customer would come to use this platform because they are ultimately Wanting to commercialize a diagnostic, typically one that identifies patients eligible for a therapeutic treatment. User interaction on platform generates data. And the data When it's combined across stakeholders, it inherits significant value. This value is realized Through market analytics services, again provided on the platform and the more analysis of the market We provide the more investment in platform services are acquired. So there's a network effect here That platform activity generates data. That data helps us understand what's going on in the market and we feed that back to our customers To ultimately require them to invest more into the market. I want to show you that in action through 3 different use cases. The first is with a pharmaceutical client who wanted to build a lab network for a new biomarker in breast cancer. The second is a client in the United States who wanted to optimize their sales force Using some of our testing data to do this. And the last is again in the United States where we identified through our market data A particular biomarker test that was being performed in a suboptimal way. The first use case focuses on the 3rd barrier. You heard Peter talk earlier about the different barriers that we focus on trying to remove through the DXRx platform. And this one is focused on testing not being offered by the preferred lab. And what we wanted to do here was enable our pharma client To have a lab network available at the launch of their drug, which would ensure patients got tested. So So here's our scenario. It was a top five pharma. They were first to market launching a new targeted therapy In advanced breast cancer, the therapy is targeting a subset of these breast cancer patients Identifiable through the results of a new biomarker test called PIK3CA. And remember, the pharma company Needs to make that test available because the test is in the label of the therapeutic and the physician must test Before putting patient on treatment. This company has 18 months on market before their competitors arrive and therefore are keen to get a head start and not have the diagnostic slowdown adoption of the therapeutic. This biomarker PIK3CA is not widely available nor routinely tested for in breast cancer. It is in other therapeutic areas, But it's novel in breast cancer and the pharma company fears lack of access to testing will impact therapeutic sales. So I'm going to move from here to our platform. I'll show you what this use case looks like in reality. So I've logged into the platform now. And this is typically the screen that our clients would see when they log in. And the first thing this customer wanted to do and we enabled them to do was to get some initial messaging Out to the lab ecosystem around this new biomarker. So this particular client worked with us to create some messaging. We use our lab broadcast capability and we basically created for them a broadcast That was sent out to the entire network. Remember our network here has over 2,000 laboratories, multiple of that in terms of actual healthcare professionals working within the lab and we're sending that message out at the click of a button to potentially thousands of stakeholders. So through the magic of the internet, I've been able to populate this message for us. And you can see here the type of information that was relevant. And this is a general message, Non branded that will be sent out to the labs. PIK3CA mutation testing is critical components, starting to build the clinical awareness and understanding Of the biomarker, a description so the labs can understand the importance, 40% of patients, HR positive patients Our PIK3CA mutated, that's a significant thing for the labs to understand because this is likely to be highly adopted by physicians. And then there's more technical information. We talk about the particular gene coverage, etcetera, that is needed. We talk about some of the gold standard testing that's available. Again, Technical information the lab needs to know in order to provide a testing service to its physicians. This is step 1 In helping the laboratories to get up and running with testing, let's first of all tell them about the test. And as I said previously, This is the first of its kind mechanism in order to push that message out to labs. Previously, you'd have to put boots on the ground, have reps, MSLs, etcetera, calling on the labs to deliver these sorts of messages. So when I click next step here, Ultimately, what's happening is that message would get sent out to all of the laboratories in our network. You'll see here the 53 different countries where we have a lab partner presence. And if I go and look at any countries in Norway, for instance, You'll see the list of laboratories. We have 13 labs in Norway, a mix of academic hospitals, public health hospitals. These are the laboratories that are testing breast cancer today. They've just received a message to say PIK3CA is coming. It's on your horizon. Let's start to think about it. Now that we've sent that message out to our network, The next thing we want to do with our client is to enable them to build the optimized lab network For the launch of this drug, they don't need every single lab offering the test, but they do need the right labs To at least understand what to do whenever a physician requests PIK3CA testing for advanced breast cancer. So we worked in multiple countries here, but for today, we're just going to focus on Spain. And what we provided was The current understanding based on the platform data of who is providing testing In breast cancer in Spain. So I'm just going to go here and I'm going to do a query on our data for PIK3CA testing In BRASS in Spain, and I want to look very recently, let's look and see who's been doing it over the last 18 months. So what I get back here is what we call a lab mapping. And that lab mapping has a list of laboratories in Spain performing breast cancer testing. Totally, we have visibility over here over 1700 patients. That would get bigger if we increase the timeframe and the biomarker. But We can see straight away some of the laboratories on whether they currently provide PIK3CA testing. So here you have the top lab in Spain for breast cancer testing based on its market share. This lab has 21% of the market, But Jet doesn't do PIK3CA testing. There's no assay details available. If we go down and look, for instance, at Waldebron, Barcelona, A significant lab, 4th of the list, 12%. They already do have a PIK3CA test Using Thermo Fisher Oncomind focused assay, but it's validated for lung. It's still a conversation we can have with them to validate for breast. That's a normal thing for them to do. They may have already done it, but we can now start to piece together with the client Based on all of this sort of information, the biomarker that the lab tests for, the method, the specimen types, the turnaround time, Sensitivity of the assay, the reporting format, all of those things that need to be optimized, we have that data already locked in For these labs, so that we can basically design a network that is going to be up and running from day 1. And we know, for instance, that this lab in Girona doesn't have an assay, but we want to make sure that they are sending out to Valdebron in Barcelona, probably a likely thing for them to do. This lab would have to work with in order to get testing up and running. Let's go and look at how we might want to do that. So once we have selected those laboratories, remember, they are on the DxRx network. We've already recruited them. We've already done the heavy lift for the pharma client. We're not going out to start a conversation from scratch. They're there. That's the advantage of using us Because we've built all of this ahead of time and these labs are here for the sole purpose of being engaged in a program like this one To bring on a new biomarker test. So it's usually something they're very willing to do. And there are advantages for them. There's a value proposition to Getting that head start on the biomarker. So we bring them into a location like this. This is not closed off to the rest of the network. We would have our labs just in Spain or in this instance, we actually combined all the countries so that there was a cross pollination Across the different labs, but we can work with them with our pharma client, with the laboratories in a collaborative way To bring on the biomarker test in time for launch. And this area basically has ways for us to communicate with the labs. We created some events around this. They were virtual at the time, various tasks, and we invite different partners in to help the labs Bring on that new biomarker in a timely way. The last piece of this program Once we got the network up and running was to monitor that over time. And we use our lab monitor tool To basically, again, keep a watching brief on the laboratories as their assay got developed, As they brought in a new kit and verified it, etcetera, the data was updated here. So at any one point in time, we could See the information coming in from the lab. And then of particular interest to the customer is we're enabling them To start to track the volume of testing through that lab. So we have our lab here, our histopathology lab, And you can see the different testing, but you can see then through the different quarters of 2020, how their breast cancer disease volume Started to build and indeed we can narrow that down specifically to PIK3CA, so the pharma client can start to see Where there's some ROI for that test in that particular lab. Again, information that's not available Easily today, but information that is procured through this lab engaging in the platform, receiving the services That it gets through participating in the PIK3CA Global Lab Network. And this is the data, the exhaust data from that interaction. So to summarize what we've done here, we worked with a top 5 global pharma company To launch a new diagnostic into European markets over the course of 5 months, we first broadcast a message in thousands of labs To immediately bolster the understanding of PIK3CA testing in those markets, We've selected a number of those labs to participate in the lab network. We've got them up and running