Good afternoon and welcome to today's Capital Markets event hosted by Diaceutics PLC. My name is Simon Geelon, and I help Diaceutics coordinate their investor relations program. The idea to host today's event was born of positive investor and analyst feedback following their visits to Diaceutics' headquarters in Belfast, where we endeavored to give them a look under the hood of Diaceutics and to showcase the management team behind the investor roadshow team that investors and analysts ordinarily see. Building on that theme of looking under the hood, we have broadened today's event to include conversations with some select Diaceutics partners. In a moment, Ryan Keeling will run through a brief introduction to the Diaceutics story for those online that may be new to the investment case, and as a refresher for those who are more acquainted with Diaceutics.
We will then have a chance to hear from Jillian Beggs, Diaceutics' Chief Commercial Officer, on how she and her team are expanding the Diaceutics footprint by both markets and geographies. Jordan Clark, Diaceutics' Chief Data Officer, will then provide a demonstration of the DXRX platform and provide some insights into the data driving the platform. We're delighted and very grateful to have some external partners joining us today. Alasdair Milton, a Partner with KPMG Healthcare and Life Sciences, will share his view on the recently announced strategic alliance between KPMG and Diaceutics. Lastly, Ryan Hutto, Head of Commercial Diagnostics at Pfizer Oncology, will give us some insights into how a customer engages with Diaceutics and the DXRX platform. All attendees are in listen-only mode. At the end of the presentation, there will be the opportunity to submit and ask questions.
This webinar is being recorded and will be available for playback at diaceutics.com in the coming days, as well as will today's presentation. Before I hand over to the CEO of Diaceutics, Ryan Keeling, a few lines of introduction on Ryan. Ryan is an expert in diagnostics, commercialization, and technology with over 18 years of experience. At Diaceutics, he has led the development of the company's proprietary data lake and played a crucial role in its technological and strategic growth. Formerly the Chief Operating Officer until June 2018 and Chief Innovation Officer until January 2024, Ryan focused on product innovation, particularly developing DXRX. He holds a software engineering degree from Queen's University Belfast and is a recognized thought leader in diagnostic commercialization and data integration. Ryan, over to you.
Thank you, Simon, and welcome everybody to our Capital Markets Day. I'm delighted you could join us today. As Simon mentioned, I want to just take five or 10 minutes at the top of the call to introduce those who are new to the business, to what we do here at Diaceutics. And for those of you who have heard this and I've spoken to you very recently, apologies if you have to listen to it again. Hopefully, there's some additionality. When we think about what pharmaceutical companies, big or small, are ultimately trying to achieve, they're either developing new therapies, new drugs that are potentially life-changing drugs for patients, or they are promoting, marketing a drug that's already approved and on the market. And in both of those settings, we help pharma to find patients.
Very simple concept, but ultimately our primary goal here is to ensure that patients who are eligible for precision medicine are indeed identified and ideally joined to a physician who can ultimately prescribe that treatment or potentially recruit that patient into a clinical trial. That is a primary goal of this business and, of course, very synergistic with what our pharma clients are trying to achieve. When we think about what that means in reality, we are ultimately providing pharma with physicians, identifying physicians who, in the very recent past, i.e., the last 24, 48 hours, have had a patient who is eligible for a treatment that that pharma company may want to prescribe. We have a very deep understanding of patients' diagnosis, right down to, in the context of, say, genetic rare disease or oncology, we're at that genetic or molecular level.
How do we ultimately get this data and what do we do with it? For the last 11 years, we have been building a global network of laboratories. It's almost 1,000 labs now. 570 or so of those labs are in the United States. These labs partner with Diaceutics. They provide us with a typically daily patient-level but de-identified and tokenized feed, which tells us very specifically what disease the patient has, right down into the detailed subtype of disease, line of therapy, and we ultimately understand that patient level longitudinally. Okay? It's not just an initial view of the patient. We can track that back sometimes as much as 10 years into the past. A very detailed view of patient diagnosis.
That data comes to us, and as I said, it's a daily automated feed coming from the laboratories, but the data in its native format, as it comes out of the labs, is challenging to work with. It's largely unstructured data. It's certainly not standardized. When you think about what we're doing here, we're ingesting data at patient level from almost 1,000 different sources. And that has been a very heavy lift on the business over the last 10 years to build the infrastructure to handle that. That was largely a manual process until around about 18 months ago, where we implemented a lot of technology to take that patient-level data, that unstructured data, and effectively make it available for analytics and add a significant proportion of value to that data through joining with other data sets, etc.
We implemented a lot of AI, natural language processing, and ultimately built our own infrastructure for cleaning that data as it comes into Diaceutics, making it available to our customers effectively the same day. That's enabled a lot of product innovation on our side and particularly benefiting our lead product, our DXRX Signal. Some of you might have noted that last year, for instance, we announced our DXRX Signal daily service as opposed to weekly. That was immediately available post the upgrade of our AI and data work to clean the data. That typical use case for that data is to provide it out to our pharma clients. As of the end of 2023, we were working with 17 of the top 20 pharma companies globally. So these are household names: Pfizer, Novartis, AstraZeneca, GSK. That list is well understood.
These are the companies we work with, along with a very long list of smaller pharma and biotech who have precision medicines, whereby this data is extremely useful and directional as to identification of patients. And again, the primary use case for that is to provide those pharma companies with lists of physicians who are able to be passed to maybe a pharma sales rep or used in some other in-person or non-personal promotion to ensure that that physician is aware of the opportunity to treat that patient, has a good understanding of the disease, the treatment opportunities, or clinical trial if it's a pre-launch asset. Those are the things that we're doing. And we deliver that data through our DXRX Platform. And the platform you're going to see today, Jordan, my colleague, is going to walk you through that.
But what I would say here is that the platform that you see, the user interface to the platform, is only one part of it. The bigger task has been building a data integration model whereby our data is integrated directly into the data infrastructure of our customers. Most of this data exchange is automated, particularly if it's a weekly, daily, monthly data update. So that automation is key. Every new customer we bring on goes through that initial integration phase. That's good for us as a business that we've done that. We're integrated. Those 17 of the 20 big pharma and most of the others, we have done that integration now, and it sets us up really well to add on to what we're already providing them.
That might mean offering services to new brands they have coming through the pipeline or to have our services applied to brands that we aren't already working with. A lot of those barriers are reduced when we've already done the integration. The platform interface allows us to really monitor and understand what's going on, and it's a key part of our business model with our customers and indeed our lab partners. Just a final slide from me, just to recap on the opportunity we see here for Diaceutics. We feel we have a strong competitive advantage. The assets that we've just talked to are a global network of labs. Remember, these are laboratories that are very decentralized, very diverse in terms of the testing they offer, the way that their data is organized, etc.
So a lot of work has been done to build what is effectively a proprietary data set from that network of labs. We also have then the platform, as I mentioned, at this stage, we're at a level of maturity with the platform where it's already well integrated with our customers. In terms of the value proposition, it's very clear for not just our pharma clients, but also our lab partners, physicians, and increasingly patients, the value that we can bring. We very much see our purpose here at Diaceutics to enable the vision of precision medicine. And precision medicine brings some new challenges to the market in terms of trying to find those patients. The diagnosis can often be very complex.