with testing. And then we have subscribed them to a lab monitor service. So that over time, we monitor the data and overall performance of those labs, Alerting our former client if one of those labs drops out of optimal service. The next use case Is focused on sales force optimization and providing data to former sales force To allow them to have a more optimized approach to targeting their physician audience. This use case is based on a U. S. Client And we're going to focus on the first barrier in our framework, which is test not requested. Typically, the starting point To investigate that is with a physician. So our scenario, with a top ten pharma, they launched last year a therapeutic in lung cancer targeting EGFR Exelon 20 mutations. EGFR targeted therapies are not new. We saw the first one around 2,009, but EGFR Exelon 20 is new. There was unmet need there and we have recently seen new therapeutics coming to market targeting This particular mutation. The therapy is targeting a subset of metastatic lung patients and that have this EGFR Exelon 20 mutation. Lung cancer is a highly competitive market. There are many companies competing to convince an oncologist To prescribe therapies, you have competition from other EGFR therapies, other biomarker targeted Immunotherapies, etcetera. So very dynamic, very competitive, and anything that can be leveraged to try to be More targeted, more specific, more timely is of extreme value and interest to our pharma customers. This particular company wants to use our data to target its sales efforts by using a data enabled strategy To only target oncologists who are currently testing for EGFR Exon twenty. So what was the solution that we provided? This pharma company leveraged DxRx data analytics tools to provide its sales force for weekly data On the testing habits of physicians. The following DxRx services were provided, our physician mapping, Where we provided 18 months of baseline data on the testing and laboratory interactions of some 24,000 physicians. And then we provided a subscription to our patient signal service where we provide weekly alerts providing anonymized positive EGFR patients utilizing data from our DXRxLAB network. So this company Availed of a data subscription and the current project duration is 24 months. As before, I'm now going to jump out of here And show you what this looks like on the platform. So we've clicked on our physician mapping tool, and I'm going to select the subscription available to this customer. Customer can have many subscriptions. And then I'm going to select the disease for this particular program. And here we have non small cell lung cancer. We have some options. We can select the overall disease, An active cohort or a metastatic cohort. And there's significant difference between each of these. And actually, I'm going to take a moment now just to explain what is going on behind this, because ultimately what these are doing are reading from our Diagnostic Deductive Pathways. And if I jump out and show you a quick slide on this, we have taken Our data, effectively our raw data, we've analyzed the coding, the diagnosis, the procedures, the treatments, The lab data matched it all together and ultimately developed AI algorithms That are, transforming that data into understandable and recognizable disease pathways. And we use expert labeling and standardization of that data on DxRx to allow Our clients to identify the best possible testing journey or as I say diagnostic pathway for patients. And through that labeling, we can get to very specific disease courts. Again, that's a really crucial thing for our clients. They don't just want to target a disease very broadly. They want to get very specific On the types of patients and our data can support that, but you need to build one of these pathways for each different disease. And that then enables the real world business application for this data. The raw data has value, but until you apply The AI and ML on top of it to be able to read that data and deduce What's going on? Remember, our data continues to grow day on day. We've mapped 54% of it so far and we've created DDPs for 49 diseases. So we go back here, you'll see the diseases we have mapped and we're adding to this all the time. But for today, we're going to focus on Non small cell lung cancer metastatic, and we're going to look at EGFR testing. I'm going to pull in my 18 months. So the data is loaded now. And what we have pulled back here are Data on the testing and treating behavior of some 23,000 590 of physicians who have been managing non small cell lung cancer metastatic patients over this time period. And you'll see this list here. There's 131,000 patients in total represented here. And that is a very high percentage, approximately 65% of the overall metastatic lung cancer population in the U. S. Over this time, so very highly representative and potentially highly insightful for the customer. So what have we got here? Start with Looking at row 1, we have a physician identifier. This is their public identifier, their MPI. We know the hospital that that physician is associated with. This is Moffett Cancer Center in Tampa, Florida. And if we go to the right, we can get additional information about the physician. But really what we want to know is how much testing is this physician doing? So this 2 90 patients This time quite prolific in terms of end of patients. And what is great news is that 289 of those patients were tested For EGFR, we should expect that. It's in the guidelines. And for metastatic lung cancer patients, all of them, if possible, Should be getting an EGFR mutation test. Other oncologists, they're not all testing to the same rates. Some were only testing a quarter of their patients, Some half, some 2 thirds, but there is variability here. And ultimately what we're saying to our Pharma client is for now while you have the resources available to you that you do focus on those physicians who are Testing for your EGFR biomarker, a high percentage of their patients. So we can start to segment this And rank them based on let's take a cut of the 23,598 patients Who are testing 70% and above. And we can use our tools here to basically filter and shape this data So that we get a targeted list of maybe 2,000 physicians who are testing and treating a high percentage of their patients. That's the lower hanging fruit and a bigger opportunity for this company to go after. In time, we can look at how we convert Some of the newer testers, the ones with a lower testing rate to test more and that's We can do that through education, awareness. We're building tools to help do that. But for now, these are the guys who are likely Managing your patients today, make sure you're out there talking to them about your therapeutic. I remind us that all the data within DxRx is Anonymized data, it's HIPAA compliant, GDPR compliant. The information you see about physicians and in a moment about patients Is a liable information that has been passed through an expert determination that gives us the ability To spread to our customers, as we go beyond the physician, we can actually get now to a patient level where we can Not just see which patients got tested with an exon 20 mutation test, but actually those Who are positive for the mutation. And that's the data I'd like to show you now. Now I'm actually seeing our patient level data. So I've gone from physician level to patient level. And each row here represents a test performed on a patient. You'll see multiple rules for some patients who got multiple tests. So here we have here an 80 a plus year old male from Florida. Obviously, this is anonymized and we have to group by age, etcetera. We have a male who had a mass on their left gluteal. They were diagnosed with non small cell lung cancer. We can move across here and see a lot of valuable information about this patient from the physician who ordered the test I'm just managing that patient. But all I'm really interested in is those who got an EGFR test. So now I have sorted my patients and filtered out those who didn't get EGFR. And I'm not just the patients who have an EGFR test. And again, I can go further than this and say, Actually, I'm only interested in those who got an EGFR exon 20 and where they were positive. So if we scroll down through these patients, Just looking for an HFR exon 20. You'll see, okay, there we have one. We have a patient test of HFR exon 20 P768I mutation, we scroll over, we'll see this patient was a 60 to 69 year old female from Arkansas, Non small cell lung cancer or the right upper lung nodule. And we can see the physician, Etcetera who managed that patient. Now they have an opportunity to engage with a physician, not just knowing That they are managing and treating non small cell lung cancer patients, not just knowing that they test those patients Free Jafar, but actually knowing that in the last week they had a patient who was positive. They don't know anything about that patient, other than the age and some high level information like we just showed you. But crucially, There could be a timing there where the sales rep calls on the physician just as they are making decision around the therapeutic And a timely education and understanding of the drug efficacy can be very useful. Remember, one of these patients Going on that therapy could be $100,000 plus for the pharma company. So every patient Going on treatment is a big deal. So to summarize then what we've done here is we've taken a very congested market, EGFR in particular and allowed our pharma company to leverage the sales resources that it has In a very targeted way, first of all, we benchmark all of their physicians to identify those who are most likely To be seeing patients that are positive for EGFRx120. And then we've gone a step further and provided weekly updates to that data to say This physician has just seen a positive patient and is therefore right place, right time for some targeted education around your therapeutic And a higher likelihood that you'll be able to convert a patient onto drug. This brings me to our 3rd and final case study for today, Where we're looking at best in class test quality implementation in the U. S. For a biomarker called NTRK. And this is specific to our Barrier 4. So our scenario, again, top 10 pharma There's a 3rd year market with a pan cancer therapy targeting NTRK gene fusions. Pan cancer, relatively novel, Not a specific type of cancer, but all cancers, if they are able to detect an NTRK gene fusion. Therapy is very rare in most adult cancers. You may need to test 1,000 patients to find one positive. So it's imperative that NTRK resides alongside other biomarkers that are more prevalent on next generation sequencing panels That are typically performed now in oncology. And therefore, if you're testing for a multitude of biomarkers at once, While NTRAC may not be your focus because it's so rare, if it's present, then there is a positive result Can go back to the physician. And the company that we're working for wants to assess the ability of laboratories to detect and successfully report a positive NTRK gene fusion. So what's the solution we provided? The pharma company leveraged DxRx data analytics tools To gain an understanding of laboratories that are able to detect and interact gene fusion, the following services were leveraged. We provided a lab validation service alongside our partner, Cericare. We'll talk about that in a moment. But effectively, we sent out samples That had a known NTRK gene fusion to these NGS testing labs to assess their ability to detect diffusion. We then used our lab monitor tool. The labs came onto DxRx, provided the results Of their validation and we then presented that data back to the pharma company. So the first thing I wanted to touch on here is As part of the XRx, we have a rich partner framework and we partnered with this company, Ceracare, who have a rich toolkit As it pertains to manufactured clinical samples that can be sent out to laboratories In order to assess the capabilities of their tests, this is one of the many uses. And Cericare have And NTRK Fusion sample material that we use for this particular program working alongside them in the United States. So the samples were sent out to the labs and the labs performed testing and they came out to DxRx to provide that Test results back to us, which we then leveraged our lab monitoring service to Help the pharma company interpret the data. So as we look at our lab monitor tool, we're now showing all of the labs in the U. S. We perform next generation sequencing panels and we are able to provide a View of each of these labs to the pharma company so they can understand, does that lab offer a test that detects NTRK fusion? And then we provided some custom analytics to the pharma to really understand the capabilities at a lab level And indeed, how they performed whenever they tested the sample sent out by Cetera Care. And you'll see in the analysis here, Some labs performed well, others last well. And it sets up an opportunity for the pharma company to then We engage with the laboratories. They can do that through DxRx as many of these labs on boarded as part of this program Or they can do it offline if that's a choice they make. Obviously, it's preferential for us to do it through DxRx. We're currently in discussions with this pharma company as to the next steps. So that brings us to the end Of our 3rd use case today. And if you allow me one more moment, I just want to summarize what I feel DxRx brings to the market. It's an outsourced solution. Pharma can outsource their entire DX commercialization to diastolic using DXRx With the services we build today and the continued services we build going forward. It's digital. Post COVID-nineteen in an era of rapidly accelerated drug development and commercialization, DxRx Technology provides a Digital solution, which can meet this market need. Scalable, the number of new precision medicine therapies is increasing exponentially. The complexity is increasing. DxRx can provide diastolic with a scale to deliver on that growth. It's a multi sided marketplace. You've seen for instance CeraCare and other lab partners. We bring all these key stakeholders together In one commercialization supply chain to create an enablement for collaboration and launching of these tests. And it's data, Rich. If anything comes across from today, I hope you can see how the combination of the platform generated exhaust data, The DDPs on the world's largest precision medicine focused lab network offers best in class insights to pharma's key markets. Thank you for your time today. I'd now like to pass to my colleague, Susanna Monkstead, who will walk us through our Q and A, And I will join her there shortly. Thank you. Thank you, Ryan. Thank you for walking us through some powerful use cases For the DEXRx platform. I'll invite you back to join our Q and A session shortly. But initially, allow me to introduce myself. My name is Susana Monstert, and I am the Chief Precision Officer at Dysutix. And it's likely a title you might not be very familiar with. Basically, I'm leading a team of experts responsible for helping clients understand the critical relationship and the dependency between Testing and treatment using the DXRx platform. I joined Dysiotix after spending years in the pharmaceutical and diagnostic industry, working with precision medicine in various commercial roles. Today, I'm very delighted to host a panel session with 3 strong professionals With working experience of the issues of precision medicine and the interface of diagnostics. We have representation from pharma, Peter Horn, Head of Commercial Strategy at Johnson and Johnson, with a long and diverse career in precision diagnostics and and whom we've had the privilege to work with over many years. 2nd, Professor Plumery, Head of Department of Pathology And laboratory medicine at the University of Milan. And he's a leader within the laboratory in Europe. He has a passion for establishing a better connection between the various stakeholders in the diagnostic ecosystem. And Professor Brunner is also an early laboratory partner on the DXRx platform. And last but not the least, we have Avi Kulkarni, Senior Vice President and Head of Life Sciences R&D at Cognizant, a NASDAQ 100 Consultancy Company. Army have in various consultant roles observed firsthand the trajectory of precision medicine from its early days in the mid-90s. And he understands from a pan industry perspective why efficient drug diagnostic commercialization remains a challenge. We also head strategy advisory board for diastutics and has been influential in helping design DxRx Gentlemen, thank you very much for joining us today and for sharing your valuable insights. Peter, I would like to start with you. Could you please share with us some perspectives Of the hurdles you see presented when launching a new therapy alongside a novel diagnostic? Sure, absolutely. I think, first of all, thank you very much for the opportunity to join today. And I can build upon Some of the comments that both Peter and Ryan said in their presentations. If you think about this growth of Precision Medicine Companion Diagnostics, it really is a significant change within the pharma organization. Our commercial models obviously have been set up to really focus on physicians and changing physician behavior. But for companion diagnostics, you really need to think about what happens In the back end, and for us, if we have a companion diagnostic launch, there is a significant opportunity to lose Patients who would be eligible for our therapies. I can maybe build upon one recent example and it's in the EGFR class, An exon 20 product that we launched recently. We did an analysis based on support and data from Diastudics This showed if we did nothing in the lab world, in the diagnostic testing world, we would lose up to 40% of eligible patients So if we did everything else right, we would miss 40% of our patients. That's because even though testing for eGFR is high, it wasn't As Ryan said, but also we know a lot of labs were not testing for the exon 20 component of EGFR. So that by itself is a significant barrier that we needed to address and that is for every single companion diagnostic launch that we have. I think the other thing that's really important to understand is this notion of seamless access to testing. Our world is a competitive one. And if we present a copy for our physicians and our pay are problematic and they may not want to use our therapy the next time. So it's not only enough that our physicians and patients can get access to it, to a new companion diagnostic, But that is done in a way that doesn't present hurdles or barriers to make that experience as easy and seamless as possible So that it becomes embedded into their practice and becomes routine. So those are barriers that we're facing when we go launch a new diagnostic. And as I think you've said, we've worked with and partnered with Diastudix over the years to help, first of all, understand those barriers And to put strategies to commercial plans in place to address them. Thank you, Peter. And in your experience, Is there a particular area or hurdle that you have experienced That have learned here is a place for you to hone in or to zone in. If you think about Peter's comments about the growth of companion diagnostics and precision medicine, the more that Then these practices are already embedded. As a pharmaceutical company, it would be highly unlikely for us to come in and change how a particular physician or provider group Does their testing. So how that testing is done is what it's also a bit of a black hole for pharmaceutical companies. There are a million labs out there. They all have little different protocols and methodologies. And to understand what they're doing and how that could impact our drug is critical. So that's really the most in piece is really understanding what labs are doing, What the potential misses, right, so what their practices are and how we may potentially miss patients based on those practices, But maybe even more critically, how to change their practices in an efficient and timely way. And as Peter said, the launch It becomes self perpetuating. If you don't have a successful launch, you lose investment in that particular brand and you never it's really difficult to recover. So to be able to be ahead of that and work with labs early on to understand how they can change to support your drug And what you need to do to help support that change is really critical. Thank you, Peter. And that your