These patients are often rare, particularly in the context of rare disease, but even in some of the oncology or other disease areas we work in, we might have a very heavily stratified patient population. So the numbers of patients available are small, and that might mean a physician might only see a patient once a quarter, maybe even once a year. So the opportunity to get to them in a timely fashion is critical. The ROI is very demonstrable in terms of the value per patient. As we look at precision medicine, gene therapy, etc., there's very clearly a significant amount of value going to the rare disease space where you have potentially pediatric patients that are on therapeutics for life, CAR-T, etc., as well. This is growing our return on investment for every patient that we're able to find for the pharma client. We talk about financial strength.
We're a high-margin business with recurring revenue and order book visibility. Remember, three years ago, this business was a pure consulting business. We did not have any recurring revenue, and we had an order book visibility that stretched out one quarter ahead. I do not want to go back to those times. Now we're looking at three years, strong order book growth, continually quarter on quarter, out into 2025, 2026, and beyond. Our customers are household names and are both fantastic customers, but also fantastic partners to work with. We have a three-year revenue CAGR of 23%. We're fully funded for growth. Remember, our plan has us moving into profitability in 2025, coming out of a two-year investment cycle, and still well funded and strong balance sheet. And we continue to win and grow our enterprise-wide deals. The land and expand strategy that we have is working.
We announced the first of our enterprise deals around about this time last year. We continue to announce those as we both sign new ones and build on existing. And I'm excited that there will be more of those as we continue to execute strongly against our strategy in 2024. From a track record, we have been in business since 2005. I feel we're very much seen as experts in precision medicine, thought leaders. We are part of the conversation around precision medicine commercialization, and that is something that's very important to the business, a big part of our presence. We have, at this point, I can no longer say that we've worked on every single companion diagnostic or biomarker in the market. A few slipped through the net, but we'll get them at some stage. But we've worked on the vast majority.
As I mentioned, we're a trusted partner with very long-term relationships. Some of those clients we've been working with since 2005, so coming up on 15, 20 years with some of them. We're very happy about that. Then lastly, as we see global pharma shifting, continually shifting toward a precision medicine approach as the science enables, as patients, physicians, and other stakeholders like payers and regulators really demand higher efficacy, higher levels of predictability around response, we see that shift towards precision medicine, not without its challenges, but certainly something that is the right thing for patients and the right thing for the future of our pharma clients. So I'm going to pass back to Simon now, and then I'll come back in later as we go to Q&A. Thank you all, and over to you, Simon.
Thank you, Ryan. Now a short introduction to Jillian Beggs. As Chief Commercial Officer, Jillian is responsible for developing and implementing Diaceutics' commercial strategy, building the brand, and scaling the sales, product, and marketing functions. She's a recognized industry leader with over 30 years of experience in strategic commercial and leadership roles within multinational pharmaceutical and medical device companies. Jillian has successfully built businesses and driven sales and margin growth through market analysis, strategy development, partnership building, and product lifecycle management. Over to you, Jillian.
Thank you, Simon. As Ryan has explained, we have a set of unique assets and products and services that enable our pharma and biotech clients to find patients and support the commercialization of their brands. Our long-established relationships with our pharma clients have delivered sales success, but our addressable market is much larger than what we're currently achieving.
Over the past two years, we've built a sales and marketing function that focuses our activity with our key pharma clients, delivering a strong presence with the leading precision medicine companies and brands. In 2023, we introduced our account team structure to support our key account managers. For each key account manager, we're adding in a project manager, a business analyst to support our understanding and our clients' understanding of data, and a strategic advisor to help them on their precision medicine journey. This team approach is ensuring that our clients have a consistent sales team working with them, but more importantly, a consistent delivery team, really ensuring that what we propose is what we deliver. Together, this team worked to understand our client needs, to build proposals, scope projects, and deliver exactly to that project, ensuring that the next project is there at the end of the first delivery.
This structure has enabled us to deliver our recent enterprise successes and, importantly, a very high customer satisfaction, which we've been tracking over the last 18 months. However, our potential is to do much more, and in 2024, we've made an investment in scaling our commercial operations. Firstly, within that account team, we're seeking to go deeper and wider in our key accounts. We have added a business partner to that team. The role of that business partner is to open up new brands and new teams in our existing key accounts, really driving that land and expand approach. This, in turn, allows the key account manager to focus on building depth by cross-selling and upselling our products to existing brand teams. This ensures that we're able to position and deliver the full range of our products to our pharma clients.
That's only talking about our existing clients, and we know the market is much broader. As Ryan already alluded to, there's a wide number of new smaller pharma and biotech entering the precision medicine space. Outside of our key accounts, we have a business development team where we focus on bringing on board new clients, particularly those smaller pharma and biotech companies. The role of this team is to identify target clients, position Diaceutics, and gain commitment to the first project. Once the first project is agreed, an assessment is then completed, and that new client is moved to an existing account team for delivery and for further business development.
In 2024, we have an aggressive target to deliver new clients to Diaceutics, and this land and expand approach allows us to both grow our base and then, with our account teams, grow and scale the work that we have with each of our clients. In 2024, we're also seeking to centralize and coordinate our product development through the introduction of a product development team within the commercial organization. This team, working in partnership with our subject matter experts across the business, will ensure that we are able to build a robust product roadmap for the next three to five years. It is important to us that this team is customer-centric, building robust go-to-market plans that enable a smooth transition to our marketing team. We're actively recruiting for a head of product, and that role, we aim to have someone in post for by September 2024.
I've positioned a few of the headline activities to the right of this slide for our marketing team. However, I'm going to touch on that a little bit more in a few minutes' time. Before then, let's take a look at how we have simplified our approach to what are effectively complex sales channels. As many of you are aware, our pharma clients are often siloed, either geographically, by therapy area, or even by brand. My experience in Sanofi tells me that it's often one brand will be working in one area and have no or little understanding of what's happening in an adjacent therapy area. Typically, we see at Diaceutics that in the precision medicine space, the U.S. business is treated separately from the rest of the world, often oncology separated from general medicine, and in some cases, precision medicine separated from non-precision medicine oncology.
As we discussed previously, we've built our account team to enable us to go deep and wide in our current clients, with a business development team to support the acquisition of new clients. To the left, you can see what we're doing with our current. In the middle of the slide, what we're doing with our pharma and biotech clients, and to the right, a new channel that we're opening up. This graphic shows how our key account managers are supported by a wider account team focused on precision medicine. Our business partners, again, supported by SMEs within the team, focus on all other areas within our large clients. Our business development managers, towards the middle, focus on acquisition of new pharma and biotech clients.
To support across both our key account managers, business partners, and on business development, we've introduced sales specialists for our very specialized scientific services and a sales specialist for our engagement solutions. Their role is to identify clients and opportunities for these specialist services and help the account team to draft proposals and scope these, particularly focused on the accurate delivery of these projects. All of the teams have direct selling capability, support from marketing to generate leads, along with potential new opportunities gained through our strategic partnerships. As I alluded to, on the right-hand side, you can see a new channel that we're opening up, where we're looking to work with other life science companies, creating this new channel and adding some business development support.