reflections here on the seamless testing In the lab that naturally leads me on to my next question for Professor Prunnery. And in many ways, I will ask You have the same question, but obviously to look at it with your pathology lab lens. So, Professor, when you need to introduce a new test related to a drug What are your considerations and the challenges you may face? Thank you for these questions. The answer is not that easy because, of course, as you know, there are a couple of You know, hurdles that you must overcome before introducing a new test in your lab. I would say that we could divide this This is obviously in 3 main sections. The first is organizational. Of course, you have to get an analysis of the costs, Including reagents and personnel, personnel is particularly important nowadays Because the figures of professionals we are working with, they are changing very rapidly. We were familiar in works with pathologists, molecular biologists and biotic technicians. Now we are working in strict relationship with bioinformaticians, bio statisticians and physicians. So the cost of this very complex analysis has To be taken into account, then of course there is the cost of the platforms and the maintenance. I mean and we have to take all these issues into account before deciding whether It is better to keep the analysis in house or externalize it. Let me just give you an example. I'm running quite a big lab doing basically all kinds of molecular testing. But we recently decided to keep in house next generation sequencing, whenever this kind of analysis is carried out by targeted sequencing. So panelists, you know, 50 to 500 genes And we decided to externalize to another academic institution the analysis of all exome sequencing and with genome sequences. This is why We would not be able to get this kind of complex analysis within the turnaround time that is absolutely compelling for clinical practice. So the organizational issue is very important. Then there is the reimbursement. And of course, every country is different with regard to the reimbursement. I'm based in Italy. And in Italy, the reimbursement is based on in a health system that has a universalistic approach. So basically, my system dictates that only tests for drugs which are registered by the National Drug Agency would be reimbursed. So this means, for example, that In the examples made before, the analysis of in the earlier Presentations, the analysis for PI3 KCA by RT PCR or NGS Has become reimbursable just 3 or 4 months ago. And for example, the analysis for microsatellite Instability for the prescription of immune checkpoint inhibitor Has not been decided to be reimbursed till now. So we could not do that By using our budget. And lastly, there is a technical issue. Let me just tell you that, of course, we have to decide whether or not to get a single test or the biomarker included in a panel, For example, NGS or NanoString. And then of course, we have to decide If the test is a companion test, in this case, we are forced to use specific kits or a complementary test, in this case, we have to choose According to specificity, sensitivity and so on. Let me finally just comment on the fact that the pre analytical phases is very important. And this is, in my opinion, an important point because, of course, technology is, Of course, very important as well. But let me tell you that, you know, as we have seen in the earlier presentations, you know, All the system is on the collection of clinical samples and the pre analytical phases are very, very, very critical. Very complex tests like target NGS, they could be affected Just by the decision. So this is why in my opinion, the pharma companies, rulers and The academic institution must work together in order to ensure that all the phases are, I'm run-in a proper way. Thank you, Professor. And thank you for sharing those insights and helping us understand all the That you're facing. So Avi, I hope you don't mind me describing you as one of the veterans of Precision Medicine and someone who has been observing the transformation underway within the industry. Could you help Our audience zoom out for a second and give your perspective on how industry wide the issues described here by Peter and Professor Brunerri are. So thank you. Thank you, Susanna. Thank you, Diacetics team. Thank you, distinguished panel, Peter Holm and Professor Bruneri. Let's first conclude with a statement and then we'll build up to it. Absolutely, yes, industry wide, Multi regional, so there's no easy answer in any particular region. And now let's explain why, right? There's many ways of picking this up, but let's start with where our good professor just Just ended, right? He was talking about the pre analytical components and for purposes of consistency, We are generating the sample appropriately, the analytical, and then there's the post analytical. There's all of the, what does it mean? Let's interpret it. Let's allow for a Actionable lab results to be reported and produced. And then, of course, billing and all of that sort of wonderful commercial stuff, Which is also important for the longevity of the lab. What this actually was alluding to Was the incredible variation that the system has That comes from, 1st, biology and chemistry, as in every disease in every patient Has a multitude of reasons why there could be variances, either in the kinds of biomarkers expressed, The levels of biomarkers and for and for certain, additional sort of, chronologic, you know, progressive Variances in patterns. So we start with a biological problem. Lab start, physicians start, former companies start with that. Let's assume for the sake of simplicity that they can solve for that. They can say either the one biomarker or the mix of biomarkers that definitively With this special greeting, can give us an actionable analytical answer is provided. Then comes the, Well, it's the industry, the lab industry able to provide this answer with any degree of consistency. And it's a brilliant a cottage industry of high level experts, right? So the cottage industry illusions, and it does a disservice. But what it is is, and again, to the point Peter made, It's like a million odd total number of labs in the world, all of which because of what they do can produce aeration. And so for any one decision maker, a pharma company exec or a scientist, it is a how do I pick this Lab to give me the answer that allows me to then move this assay through And for patients, which is to have the right prescription decision and then get to the right outcome. Right? And then Following all of that is a huge amount of variance around reimbursement and reimbursement coding and for that let's not just yet. It is a gigantic problem, which still recently we have said to ourselves, wouldn't it be nice If somehow all of these data could be aggregated in some logical fashion And insights engines be overlaid onto the data to start answering the sorts of questions that have bedeviled us for Decades. And not to make this just a pure play pitch for DxRx, but that is exactly what DxRx is doing, right? So To turn this now to what sort of what Ryan said as he was presenting the case, the use cases. In effect, we have taken one of industry's Most difficult challenge is a glomeration of data, which was a very hard thing to do, cleaning the data so that it could actually be lend itself to analysis. And then we are an AI technique, especially AI because you want to have a hypothesis If you want to bake into the analytical tool that you will build, start to draw an insight generation engine. And so That's both the problem and the solution that I think we're talking about today. Thanks, Susanna. Thank you. And I think we have some common themes here on variations and complexity and the need for Standardization. So let me move to the next topic, which essentially is how do we address these issues. And You are from different perspectives familiar with the ISUJIX and the recent launch of the DxRx network as an Implementation platform and data rich solution. So Peter, if I turn to you again, when talking precision medicine And introducing a novel diagnostic test. We've heard various challenges Right by the panel. In your view, what needs to be the key focus in an end to end solution for diagnostic commercialization? Great. Thanks, Susanna. I think from my perspective, unfortunately, I don't think there's just one thing, but The important point that you mentioned is end to end solution. So for us, it starts with who our diagnostic partner is going to be. We live in this kind of weird dichotomy that we need a regulatory approved companion diagnostic. So, we want to pick a partner that has capabilities at, But that they also have some footprint in the world so that we know that that one diagnostic test is available in many places around the world. But we also know that in most countries that companion diagnostic will not be the majority test used, that these are laboratory developed tests that will be used. So it starts with picking the right partner, but then it quickly goes to understanding that lab environment as I was talking about before. Focused percent and this is why I think the diastutics capabilities and in particular DxRx So important for pharmaceutical companies, we have no real capabilities focused on that lab customer. There are some farm companies who have built up some small capabilities, but that's really just the tip of the iceberg. So, really understanding that lab environment, what labs will be that kind of The eightytwenty rule, the top 80% of labs that are going to be servicing your test and what are they doing? What do you have to do to help them either adopt a new test, change what they're doing, or be a partner in helping to kind of validate a new test. So to me, it shifts quickly from we have this companion diagnostic partner There's this whole other world out there that we have to get our hands around and doing it in an efficient and effective way, so we can Meet that test uptake and product uptake requirements that we have. Thank you, Peter. Some very interesting reflections. And I'll direct my next question to Professor. As you know, one of our ambitions with DXRx to support a stronger local and global lab network to facilitate the collaboration between multiple stakeholders in the diagnostic ecosystem And to shift a lot better testing for doctors and their patients. So Professor, can you give us your early view on The advantages of this type of platform and how this may support you and other laboratories. Thanks for this question. I mean, I remember the first time I saw this platform. I mean, I thought it was, you know, it could be an extraordinary chance To be networks focused on specific tasks and procedures, Especially in the area of equity related to accreditation, regulation And of course, good clinical practice. This was the first impression. Then I think that The second important issue that is related to a platform like that, The chance for an institution, this is quite new in my opinion, because we are not very familiar to this kind of activity, but it's a very good A chance for an institution to let the other institutions, the biotech companies, the pharma companies, how we are, You know, dealing with specific problems. It's a kind of, I will not say, you know, Advertisement because it will not be correct, but it's just in order to let the others know What we are doing? And I think that it's I mean, it will be very, very important. Let me tell you that, For example, in my institution, we are trying to integrate and improve and implement the platform, the profiling platforms we have here and we launched the Molecular Arturo Board 1 year ago and as soon as we completed this project. We will for sure try to present the project in your platform because it will be very important in my opinion, I'm trying, for example, to get info in Italy or in Europe With regard to the molecular tumor boards, how they are working, the procedures they are following. So for the Time being, we are just being involved in a project that is very important in my opinion, that's being chosen properly. That is the assessment of the HER2 law in the clinical practice. This is a very I'm in task for the future. And with regard to the laboratory, to the pathology labs, This is quite a critical area because we must still discuss how to evaluate the cases. We have to register Our reproducibility and so and so I'm very excited to be involved in this project. And lastly, I think that, I mean, We should keep in mind that the future in my opinion is, would be, awareness, culture and data. And I think that the platform like yours is fulfilling all These activities and this issue. So I think that a platform like that could be fostered and endorse a more close network between institutions. And I was I'm also thinking about the fact that we will be faced in the next future with the IVDR, with the IBD regulation in at least in Europe and we need help. We need to work together in order to, To get this kind of regulation real in our labs And again, procedures working together, I think that you are creating a tool that is very important to get this kind of objectives. Thank you. Thank you. So Time is running and there are so many questions I would like to ask. But before we go to the Q and A, Evie, I would be interested in hearing from you your perspectives on The digitalization which digitalization is a word we cannot avoid, but it seems that digital commercialization is still relatively new to the pharma business model. What do you see as the advantages of DxRx as precision medicine and the need for timely access to new diagnostic tests continues to evolve. Thanks, Juliana. And I think this is a key question in today's time, right? We accept For today's discussion, especially that our definition of digitization is that all of the data related to the tests, The labs, the performance specs and the network and the outcome is digitized and is available. And then added to that, over time, we start to put in social determinants of behavior. What we have here then is the ability to, in one set of keystrokes, start answering some of the most important questions that we have grappled with for, you know, for a long time. Is this test or assay available? Where is it available? What are the performance specs? Which are the technology Forms that support this particular performance. How can we roll this out in to meet the disease burden? What kinds of variances come about because of idiosyncrasies with patients and providers and all of the things around guidelines that do vary from around the world? And then how can it be coded for appropriate usage, for appropriate pricing? And that list does go on, right? So but The advantages of digital is that it allows for this step change where it is not a one problem, one analysis, One answer to a multitude of repeatable and fast analyses that will, I think, break the logjam in this business of How do we generate perfect valuable and perfect information that then results in actionable, that can then results in action? So I think this is critical, and we are on the cusp of it now. Thank you so much for sharing your insights. And at this point, I would like to bring Ryan back in and open the floor to Q and A session and to any of our guests And while we're waiting for those first questions to come in. I would like to maybe point attention to a recent article in The Economist where the CEO of Roche I'm interested in hearing if you agree to this statement. And if so, what is the opportunity of the EXRX? Thanks. Let's break this up into the following components and then answer it. Pharma produces a drug Just a surgery produces an intervention, right? So it's an action that is taken. And in that sense, it's no different than, let's say, There's a device like a knife that can be used to cut something. Diagnostics produce information on the state of the patient That informed you on what actions you can take. Each of these steps have their own inherent value. But it is when you combine these 2 that you actually generate the best value so that you can have the best outcome. So, Deborah and Schwab, the CEO of Roche, who was in this article that came out, I think, last week's Economist, I'm actually alluded to something very, very important, which is if you only participate in part of this, If you only participate in explaining what the disease status is, you know, biomarker based, patient segmentation strategies and so on, That's part of the equation. If you only can I know what to do? I have drugs to take care of that. Well, that's very good. But if I can put it all together, I can start getting to genuine outcomes. I can posit what those outcomes will be. And then I can participate in the healthcare system as a both value creation and value capture on an outcomes basis. I can get back to a concept which if I was in this place, I'd be thinking about when do I get to participate in disease management And start thinking about things like capitation models and so on, which are all the rage, especially with personalized medicine and solid gene therapies Coming to the floor. So this is a very powerful statement that he's made. I think we're going to see this play out over the next several years. Thank you for sharing that. Do we have questions? We do have some questions, yes. Precision medicine has so far only really been widely prevalent in oncology. What are some other therapy areas that should see an increase in the use of precision medicine in the near term, say 3 to 5 years? Peter, can I direct this question to you? Sure, absolutely. In my role when I was leading the strategy group for precision medicine. We worked across all therapeutic areas and admittedly a majority of our projects were in oncology and And still are. But what we had projects across areas such as neuroscience, immunology, Cardiovascular and in our new gene therapy unit. So we definitely see the science And the market behind in other therapeutic areas, but in some respects is catching up quickly. The science is obviously different. Oncology targeted therapies is very mutationally driven, but we are seeing in most of these other areas that there are biomarker Determine discovery efforts that are leading to drugs. One area in particular is Alzheimer's disease. We saw recent Somewhat controversial approval and that's also based on a diagnostic test around beta amyloid. We worked in that space Significantly as well. So, this is a trend, the precision medicine trend is not limited to oncology. It is definitely the leader, but in our business, we see it across all areas. Every single one of our therapeutic areas have Biomarker leads diagnostic experts and commercial strategy to help really understand and identify where the precision medicine opportunities are and to bring them to life. Many thanks. And if many new diagnostics take years to reach How much more quickly could laboratories offer new diagnostics if they're able to collaborate and network together? So I would be very interested, Professor Pronary, to hear your opinion on this question. I think that working together would be absolutely necessary, especially in the firm. We could not think, you know, keep working separately and trying to get in every in each All the diagnostic procedures. I'm already mentioned the fact that even if we are quite big lab, we decided to externalize whole exome sequencing seeing a wound genome sequencing analysis. Let me tell you that in a more, you know, pragmatical and I mean, view, there are data coming from ASCO telling us that patients with advanced lung cancer, they have, you know, An extensive and sufficient analysis of their disease just in half of the cases. And this is why we are not working together. I think that the future, I'm just using the example of Italy, I'm based in the north of Italy, but I think that it will be the same in Europe and possibly in other countries. We must try to set hub and spoke networks very closely interrelated, Possibly working together by using digital pathology as the first analysis. So we could work together With regard to the first diagnosis by digital pathology and then sending in central labs Tissues or nuclei seeds for 2nd and third analysis like next generation sequencing. So a patient getting in a very local and small centers, they could have the Same, you know, analysis they could receive very big hospital, very big centers. And this would for sure filling up the process of diagnosis and the translation From Research, Clinical Trials and Real World Data. This is in my