What I hope I'm demonstrating is that we have now been able to build account teams and scale those account teams as we grow and add new clients or add additional support to teams where we have enterprise-level agreements. With the core structure in place in terms of how we approach our clients, we've then reflected on how we enable sales. As you're very well aware, true success comes when you have that perfect triangle of knowledge, skills, and attitude. With the commercial team, we support building their knowledge by providing them with protected learning time every week. We run a series of internal webinars supported by our SMEs across the business and audit their learning every quarter, building to fill any gaps for the quarter ahead. In late 2023, we introduced a SPIN Selling methodology to our sales and business development teams.
This investment in skills created a consistent approach to sales across all of our teams. In January 2024, we introduced the Miller Heiman models for account management. Building further on the SPIN methodology, the introduction of the Miller Heiman Blue Sheet helps us scope opportunities to identify risks, understand stakeholders, and predict our success. In the months ahead, we plan to introduce the Gold Sheet to take this up a level and help us manage our accounts, supporting our goal to really drive that enterprise-level engagement. The really neat thing about this is we can build these tools into our CRM system, and that, in turn, enables us then to use AI modeling to predict the success within our sales pipeline. A few months ago, we announced investment in our three-year marketing vision, beginning with the recruitment of a new vice president of marketing.
With this new appointment, we're focused on building our brand, driving our partnerships, and creating marketing-qualified leads. In quarter one 2024, we announced an upgrade to our DXRX platform. Jordan will give you a small insight into that in a second. The upgrade was to enhance our client engagement and enable us to cross-sell and upsell our products and our services. The upgrade delivered client dashboards and curated content relevant to our clients and their projects. As I'm sure you already understand, Diaceutics is recognized as a thought leader in the precision medicine space, with a long history of developing and publishing reports and insights that support our clients as they commercialize their brands. In fact, our precision medicine report remains the most downloaded content across all of our marketing channels and regularly creates new leads and opportunities for our sales teams.
In late 2023 and early 2024, we completed an audit of all of our content, categorizing its value, updating and refreshing the messaging, and indexing it all on our DXRX platform. Jordan will show you a little bit of that in a second. In Q2 2024, we introduced AI tools and marketing automation embedded in our CRM system, enabling us to take the leads that we generate through our social media channels, marketing, and events, then qualify and nurture these leads before transferring them to the sales team, further increasing our chance of success of turning that lead into commercial success. This personalized approach also enables us to track the revenue impact of all of our marketing activities.
Our priority for Q3 and Q4 is to launch our brand strategy, introducing Diaceutics as a commercialization partner for pharma and biotech, differentiating Diaceutics from our competitors and creating a clear market definition. I've given you a brief introduction to the activities that we've completed in the past few months and the exciting plans for the remainder of 2024 as we continue to grow and invest in scaling our commercial team. I'll now hand back to Simon.
Thank you, Jillian. And now a short introduction to Jordan Clark. As Chief Data Officer, Jordan spearheads Diaceutics' comprehensive data strategy spanning acquisition, engineering, and data science to deliver cutting-edge analytics to our clients and laboratories. With over a decade of experience at Diaceutics, he has cultivated a profound understanding of the critical role real-world data plays in optimizing precision medicine.
Jordan's academic and professional credentials in biomedical and clinical sciences, coupled with his state licensure as a hematology scientist, underscore his expertise. Additionally, he is renowned for proficiency testing, bioinformatics, and biomarker testing, honed through his involvement with UK NEQAS. Jordan, over to you.
Thank you very much, Simon. So today, I'm going to talk about the overall data strategy of Diaceutics, show some highlights from our US laboratory data, and then take some time to go through a case study of our lead product, DXRX Signal, as Ryan mentioned. And then I'm going to take control of the screen and show you a demonstration of My DXRX, the platform, which really we're going to concentrate on the final mile of what does that visualization of the data look like. And I will touch on the engineering side, as Ryan already mentioned.
A lot of the hard work in the DXRX platform is around the ingestion of that data and validating, processing, cleaning, and drawing insights from that data. We're going to touch on that a little bit, but I want to show you what that end product looks like. But to our data strategy. So first of all, for Diaceutics, as we look at our data strategy in precision medicine, we're really trying to think about how can we exquisitely and accurately measure testing rate, positivity, and then conversion to therapy. And we do that by looking at patient-level data, ensuring that we can link those different data sets so that tokenization to ensure we can see that patient through different data sets that are coming through. And for that, we need a diverse data set as well. We need diverse laboratories. We need diverse claim sets.
We need EHR, electronic health record data sets, and importantly, those prescription data that can come from multiple different places, because we have to stitch this image of that patient journey together so that we get that 360 view. Ultimately, what we're trying to do with that data strategy is really understand that central dogma of precision medicine, testing rate, positivity rates, and conversion to therapy, so that we can use this for hyper-targeting, which is Signal, our main product there, but also segmentation around how we think about messaging to physicians and laboratories so that we can drive that digital-first engagement through our scientific services and our engagement solutions. Ultimately, trying to get to that commercial prescription or clinical trial recruitment, trying to change behaviors on the ground so we see increased patient benefits and outcomes.
Our job here at Diaceutics with this data and the engagement solutions and scientific solutions is to try and ensure that those patients get another Christmas, another Thanksgiving with loved ones, because we need to educate physicians around the better outcomes with precision medicine. As I said, to do that, we need a diverse data set. We also need to be able to link those data sets while maintaining the appropriate levels of privacy. All of our data is HIPAA-compliant, and it has an expert determination and recertified for that HIPAA compliance, something that we go through every year to maintain that privacy level, which is important.
As we go and procure new data through our laboratories, as we grow our DXRX Network of laboratories and look at EHR data sets and other things like that, we're always thinking about the actionability of that data, and the freshness of that data is something that we really work on in how we process it, again, how we validate it, how we use our AI all the time to try and ensure that that freshness is there to increase that actionability so it is useful for our pharmaceutical clients. So I'm just going to show some very high-level statistics from our U.S. lab data at the moment. So as Ryan already mentioned, it's a very messy data set when it is ingested. First of all, there are 67,000 test types covered in that data, with lots of different names and panels being used.
We have to standardize, normalize that so that more insights can be drawn from that and accurate data can come out of that. It's a very high-volume data set, over 1.8 billion rows of data just for the lab data alone that goes to many, many tens of billions when we add in claims and EHR as well there. When we look at just the volume of test orders, we have over 100 million test orders each year in that data set. Again, very, very large volumes of testing going through all of these laboratories that we have to then process as we get the data every single day. So very, very large volumes of data, storage capacity, efficient processing, and compute power is really important for us.
It equates to around 23 million patient lives, and that's growing as we bring on new laboratories to our DXRX Network all the time. We have a dedicated team that are out there talking to laboratories, growing that network in DXRX all that time, feeding that database that we use. Importantly, on our right-hand side, this is the makeup of the data as of today, where we have around 25% of it being oncology data, around 75% of it being non-oncology data. When we work with laboratories, we work to use all of their data. So we ingest all of the data from the laboratories, not particular single test types or particular patient types.
We believe that's a really important part of the model as we go forward, as we see rare diseases becoming more important, as we try and reduce that time for diagnosis for a rare disease patient from the average of being over two years to below that by using different biochemical and immunological tests to help guide education to physicians around which testing should be done for confirmation of diagnosis. There's also lots of things in that data, like a hemoglobin level that's actually really important when we look at a PNH patient, a hematological disease, a relatively rare one. But those patients are monitored through their hemoglobin levels to see if they need to switch therapies.
So that non-oncology data is really important for that broader sense of precision medicine, where a patient's treatment pathway may look different depending on monitoring tests that are being used on them to help guide switching of therapies and different treatment decisions. So that broad spectrum of data is really important for Diaceutics as we think about precision medicine in a broader context rather than just oncology and companion diagnostics. Last slide I'm going to present here, and then I'll go on to the demonstration. So this is a case study of our DXRX Signal. In this case, this is a non-small cell lung cancer patient population. This pharmaceutical company has a relatively rare biomarker, a genetic biomarker in non-small cell lung cancer.
Throughout the year, in the first half of the year in our graph here up to week 26, the pharmaceutical company was relying on a pretty standard targeting methodology using claims data, understanding when patients were being diagnosed with non-small cell lung cancer. So very blunt in our view. We worked with them. They switched on the DXRX Signal. In this case, they were getting a weekly feed of biomarker-positive patients, and we switched that on just after week 26 here. And straight away, we saw that we increased their lead generation. The number of leads, NPI leads that they were giving to their field team, their sales team on a weekly basis, jumped up from around the 10-12 number greater to 20, in some cases, nearly 50 patients a week. The thing with these leads was they were very, very specific.
The sales reps could go in, and they knew that there was a positive patient. The timeliness of having that discussion with the physician was very, very important. Again, that's that hyper-targeting approach that we discussed in the data strategy. From a return investment perspective, again, it's anticipated this will return $350 for every dollar spent on that Diaceutics product here. It has really become part of their strategy, not just for this brand, but for multiple brands going forward. Again, as was mentioned earlier, the data infrastructure, the AI that we have put in place has allowed us to do these things in a more automated fashion. That's allowed us to therefore do daily feeds rather than weekly feeds.
This client actually upgraded to a daily feed during this process because they could see the benefit of getting into the data to their sales team's hands quicker so that they could engage with those physicians, those NPIs, physician numbers as quickly as possible. We have also seen cross-sell with this opportunity. As this drug was then repurposed and used in a different indication, we have seen that we've started providing that DXRX Signal in colorectal cancer as well as lung cancer. Again, one of the real benefits of DXRX being the main product here is the actionability and the return investment that we see.
We find that with that opportunity to upsell to daily, where it's a particularly competitive landscape like non-small cell lung cancer is, or where these patients are really hard to find and rare events, that upsell to a daily cadence and that cross-sell to different brands has really been one of those things that has driven the enterprise engagements that Ryan has talked about in the beginning. So I'm going to just switch over screen and take control for a minute. So if you give me one second while I do this. Hopefully, everybody can see my screen now. So this is our DXRX, My DXRX platform. I've already logged in just for speed. We use two-factor authentication to ensure that we have the highest levels of privacy. Here is my homepage. And again, this is a demo page here, so it shows internal Diaceutics things.
But if you're a pharmaceutical client, you'll come onto this page, and it will have your feed around what's happened in your project, how many potentially patients you've identified with Signal in the last week, if there's communication between the project managers and others around when deliverables are and presentations are. So this is a very active feed. It's also intermingled with, as Jill mentioned, the educational things. Here we've got our highlights from ASCO 2024. There are other things like our IVDR work in Europe and others. So this feed is tailored to each individual person as they log in and see things directly for them. But we're going to go to the dashboards, which is an individual section here. So the demo dashboards, again, if this is you as a pharmaceutical client, this would be a particular project, a particular brand, and they would see activity associated for them.
We're going to jump straight into the Signal demo. I think this should load relatively quickly as the data renders. Again, we use a lazy load methodology that just means that the data is active as quickly as possible for our clients while being efficient in compute power. I mentioned earlier that a lot of the hard work is in the back office of this data, actually bringing this data in, linking it together. As I said, tens of billions of rows of data, being able to do that compute power, put on the artificial intelligence. What we're showing here is literally that last mile as we try and visualize that data here. But first of all, I'll just go to the documentation side of things. Again, really important that we have standardized data dictionaries.
There's all the documentation to help people understand exactly what data they'll be looking at and how to define it. If we then go to what we call the NPI view, so this is the physician-level view, what we're doing here is looking at prostate cancer. We're looking at two different subtypes of prostate cancer. One is metastatic prostate cancer, looking at BRCA testing, but we can also further characterize those patients into castrate-resistant prostate cancer. Again, a particular cohort of patients with medical unmet need and really being able to link our data through claims and EHR to get to those subsets of patients is something that is not common in the industry. Being able to get to that specificity with the testing as well is really key.
So we look at here the physician volumes broken down by the two different types and the number of physicians with positive patients each week as this data is fed out each week. We can then go further and look at, well, what states were they in? What were their specialties? Was it a hematology oncologist? Was it a urologist? Again, particularly important stakeholders in the prostate cancer setting. Another thing that our clients really want to understand is, well, how many new targets are being identified? How many new physicians who we haven't seen in the data before are being identified on a weekly basis? And here we show the number of physicians that are being added to the database, particularly for, in this case, prostate cancer with BRCA positives here. And then ultimately getting down to who is that physician?
So their NPI number, which is a unique identifier for those physicians across all data sets and is unambiguous in the United States, allows us to say who they are, which hospital they're affiliated with, and what specialty they have. So this is the type of information that is at the sales team's fingertips. They'll look in thinking about their call plan. They turn their laptop on on a Monday morning. Okay, who do I need to go and see? And they'll see this list of physicians, again, being able to filter by state, region, city, all of those types of things to then say, okay, we know that this doctor has a new positive BRCA patient in our cohort that are of interest.
We need to go and talk to them and educate them and raise that awareness between positive biomarker result and the therapy and by doing that show that there is a better outcome for patients. And again, another list here just showing those NPIs that have already been seen in the data. And then which hospitals are they affiliated with? So here's just a summary in the last week of the top 10 affiliations. So looking at the hospitals, so again, thinking about those pharmaceutical reps as they plan their week, where do they do their site visits, who are they looking at? Just the last bit that I'll show you is just on this patient view, looking at, well, what's the volume of patients tested versus positivity?
Again, what is a positivity rate for this biomarker being BRCA1 and 2 in our metastatic prostate cancer cohort versus our castrate-resistant prostate cancer cohort? What does that positivity rate look like? How does it change over time and those things? And you'll see here on the left-hand side all the filtering that we can do. We can look at one subtype of patients or others. If we just go here and I'll filter quickly for perhaps California, again, you'll see that everything in this data set is dynamic and will load through. And we'll start looking at this data just for the state of California. And you can see all the information there just by California. So a very dynamic data set that allows you to it's very, very useful for our pharmaceutical companies. But again, let me reiterate, this is kind of that last mile.
This is the visualization of the data to be able to label these patients the way that we are, to be able to draw that conclusion from BRCA if that is pathogenic versus a variant of unknown significance. All of that information is down to the large language model that we have been developing and using the tokenization to link all that data, all the data infrastructure that allows you to get to this point, which we believe is a quite concise and clear picture of what testing looks like. But the hard work is getting that through the ETL data pipelines to be able to hopefully bring this into a clear, concise, and very insightful, and therefore actionable view to our pharmaceutical clients. On that note, I will ask Simon to come back in and also to take the screen back to show the presentation. Thank you very much.