opinion the One of the most important challenge we will face in the future, there are a lot of new drugs, new tests coming from the research and clinical trials area. What it is difficult is trying to integrate And do you Aby, can I ask your opinion first, but I would also like Peter, if you could give your opinion after? Well, I can just point to the industry trend, right, which is we have seen over time as it becomes clearer To industry and to the commercial and brand and the lifecycle teams, what the value of diagnostics And segmentation strategies are, they are putting more money into it. And as they put more money into it, it's a virtuous nice virtuous circle, right? They put more money into it, But our assets get developed, price points go up. And so we start to see, in general, a larger spend going towards Companion diagnostics, enabling diagnostics, that general area of assays. Peter, I'll defer to you. You're probably on the side where you get to make these decisions? Thanks. Yes. So, I would say absolutely yes. And there's a couple of components to it that I think are really important to understand. So, first of all, unfortunately, we as big organizations sometimes tend to Learn things after the fact. We have the Herceptin story that Peter talked about, but I think everybody in every company that has any experienced with launching companion diagnostics realizes that the things that we could have done sooner that we could have done better to really optimize that patient identification. So that's a learning that's now embedded in our organization. And So that's the learning that's now embedded in our organization and I think in every organization. The other thing that's really important to understand as you have this trying towards more companion diagnostics, particularly in oncology, where testing becomes the standard. Oncologists are going to test a patient. So if you have a patient with non small cell lung cancer, most likely that physician is going to do a broad panel Test for that patient. That test will determine how that patient will be treated. So, by definition, that lessens The impact of any particular representative, it's not about, hey, doctor, please use my drug. It's please test and do what the test says. And those testing practices are already determined. So, as I was saying before, it's really critical to understand How that physician test, how the test is done and does it appropriately call out a positive patient. So that will shift Budget from more traditional pharmacellingandmarketing towards commercialization Around the test and I use the term commercialization broadly because it's not just about a sales rep, but it's about Really helping to enable a lab network that could start years before launch to do things like concordant studies, Bring studies, getting labs up and running. So that shift is starting and I believe is going to continue As you see, less impact in traditional selling and marketing and more impact, more consequence around getting The lab world, the lab networks are ready to test appropriately. Thank you. And how much manual Input from the lab is needed to keep all data up to date. How onerous is it basically and how much can be automated? Ryan, do you want to address this question? Sure. Thank you, Susanna. I would say we're halfway through our full automation of Data extraction from the lab. So today, there is a level of commitment they need to make to provide that data, but we Provide significant value to them as well where that level of Commitment they need to make seem to be justified. So through that value proposition, Through giving the data back to them when they put it in, there is a general view that it's worth it from their side. And as we continue to develop the platform, we're making it easier and easier to get that data and allow the labs to interact with us. Thank you. And a question for Peter. When you looked at your diagnostic testing for EGFR Are Exxon 20. What were the other options considered for addressing this issue? Are the data providers in house capability, etcetera? Why will a lab engage with the lab broadcast message? And what's the engagement depth? So, A couple of things. So there are 2 companies have launched exon 20 drugs. I'll speak to our And our work with Diaceutics. Once we understood the issue at hand, and again, this is you have to really be in this space And even our farm colleagues didn't really appreciate the fact that even though EGFR testing is standard, Being able to identify and call out Exxon 20 was a nuance that not every lab was doing. So, first of all, really understanding that and getting the organization And that was critical. One response potentially to it was to build our own lab sales force and start once we identified the KeyLab is going out and working with them significantly before launch to help get them on board and Exxon 20 was coming and make sure that they were testing That potential solution was actually reviewed, but it was not accepted because that's a High cost solution to build, even if it's a small sales force to be able to do that. It's also spending significantly at risk Because that would be long before the drug was approved. So we opted to work with the diastutics team and the lab specialists within diastutics To be able to identify and call on the right labs to help support the development of The exon 20 test within that particular lab. So that was our response to that particular question And working with Iastudix, in some ways, I want to say it was the only option, but it was clearly the most effective and efficient option for and that was in the U. S. Specifically where we've launched that with our U. S. Team. Thank you. And the integration of data from the lab matters. Could you talk a little about the general state of the lab's IT systems and how the integration processes work? And And how the integration processes work and how much of the average labs testing is actually being captured in the data and how much manual data entry, I could take this one. Okay. And I'd like to maybe pass to Professor Poornary. It varies massively. And It's not just regionally, but by lab type, by type of testing. Some laboratories are Very ready to engage and their data is in a very ready state to work with and we can engage And it's a good very quickly. Others are at a different stage in their journey. We have built our model to be compatible With labs across entire spectrum, it's not just the bigger labs who are better prepared. As I said, it's incredibly variable. It is improving. And as a level of standardization comes in, we are benefiting from that. But in many ways, A large part of our onboarding and integration is working through that data integration with the laboratory, Which as I said is in variable depending on the market type of lab, etcetera. And we have a quick question for Professor Prenari. How many other service companies do you provide testing data to? And what do you believe the benefits will be to you from being a part of a larger DxRx marketplace that brings together other labs We are working in close partnership with especially with biotech companies. Approximately 30% of our, for example, The results of next generation sequencing are provided in our institution by FoundationOne. This is because They are providing tests, which are companion tests in clinical trials. And so what we have done is I'm externalized this our cases to FoundationOne and centralize the results So that all the data are discussed within our Molecular Tumor Board. Then of course most of our patients are included in clinical trials, Which may be pharma driven or academic. And Lastly, let me just comment on the fact that data are very important and this is a problem in academic institutions. We just licensed the project for the implementation on the informatic a structure in our institution and the funding was approximately €1,000,000 just for the implementation. This is because we need safe data, data which can be integrated with clinical Outcome data and all the and also the biorepository data. So, and with regard to the lastly, With regard to the chance that we have to work together to the pharma companies, I think that I mean, in my opinion, academic centers will be an ideal partner for academic for pharma companies and also for biotech companies. And we will in the next year, I would bet that we will be working in closer contact than earlier because We have the same at the end of the day, we have the same objectives. And I think that we could address all the issues working in closer a partnership with the pharma companies. Thank you very much. And that's the end of the question. Susana, back to you. Thank you so much. And I would like to thank the entire panel and especially thank you to Peter, Professor Prungari and Avi for taking the time to join us and share your expertise and insights. That's been really helpful and fascinating. I would like now to pass back to Peter to talk about the strategic roadmap underpinning the platform. Indeed. Thank you, Susanna. And I echo my thanks to Peter, Professor Preneur and Avi. It's interesting just listening to each of you breathing life into a problem, which For many, even in the industrial world has lain opaque for far too long. And I think you've given voice To that and indeed describe quite well the importance that this will have within the future pharmaceutical business model. So, I really appreciate you taking the time to do that. And in a few minutes, I'm going to ask Philip, who is our CFO, to speak to the financial flows underpinning our evolving business model. I suspect that will be a question for many of you. But I want to take a few minutes to speak to the strategic roadmap and where are we going With the platform and the progress along it. So let me first deal with competition. I think as Peter and others spoke about, The pharmaceutical industry is already spending money to understand and address the diagnostic hurdles. But this budget is not yet centralized. In fact, by our own view, it's spread over as many as 15 different buckets Within the same brand team around the globe. It's not yet pulled and integrated into one location. Consequently, we see competitors calling into a number of the buckets beginning to target the now recognized diagnostic problem. In areas of data, For example, we have competitors like Prognos, which is a U. S. Centric. It's non oncology focused by and large and provides largely generic datasets next to pharma for their own teams to interpret. In contrast, our data insights and the diagnostic deductive pathways, which Ron mentioned, They're laser focused on identifying and eliminating the hurdles that we've described. There's also competition in the lab network space. Companies like Roche's own foundation medicine, which Professor Pernieri mentioned, they are promoting a highly centralized testing model, very effective within research and development. In our model, at the commercial end, we do not impose a disruptive lab infrastructure in the issue, But instead we've sought to create a network, which we hope to leverage their experience over several 1,000 labs, All those labs with existing doctor relationships. And of course, we also see consultants in pharma services Augment their own businesses with the precision medicine offering, companies like Lec or IQVIA, names that will be familiar to you. We of course absolutely recognize the importance of understanding our competitive landscape itself. It's a function of a precision medicine market that's on the move. But our focus really is building a comprehensive and dedicated offering to pharma And to our lab partners. And in our view, it combines all the strengths of those competitors, but we go one step further. We go one step to deliver a single commercialization service dedicated to delivering a superior return on investment And getting more patients on the treatment. Many talk in the precision medicine business about the highly competitive and mature Services market, which is focused on the R and D side of the Pharma business. But today, our market opportunity on the less well served commercial side It's now clearly mapped out for us. More test dependent therapies will continue to need a seamless diagnostic commercial solution. More pharma wallop will be released and managed to ensure each of these important drug launches do not lose patient opportunities. And these budgets themselves will increase. They'll become centralized within pharma. And we can also see an accelerating trend towards seeking digital And indeed cost effective solutions here. Again, Peter already alluded to that in his own example. Based on our track record, our position with all the important in the precision medicine. Alongside a nice scalable platform, we believe that we're optimally placed to capitalize I'm the 1st mover advantage in the space that we built. And we think it's a space that's worth over $3,000,000,000 in the next 3 to 5 years. So what do we see as the strategic roadmap for those 3 years? In essence, it's an aggressive pursuit of market share in the space. Let's start with 2021. Platform adoption, as you know, was all about bringing the most important partners onto the platform and driving hands on use. That's our focus for this year. Using the measurable impact of those first platform based projects to quantify investment to clients And give them the proof of their ability to actually control and obtain this diagnostic ecosystem. And to do that predictably It's our focus in 2022. And by 2023, we will illustrate the benefits to each of our clients of migrating many For all of their diagnostic commercialization needs onto a single platform. Consider this, salesforce.com Has become the ubiquitous tool in managing the time and metrics of Salesforce Optimization. We aim to provide that same enterprise wide solution For our clients when it comes to diagnostic commercialization, and we believe we're really well placed to do that. So If 2021 is all about partner acquisition and hands on experience, what's our progress after 6 months on the market? We're genuinely excited by the traction in this foundational year. And whilst we were budgeting to convert 20% of our business onto the platform. As we sit today in that kind of 1st 6 months, the run rate is closer to 40%. It's also unlocking benefits to value coming from margin and price differentials versus the same time last year. And as you can see by the chart, All the adoption indices that we're building for ourselves are all trending in the right direction. And with only 6 months into a 3 year conversion of our business model. Interestingly, our multi sided platform is already generating interest as an integrator in this broken diagnostic ecosystem, Even beyond our historic focus on pharma and lab stakeholders, something we hope to report on in future sessions. Hi, Deborah. Our goal for platform conversion was, as you know, not just about projects, not just about patients and not just about disrupting and changing a business model. It was also about evolving our underlying financial architecture away from a consulting esque a project centric approach to predictable long term revenues and high margins enjoyed by platform business models. And here I'd like to hand over to Philip to just refresh where are we in our journey and progress there. Thank you, Peter. You can see why we're hugely excited by the power of the platform. Rand demonstrated some of the granularity around the data And also the activity, as Peter described, in the KPIs to date. So over the next three slides, I really want to set out the DxRx business model. There are some dynamics within this business model I want to bring to life. We then want to look up the revenue streams that underpin the business model and then bring that all together Into the financial impact and our aspirations as we move towards $1,000,000,000 business. But firstly, let's look at the DXRx business model. And if you look at the graphic starting from left to right, The platform itself leverages off the data repository and the insights, the data lake and the insights that we've developed Over many years, and Brian has demonstrated how the data can flow back many years. Key question for us is how do we monetize the platform And how do we increase our revenue capture? We monetize the platform by selling 16 modules, which come off 5 different revenue streams. Network access, data license, data subscription, tech enabled services, and professional services. And we'll come to these In detail on the next slide. These 16 modules, and Ryan has demonstrated some of those, make up our full end to end commercialization offering. Some modules are point in time revenue, some are subscription based. And our sales strategy is to land and expand, landing 1 module within our clients and expanding into many modules Over many years, effectively selling more to our existing clients and winning new clients. So to summarize, monetizing via our 16 modules, increasing our total contract value as we layer in our data, Our subscription and our tech enabled services over a longer engagement period. As Deborah stated at the start of the Presentation, increasing the customer lifetime value. Looking at another positive financial impact for the platform is our laboratory engagement And the financial benefit as we bring laboratories onto the platform is the reduction in labor associated with our own laboratory engagement teams. Ryan touched on a communication channel within the platform. That was all manually done pre platform. Another important financial impact of the platform is that we have access to the data flows from the laboratories within the platform. The Board of Directors get the benefit of being on the platform, and we receive data in return. We call this exhaust data, And this effectively reduces the acquisition cost of our data. So as we increase the activity and the engagement on the platform, it generates stronger data and insights for us. It creates and increases our offering in real time data and insights, opening up more pharma brand teams for our BD folks to target. And just to close off this loop, as more pharma brand teams come onto the platform, the stronger it becomes via the data And the Laboratory Network and the Cycle Continues. So the platform in itself lends itself to subscription revenue model because it's data led. It's a scalable platform with high gross margins. The data alone represents a gross margin of 90%. I touched on the network effect efficiencies within the platform in data capture and the reduction in labor cost around our labored reengagement teams. And there's potential for short term to medium term upsides in non pharma Revenue channels, that is data companies, laboratories, and diagnostic companies. So I've mentioned the 5 revenue streams. Each of the 16 modules we sell within the platform fit within these revenue streams. Again, some are point in time revenue, network access and data license. We also have data subscription, which is a 12 to 36 month As subscription to data, tech enabled services and professional services are broadly milestone based revenue. And we see data and tech enabled services making up 90% of revenue. Our objective is to land the client into network access and data license, transition into data subscription And then layer in the tech enabled services modules. And if we take a recent example of a top 5 pharma company, firstly engaged via a data license to really in one country, one biomarker to understand the market. Within 3 months, that had moved to a $500,000 data subscription and multiple tech enabled service modules covering multiple countries. The output of this was an understanding of what Peter described earlier as the barrier to prescribing one of those key barriers. And we are exploring the opportunity of a further $500,000 contract to understand the laboratory testing. And we can see this engagement for this one brand team expanding globally with the need for data and tech enabled service addressing those barriers that Peter touched on earlier. So within this real world example, we can See really a runway for us providing $10,000,000 of value to this one brand team over multiple years. And we don't want to stop there. We want to provide that type of value to all of the brand teams within our clients, really embedding as an enterprise wide license, and the platform allows us to achieve this. Capturing a meaningful market share will transform our key financial results, and it is our aspiration to do so. And I'd refer to Stifel's recent note on