Thank you, Jordan. And now a short introduction to Alasdair Milton. Alasdair is a partner in KPMG's U.S. Healthcare and Life Sciences strategy practice. A cancer biologist by training, he heads KPMG's precision medicine practice. He has over 20 years of experience in strategy consulting, specializing in organic growth and commercial strategy and portfolio optimization for biopharmaceutical, genomic, diagnostic, and health system clients, as well as private investors. Alasdair has also worked with numerous pre-revenue biotechnology companies to help them shape their equity story in preparation for capital raise. He also co-led the creation of KPMG's recent documentary, Connections in Precision Medicine, which explored the challenges and opportunities we face in precision medicine from the perspective of experts from across the precision medicine ecosystem, including physicians, pathologists, industry, and patients. Over to you, Alasdair.
Great. Thanks, Simon. And thanks to the Diaceutics team for actually asking me to present today. Good afternoon to everyone on the call. As Simon said, my name is Alasdair Milton. I'm a Partner with KPMG's U.S. Healthcare and Life Sciences strategy team. Just going to cover a few slides on our life sciences practice. I'll talk about why we see, from a KPMG perspective, precision medicine as, quite frankly, we describe it to our clients as the future of medicine. Then I'm going to wrap with just an overview of this really exciting strategic partnership that we've forged with Diaceutics. If we can go to the next slide, please. KPMG, as you'll know, is obviously one of the Big Four auditors. We've built a pretty significant presence in the life sciences globally. We're a global life sciences team across our audit, tax, and advisory practices.
We have a global network across the firm of around 6,500 professionals serving virtually every part of the healthcare and life sciences ecosystem, from virtually the smallest startup to the biggest multinationals. Within our deal, advisory, and strategy team, which is where I sit, we have roughly 600 people globally, including 200 in the U.S., who focus on deals. That's everything from helping clients do scans for potential M&A targets. Then once they've identified the target, we'll do the full suite of diligence work, everything from the commercial due diligence, the operational diligence, financial HR, etc. Then we'll do the full integration of the target. We'll also do separation work for clients if they need to rationalize their portfolio. On the strategy side, we focus really on helping clients think through paths to growth.
So whether that's through portfolio optimization or geographical expansion or some kind of new market entry. And I think from the top of the slide there, what's a little bit different about this team is the scientific depth that we actually bring and that's helped us make us a leader in precision medicine from the consulting perspective. I did my PhD in cancer research. Kristin Pothier, who leads life sciences for the firm, started her career sequencing for the human genome. And we have MDs and PhDs across all levels of our staff, from associate through partner. So that's allowed us to really build a dedicated precision medicine team that's now really excited to partner with Diaceutics. So if we can go to the next slide. So as we look at the wheel on the left here, you can see the various subsectors that we work in.
It's everything from digital to biopharma, a lot of the clients that were mentioned earlier on, med tech companies, diagnostic companies. We work with pretty much every one of the top 25 life sciences companies, majority of the biggest healthcare and health insurers, half the top 200 healthcare systems, as well as many of the leading multi-site providers. An important part of what actually enables us to bring innovative solutions to these clients is our partnerships. Whether it's with Salesforce, with Microsoft, and also now we're really proud to add Diaceutics to the list of partners who we're going to be in the market with, bringing these innovative solutions and the kind of forward-thinking to our clients that ultimately is going to benefit patients. Okay, so if we can go to the next slide, please.
So it's just an overview of our kind of ecosystem within precision medicine that we work with, our biopharma clients, all the leading biopharma clients we work with in precision medicine, diagnostic and life science tools companies, healthcare systems. We do a lot of work with commercial and academic labs, and a lot of work with private equity firms as well, who are increasingly focused on acquiring those targets in the precision medicine ecosystem, particularly around the pharma services space. If you think about the cell and gene area, it's been a very hot area for the last few years for PE looking at those raw material suppliers. We have a lot of experience across all different functions in these client types. So we don't just work with commercial teams. We work with R&D.
We will work with manufacturing, supply chain, medical affairs, a lot of work with the business development teams, and also regulatory. So we have folks who are experts in precision medicine regulatory aspects of the market as well. Okay. We can go to the next slide. So I want to transition to talk about the precision medicine market more broadly. And I mentioned earlier that we kind of see this as the future of medicine. If you look at the top of the slide here, historically, precision medicine was really all about helping oncologists select the right therapy for their patients. Now, if you move to the bottom of the slide, we're seeing an increasing focus in precision medicine across what we think of the precision medicine continuum.
So that's everything from risk assessment on the far left, what's the likelihood of developing a disease, what's the risk you develop a disease, think about BRCA testing for breast cancer, all the way through to monitoring on the far right, where there's a huge amount of interest from a lot of pharma clients right now in tracking those patients post-treatment for either looking at how the therapy is working, but also in terms of disease recurrence as well. And now, and I think this is what's really exciting for both of us and for Diaceutics, is we're seeing precision medicine move beyond oncology. Okay, we're seeing it in the likes of ophthalmology. We're seeing it in neuroscience. We're seeing it even in cardiovascular disease, and even in those kind of more complex non-genetic-driven diseases like immunology.
A perfect example of that is the fact that Merck paid about $11 billion last year. I think it was in April of last year for a company called Prometheus that has an asset for a number of different autoimmune indications, and they're stratifying patients using a companion diagnostic. So even in areas like immunology, we're seeing precision medicine really kind of enter those markets. And we did some analysis recently. What's quite interesting was if you looked at the top 10 biopharma deals by value last year, nine of those had some component of precision medicine. Okay? Another data point that I think really drives this home is that roughly 25% of all FDA approvals over the last seven years, if you average them out, have been precision medicine. And what fuels precision medicine? It's just what we talked about. It's just what was mentioned by Jordan. It's data.
It's EMR data. It's clinical data. It's the kind of biomarker testing and the lab-level data that Diaceutics has and is an expert in. So exciting times. And really, we're seeing this as the future of medicine, not just something that's limited to oncology. Okay? Next slide, please. But it's complicated, right? This is a complex market, particularly in the U.S. The U.S. healthcare system was not designed for precision medicine. And so there's a number of different stakeholders that have to be linked. As was mentioned earlier, the labs are an increasingly important stakeholder, being able to understand the testing volumes, the types of biomarkers that are being looked at, the modalities that are being used to test for those markers. And these are all really critical to our pharma clients and actually for diagnostic companies as well.
If you kind of think about some of those more centralized labs in the market, they need to understand testing volumes in different places as well. But it's a complex market. And so we realize that we're only going to ensure that we can get the right therapy to the right patient if we actually work with different partners to bring this ecosystem together. So just wanted to give you a sense of the complexity of the market, but how we view the partnership with Diaceutics helping to really enable connecting the dots with a lot of these different stakeholders on this slide. Okay. Next slide. And to that point, a couple of years ago, KPMG started on the road to creating a documentary series. Two parts. First part just launched a couple of months ago. The next part will come out early next year.
It's called Connections in Precision Medicine. We wanted to tell the story of kind of the evolution of precision medicine. Why do we see increasingly improved sort of survival rates with breast cancer, but not so much with lung? Lung has come a long way, but if you compare breast to lung, we're still far behind in lung. There's a social stigma to lung cancer, right? We still think that everyone who has lung cancer smoked. That is not true. There's an increasing proportion of newly diagnosed patients who have never smoked. We wanted to tell the story of health inequalities that we see with a lot of minorities not getting access to the right healthcare and precision medicine. We created this two-part documentary. You can see the names of all of the stakeholders who we interviewed as part of that.
We realized that if we really kind of look at that last slide and you look at the complexity, you have to have the perspective of all those different stakeholders. So we interviewed individuals from the payer, right? Key stakeholder in this ecosystem. We interviewed pathologists. We interviewed physicians from City of Hope, who were KOLs in both breast and lung cancer. We interviewed, obviously, the patients, who are a key part of this, central part of this, and their journeys, and the diagnostic companies. So our goal in this is really to help educate the ecosystem and help everyone understand that we will only be successful in precision medicine if we stop, I guess, pointing fingers at one another and we actually sit down and start talking kind of to one another, so. Okay. And I'm going to just wrap up with one more slide.
This is the one I'm kind of most excited about. So KPMG and Diaceutics, a few months ago, we formed a strategic alliance in order to do a number of things. We are going to help our clients together. So Diaceutics has got a very specific skill set that they bring to the table. KPMG has a very specific skill set that we bring to the table. We're going to be working on the strategic work together, that kind of corporate portfolio and brand-level work. We think there's opportunities in the deal space as well, as we do a lot of that diligence work that the Diaceutics data and expertise can be very helpful in, even in operational work that KPMG does as well. So KPMG has the global reach. We believe there's also a kind of what we call tactical to transformational work that we can engage in together.
We're going to engage across the entire ecosystem, not just with the biopharma companies, but with those diagnostic companies, those academic medical centers that KPMG has great access to, and a host of other stakeholders in the ecosystem that we're working with. We have proprietary data, we believe, is very synergistic. Then, as you've heard over the last hour or so, this team with Diaceutics, this team with KPMG, we have very deep precision medicine knowledge. We've been in this space for a long time, and we believe that by coming together, we can be real value-add even more to the ecosystem and kind of help our clients and ultimately make sure that we get those precision medicines to patients, which at the end of the day is the single most important thing. Okay. A nd with that, I will hand back to Simon.
Thank you, Alasdair. Now a short introduction to Ryan Hutto. Ryan is Head of Commercial Diagnostics at Pfizer Oncology and has a proven track record of success leading laboratory, biopharmaceutical, and medical organizations to achieve sales goals and sustain profitability. Ryan is a business development executive and leader devising tactical and strategic territory plans with expertise in corporate strategy, planning, and compliance, and has a reputation for developing strategic partnerships with functional leaders to bridge the gap between commercial sales and operational goals. Over to you, Ryan.
Thank you, Simon. Thank you to the team at Diaceutics for inviting me on the call today. It's my pleasure and honor to be a part of this. I fully believe that the future of precision medicine starts today. I think the team is probably all taking a deep breath about what I'm about to say.
But I've had a long-standing relationship with Diaceutics. They've provided us valuable insights along the journey that I've been on. I'll start with my disclaimer, first of all. The views that I'm about to share, the insights, the information, this is all based on my own experience and not that of Pfizer or Pfizer Oncology. With that being said, I'll take you through a little bit about what I do, how I do it, my why, why oncology, and then a little bit about the complexities when launching a product into a market and how Diaceutics is strongly positioned to meet the needs of the customer at the end of the day, and thus providing excellent care for patients at the other end of the funnel. That being said, I was with Seagen, otherwise known as Seattle Genetics, about 6 years ago.
Prior to the acquisition with Pfizer, I was in charge of building out a commercial diagnostics department, an end-to-end solution where we would have complete support from a pipeline funnel all the way through commercialization into the field. Part of the job came with understanding labs in the U.S. I know Jordan mentioned, and Simon or not Simon, Alasdair mentioned the complexities of the U.S.-based labs and the infrastructures that are in place and the testing modalities or whatnot that go into that. There's quite a bit to consider. From that perspective, as I was being in charge with building out a diagnostic department, I had to understand what is the lab landscape, how many reference labs are there, what are the academics, what are the capabilities, what are the community labs looking like.
All I had at that point in time was a list from CAP. So I turned to Diaceutics after meeting a number of different vendors and customers that supposedly can meet the needs and had the lab understanding. Honestly, Diaceutics at that point in time was the only ones that had the rich lab knowledge and infrastructure to be able to give me essentially a target list of the labs by market share, by testing modality, and biomarker. Then fast forward, they were the first ones to be able to initiate lab Signal alerts. I'll talk a little bit about my experience with that. But basically, my responsibility is from a peri-launch to post-launch approval. Years before a drug's approved, I'm involved to ensure the selection of a potential CDx partner assay and lab landscape for a biomarker is commercially viable on a global scale.
Once FDA approval happens, my department then takes action in the field to work with labs on biomarker awareness and unbranded education. Commercial diagnostics touches many departments and functions within the organization, from marketing, from medical, biomarker translational, market access, and patient advocacy. All these different respective functions are very, very important in finding solutions for patient care. And everything that we do, patients are at the heart of it all. So I've also been very blessed to have a very strong team of talented diagnostic experts who work with the insights, learn from Diaceutics, and others in the market, bringing education and awareness to those when it matters. And I will reemphasize when it matters is very, very important. The timeliness of this is crucial. So why? Why oncology?
Honestly, I say this to everyone I meet, and that is either from cancer touches us all, whether we have it directly or those we love or care about or our family members have been diagnosed or have had an inflection point with cancer. It happens to everyone. As of this year, about two million people are diagnosed with some form of cancer in the United States. Only one in 15 oncology drugs studied in phase one clinical trials will actually make it to market. In 2017, analysis showed that the estimated cost of bringing a single cancer drug to market was around $648 million. As of December of 2023, there were approximately 224 cancer drug approvals across 119 individual drugs in the United States. In the oncology sector, patients are very ill and can progress quickly through lines of therapy, depending on the stage and type of cancer.
It's important to note that as progression occurs, providers have the right information on hand to make a timely, informed decision that best suits the needs of the patient. In oncology, there is a very high sense of urgency. There are more and more precision and biomarker-directed therapies in the market, such as technology with ADCs, antibody-drug conjugates, which are like heat-seeking missiles that are intended to treat or, sorry, intended to target and kill tumor cells while sparing the healthy ones. The market in general has moved to a targeted personalized therapy. In order to find the patients you're looking to treat, you have to test for them. It's a crucial elementary part of the cycle.
So what we're trying to do when we go to drive launching a biomarker-driven product, we're looking for rapid test adoption and biomarker awareness, increasing testing rates, opening the funnel for patients to receive the appropriate therapy at the right time. And for patients in oncology, time is life. Every moment counts. Ensuring accuracy, efficiency, and timeliness are all critical components when launching a drug. We have to get it right the very first time. You heard about the new drugs that are being approved. It's fantastic for science. It's fantastic for patient care. But in order to get access to many of these drugs that have personalized medicine and biomarkers that are attached to them, patients have to be tested. Physicians have to understand what the test means and what to do with it, and also how to order it.