our immediate outlook. We have a clear path to revenue growth with our DXRx platform And the ability to capture the increasing demands from our clients. The platform is delivering high gross margins. We have this network effect efficiency within that, resulting in a strong EBITDA moving from 15% to 25% And into a cash generative position. So we have a platform to become embedded within our clients, Underpinned by a high percentage of subscription revenue. And of course, we will continue to invest in the platform and continue to invest In our data, the aspirations that I have presented are highly achievable. And we are passionate and excited about delivering the next phase of growth for our business. I'll hand you back to Peter to round out the presentation. Indeed. Thank you, Philip. This is the last slide, I think, before we open up to any final Q and As. And you can read the key investment points for yourself here. As I reflect really on the decade plus journey that we've been on at DynaCivics, I told my team Many years ago that in essence we were placing a bet. We're putting a bet to be in the right place with the right company at the right time. And as most of you know today, I think precision medicine is the right place to be in healthcare. I hope that what we've demonstrated today is that we build a strong beachhead in precision testing with leading clients and we're in the process of converting that to a scalable platform. And that makes us the right company to serve the complex unmet need here. But of course, what I did not say to my team was that the last of these, in other words, To get the timing right, it's not actually in our control. It's more in the hands of the marketplace. But we can hold our heads high And speak to the team and say that we really are in the right place with the right company at exactly the right time. We're never complacent about the challenges in front of us. And I can say that across the company every day, there is an entity of a team that knows the impact that we can make and very much focused on the roadmap and is ready to take our place alongside the company shaping precision medicine So with that, I'm going to open the floor to any final questions you might have for myself and the team. And the first question directed at Ryan. What is the lead time to build a lab mapping and network for a pharma client? And how many If your 2,500 labs need to sign up to DxRx in order to have a critical mass, I. E. Versus greater than 200 labs today. And what is the potential issue if a pharma client decides to go direct to a lab identified On DXRx versus trying to keep the engagement with the platform. Okay. Thank you. I'll try and deconstruct that question. First of all, the lead time is we can pull those lab mappings out effectively instantly. We maintain the data across those 2,000 labs. And just to correct that, so While we have 200 and increasing labs on the network recruited, we still have profile information And data on the additional labs. So we can still have a mapping that where we want to Interact with those labs are limited to those that are actually already recruited onto the platform. So the lab mapping is still done in its entirety. And where there's a recruitment step or an involvement in the tech enabled service, that's limited to the laboratories that are onboarding today. And that process is very quick from a pharma perspective. As the labs on board, they Sign an agreement with us as to the types of services that they are enrolling in. One of the part of that agreement is that they will be exposed to pharma. That's actually an advantage to the laboratories for the most part. They see that as a good thing to get closer to industry and to get closer to the foreign company. And indeed, Where our client wants to take that information and build upon it themselves, that's perfectly appropriate to do so. We don't restrict it in any way. We're trying to build a collaborative model where we believe all stakeholders should be allowed to interact. In fact, we promote that. Ideally, it's done on DXRx and what we believe is we're building a channel that makes it easier to do that on platform rather than off platform, but we don't limit that. Ultimately, it's about doing the right thing for patients And we make sure that that lab and formation can happen if it needs to. Thank you. And have you had any pushback from doctors About being targeted around prescribing decisions, even though it's based on anonymous data. Again, I'll take that. There are mechanisms by which businesses can opt out of any direct interaction with Sales teams, etcetera, that is well established as a mechanism. Ultimately, where we are Leveraging the data is typically to provide education and awareness. And what we are hearing consistently from physicians This is of a benefit to them. This is an incredibly complex space. We see through market research that Anything we can do to support the understanding of biomarkers and when they should test and how they should test and where they should test It's generally well received. And the information we have is powerful, but also it needs to be used in a way that is Appropriate for these and there's a high bar as it pertains to compliance And a regulatory framework in which that data can be used, which keeps all stakeholders somewhat protected here. And as you say, it is anonymized from a patient perspective. So they're absolutely anonymized. And the physician relationship with pharma is a regulated one. Thank you. And what are the greatest risks The And medical practice perspective, what costs do diabetics need to bear to break down resistance? I think Let me take that One of the things I would say we cite in many of our documents, the experience that we've had Over the last decade or more, and we're not just saying that as a kind of a library boast, we're really saying it because we have spent I'm many, many years on the job experience building the right product. It started with building a method, which we call the diastolic method. And as you know, we've been converting that method, the data, the lab network into the shape of the platform as it sits today. I think from our point of view, we recognize that the platform is both A smarter way to deliver what in essence are a series of very disparate and fragmented existing services. So it's providing inefficiency and riding on top of that efficiency, we've already seen some pharma some of our pharma clients are restarting to move and adopt Because of the efficiencies that it brings to the table. And again, Peter and Abi mentioned that. But of course, we're introducing a platform business model into an area which is siloed and fragmented. And we shouldn't be complacent about, I think the challenges, both the educational challenges that that requires. What we do know Is that if you want to drive a modern smart platform in healthcare today, you need to do 2 things really well. 1, You need to give your clients and your labs hands on experience. You need to let them go and get dirty with the product itself, roll up their sleeves, See what that experience is. And we're in absolutely in the midst of that process. And the second thing we need to do is to give them the confidence The impact of that platform is real. And here, I think we have an absolutely huge advantage. We're not just changing practice, We're measuring all the time. We're quantifying. We're quantifying going into projects. What is the state of play today? We're changing practice and we're measuring how that practice is changing. And there's nothing that is going to give confidence more To our clients and to our labs and to other stakeholders and to see in front of their eyes, it's something that has normally taken 3 to 7 years to get a new biomarker Into the hands of the right labs is happening in 10 months. That's the sort of impact that will drive change in the market. And that's why I said in our strategic roadmap is this year, get hands on experience, get our clients and our labs rolling up their sleeves and joining us. Next year as we bring some of those impact studies through, we will make sure that we shout loud and clear at how we are active, turning a broken diagnostic ecosystem into something that is a benefit to patients where the outcomes to those patients Will radically alter. They will get tested faster, and they'll get onto drugs faster. That's the sort of impact that we will be bringing back to the world. In my view, Other hurdles like cost, etcetera, will fall away because we'll be bringing a bespoke and tailored solution To a marketplace that frankly over 15 years, if not 20 years, has been neglected. Thank you. And we'll squeeze one final question in. Revenues are currently relatively modest, especially set against the immense value you create for farmers given their high return on investment. Can the model shift to take a share of the incremental drug revenues the platform seems to create? The platform allows us The runway to provide $10,000,000 of benefit or value to our clients. And we see that transitioning through 2023. But The question raises a good point. And we do have our eye on what we call milestone payments. Our pharma clients Do not really like the word royalty. So it would have to be in the form of a milestone payment. And I think within a mature platform, Within the post-twenty twenty three, that certainly we could look at pivoting the platform towards a milestone payment, really attracting more of that value that our clients see and really rebalancing the sort of the value shift there. Peter, back to you. Do you have any closing remarks? Well, just one, I know that everybody who has joined us today From the investor side, does so in the midst of an extremely busy period for you all. So look really grateful that you've coming along and spent the time with us today. As Tamsyn mentioned, all the questions that you've answered asked will be answered. And for those of you who've already invested in our journey, hopefully you can see some of the fruits of that investment coming through. We genuinely look forward to reporting progress back in the months and in the years ahead. So thank you very much indeed for joining. And again, for our panel for breathing life into a kind of a very opaque issue. Thank you very much,