This is really how I see Diaceutics leading the pack as far as the understanding of labs, the workup, and the workspace that it takes to actually do this accurately and correctly. They've identified many gaps within the testing lab landscape and helped my team exponentially move things through and help educate on those gaps and providing better patient care. Oncology and science have progressed at light speed, and now there are biomarker-targeted therapies that show high patient responses in various cohorts. These are the type of patients we are seeking to impact with breakthrough therapies. We're looking for a very specific bunch. Earlier, Jordan, I think, mentioned about PNH patients, right? Those are ultra-rare, hard to find, needle in a haystack. You've got to get there quick. You got to know they're there. Well, the same thing goes with biomarker treatments for cancer care.
We've got to be there quick before a patient can progress on line of therapy, and also so the physician has the opportunity to put them on the right treatment at the right time. So while some companies are also focused on claims information and around physician prescribing habits, Diaceutics has opened up the hood. They've looked at the lab and what actually goes into ordering a test and what that actually means for finding an actual patient and then bringing that back up. So we're able to track the full, I would say, patient journey continuum through the testing paradigm because of the information that they've been able to provide. So I'll stop for a moment and just briefly talk about the lab Signal alerts and how, when I was introduced to Diaceutics, what we thought we could do with those.
We started those on one of our franchise products. It became a very much high-valued asset and success in the field. It helps with tailoring the messaging at the right time to the right physician and giving them all the options on the table, right? So that's worked very successfully, and we've rolled it across numerous franchises thereafter. So I see the information that Diaceutics is providing is very timely. It's very needed. They're meeting a high unmet need with this information. And the fact that they're able to now marry that with Rx Data and increase the Signal alerts from weekly to daily, I mean, honestly, it's given them a leg up from what I can see. 500+ labs in the U.S., 1,000 globally. That's a pretty big footprint. And that's what we're looking to do.
We look to partner with vendors and partners to actually see the holistic picture and have as much data as possible that we can pull from to give us the real-life scenarios of what patients will go through and what physicians will see and then how labs work up patients. So the lab landscape, there's lots of testing gaps. I'll talk a little bit about kind of some of the challenges with the academics, communities, and the reference labs, and then take you through kind of the different modalities or types of tests that are used in the field. So first of all, academics, I think of those like a Costco, right? They have everything. It's a one-stop shop. They have everything under their roof. They have their own lab. They have their own specialty communication pathways, EMR, informatics. So they have everything in one stop.
You look at community; they're more rural, more outskirts. They're treating the general population base. They're more like, I would say, a grocery store. They're still good. They're still needed, but they don't have as many resources. So they look to other partners, other reference labs to fill that need for the lab workup in areas that they can't do it in-house. So they send it out, and they'll send it out to a Quest or a NeoGenomics or LabCorp or Caris or whatnot. Within the reference labs, you have national reference labs, you have regional reference labs, and you have local labs. The utility of each changes based on the technology being used and what's needed for the workups. So for example, the different modalities of testing that exist could be IHC, FISH, Flow, PCR, next-gen sequencing.
Within next-gen sequencing, it's a whole slew of other things where you've got large and small panels. You've got mutations you're looking at, amplification. You can be doing liquid or tissue. You can be looking at somatic or germline tests. There's really no straight and narrow road in lab. And I think that's really my point of this is trying to let you guys know that lab is a very complex situation to navigate. And so for Diaceutics to have the information, that's one thing. But to be able to make sense of it all, that's a whole nother thing. And I think of it like a good winemaker. They have years and years of experience. They know what works, what doesn't. Well, the same thing goes with Diaceutics. They have experts there that are in the field that know what's going on.
They have relationships with labs and partners. They have deep, rich experience from the C-suite leading this. So they can bring it all together to make sense for pharma and help us seal up the gaps and the blind spots that we're not seeing. So as more and more companion diagnostics go to market and as more, I would say, CDx-agnostic or biomarker-driven therapies go to market, there's going to be more of a need. There's going to be more of a need to understand the lab workup and the paradigm between patients being tested upfront and then being diagnosed. Several different tools that we've utilized from Diaceutics along the way that's really helped, I would say, navigate us to better waters has been the market assessment, looking at the relationships of payers, of patients, of physicians, looking at guidelines and regulations.
I will also note that Diaceutics has taken a strong stance in being the voice for a lot of labs and a lot of pharma with the ongoing regulation changes. So lab landscape analysis, identifying specific gaps in testing where patients are being missed. And that might be from the biopsy. That might be to the collection, the reporting. It might be to the workup. But they have their lab landscape analysis. They can take it from the beginning to the end of the patient journey from a lab perspective and show you and show the pharma, "Here's where you're missing the majority of your patients." And it shows the gaps. And then we can work to fill those gaps in the market ahead of a launch, taking away a lot of headache and issues before they become a big thing. They also have the testing rate trackers.
So as you're out there talking about to physicians around a new biomarker-directed therapy or labs talking about, "Here's a need to test for a new biomarker or here's a new CDx that's now launched," you can also track the testing rates through their lab landscape analysis. So you can see the uptake on that. You have your lab Signal alerts, which I just touched on. It's a fantastic thing. You can do it weekly, daily. It's tokenized, de-identified. They have a global network of labs of over 1,000, 500 in the U.S. The other thing that Diaceutics has been decided to have been doing is market case studies, white papers, helping to identify where biomarker challenges are coming up at. So they partner with pharma to help educate the market. And then finally, where we've also utilized Diaceutics is expertise and consultancy.
They have experts that are very much aware of where biomarkers have fallen short being launched with a CDx, and that's a novel CDx or not a novel CDx. They can help identify pain points early on and then make solid recommendations on where to fix those gaps. Finally, Diaceutics is at the forefront of personalized medicine. They have a full offering of solutions for pharma and biotech looking to ensure that all elements in a launch are considered, planned for, and then executed on. What sets them apart from others is their complex lab network and partnerships. They're data-minded scientists who can break down most challenging scenarios and co-create solutions. Having information is one thing. It's what you do with it and how it's delivered to make sense that changes the game.
At the end of the day, patients are at the center of everything we do. Information is knowledge. The more we understand, the better we can be at ensuring each patient gets access to the right therapy at the right time. At Pfizer, our mission and our motto is to outdo cancer. Back to you, Simon.
Thank you, Ryan. We will now open up the webinar for a question and a Q&A session with our panelists. Please click the raise hand button or use the Q&A button to type and submit a question. We will endeavor to get to as many questions as possible online today, but should we not get to all questions in the time we have remaining, please do follow up with us at investorrelations@diaceutics.com if you wish to discuss anything raised on today's webinar in more detail. Given the number of people we have online, I would ask our covering sell-side analysts to restrict your first turn to two questions and then go back in the queue if you have more. We will now take our first question from Christian Glennie at Stifel. Christian, please unmute your line and go ahead.
Hi. Good afternoon. Thanks all for the presentation. First question then would be around just trying to drill a little bit more to really understand, ultimately, I guess, how important is precision medicine really to pharma and specifically how important is that in terms of the development strategy and the commercial strategy as these companies, both in pharma and biotech, look to progress their therapies?
I'll take this one, Christian. Thank you. I think I'll refer back to initially some of the quotes from my dear colleagues on this call, Alasdair and Ryan. What you said, Alasdair, 25% of all FDA approvals, precision medicine, and growing. And nine out of 10 of the large deals of the last year, was the last few years, have had a precision medicine component. So it's very clear that, and as Ryan said, this is the future of medicine, and that future is here now. There are challenges, particularly around commercialization. And I think we are, as an industry, and as we work with our pharma colleagues, partners, customers, starting to get on top of those challenges, particularly around trying to find those difficult-to-find patients. But the science is driving this. The patient story here is what absolutely should be top line.
Ryan spoke very eloquently about his purpose and why oncology is where he is focused. I'll broaden that out to precision medicine. Anything we can do that gives a patient a higher likelihood of response to a drug for whatever their disease is is the right thing to do. As I said, I think there's a lot of pressure, not just from the scientific community and obviously advances there, but also payers, regulators, coming to a point where the expectation is that we need to understand these patients better before we treat them. We need to make sure that we treat as we look at a nearer value-based care and understand really how we are benefiting patients and what that means in terms for potential return on investment. It's all driving toward a more precise direction, and precision medicine is the solution. We have it. It's there. We are very much ready to continue to deliver on our promise.
Can I add one thing too? Ryan, thank you for sharing.
Please do.
The one thing I'll also say is access to education and new information. That's essential, right? And from the world of an oncologist, just I'll speak in the oncology world, that is very timely and necessary. And so a lot of the depending on where they're located, whether they're community-based oncologists or academics, some may have information at the ready and others may not. And as science is evolving in leaps and bounds with new technology, new products hitting the market, it's really hard for oncologists to stay in the know. And so having the type of informatics and information that Diaceutics can provide to the market really helps us tailor our timeliness, our messaging to really impact patient care at the forefront and get them on the right drug at the right time.
That's very helpful. Thank you. And then my second one would be around, I guess, just to understand a little bit more around the potential new opportunities. I know there's a lot to go for within oncology, but you talked about the potential for going outside oncology, the fact that you're actually collecting 75% of your data is actually non-oncology indications. How do you start to go after that market? And then related to that, the sort of the other customers that you said are non-pharma, non-biotech, what are some of the examples of those? And what's the sort of opportunity there?
Yeah. Let me triage and answer to that. I'll answer a bit, and then I'll bring in Alasdair, maybe you talk too. You mentioned there are a lot of opportunities in ophthalmology, immunology, etc. Maybe just talk a little bit about that. And then, Jill, if you come back in about how we are trying to move into those other areas. The precision medicine story has been an oncology one initially. I think that's fair to say. And it's still strong. And I would say absolutely now the predominant model in oncology. As we move into other therapeutics, it brings a whole new set of challenges. As we think about more general diseases, there are plenty of much, much larger populations.
Oncology, while it touches us all, to Ryan's earlier point, and is obviously something that we're all very aware of, in the grand scheme of things, it's still on the rare side of disease compared to cardiovascular disease, diabetes, things like this. So when you have a precision medicine going into one of those huge therapeutic areas where you don't have 2 million patients a year. You have 200 million patients a year. And to test them all and stratify a population where you still might be looking for only a couple of % of patients, but you're having to test potentially 100 million patients to find two, all of a sudden, everything gets bigger and more challenging for an industry and for an infrastructure that's not necessarily set up for that. So there's a journey ahead for us all in precision medicine.
We have the data now that can help us illuminate and target. I also think we have a lot of learnings from what we've done over the last 10, 15 years as an industry in oncology. Sometimes there's a view that those learnings are very oncology specific, but they're not. They're actually very much applicable to other disease areas. Alasdair, do you want to just talk a bit? You'd mentioned some other areas that are particularly front and center right now in terms of the push on precision medicine.
Sure. I mean, there's a lot of these rare genetic diseases. I mentioned ophthalmology, a lot of those monogenic diseases that we see in ophthalmology. I mentioned there was nine of the top 10 biopharma deals last year that by dollar value that were precision medicine. And a lot of them were outside of oncology, as was just mentioned there. This is not something that's limited just to oncology. We had the AbbVie Cerevel deal, right? They're essentially stratifying patients based on disease phenotype, a little bit different, but still precision medicine. There was the Biogen-Reata deal, which is for Friedreich's ataxia. There was the, I think, the Astellas-Iveric deal, which is an ophthalmology. I mentioned the Merck Prometheus deal. There was Roche-Telavant. So these deals that pharma's doing are very much focused on expanding the aperture of precision medicine beyond oncology.
And look, I think from a pharma perspective, if you can identify those patients and you can kind of own those patients, quote unquote, it's better than taking a mass market approach, right? If I know I can find those patients through a CDx, through biomarker testing, better to have that smaller patient population that I know I can actually find and kind of get on drug rather than kind of have a more scattergun approach, if you like, where I'm trying to find everyone. So it's earlier days in other disease areas. For sure, oncology has been the leader for precision medicine for the last decade, two decades. But we're definitely seeing a lot more activity in other disease areas. Neuroscience now as well, right?
If you think about the development we've seen in the last couple of years in the neuroscience here, we've seen a lot more deal activity in that space. I think that's indicative of how we're kind of viewing that as probably the next frontier in precision medicine. Exciting times.
Okay. Thanks, Alasdair. Jill, maybe just talk a bit about how we're approaching that, how we're trying to build, especially in those clients where we already have a stronghold in oncology, but maybe wanting to move sideways into their neurology franchise or otherwise.
Sure. Just before I do that, it may be of interest to everyone to note that actually Diaceutics, while globally recognized as a precision medicine company, actually started in precision medicine looking at diabetes. So our early beginnings were in other non-oncology areas. But think about it from a client's perspective. Today, large global pharma companies may have a rare disease or another precision medicine drug whereby the physician only sees a patient once every year or once every two years. It's not something that is an easy model for our pharma clients to find those patients and ensure those patients get the appropriate treatment. And we're able to help them find those patients through the Signal that Jordan presented. But more importantly, we're able to engage with those clients because we've got our business partners out working across our accounts.
Our key account managers can work with our precision medicine oncology team, but our business partners are free to really go and explore some of those rare diseases and non-oncology precision medicine. As Alasdair said, neuroscience is really interesting today. We're just back from ASCO. And many of the clients that we met at ASCO were talking about their neuroscience portfolios. And that's a really interesting area for us to get into in terms of our precision medicine. I think it opens up a stream for us that is new and exciting and is really where precision medicine will be in the future. And we're set, poised, and ready to act. So it's a really exciting time for us. Thank you for the question.
Thank you, Christian. Hopefully, that addresses everything. We will now take our next question from Chris Glasper at Singer Capital Markets. Chris, unmute and go ahead.
Hi. Yeah, thanks, Simon. A couple of questions. First one really around Signal in particular, which obviously is your killer application at the moment. It looks to be such a no-brainer for adoption given the return on investment that customers can generate on the back of it. So I guess the question is, why are pharma not falling over themselves to adopt this product yesterday? What are the key barriers to adoption, and how are you overcoming them? And then the second one is, well, we can come back to the second one.
Yes. I'm glad you paused the second one because I would have forgotten it. That's so good. I have to write it down. Let me take the very initial part of that, and then I'm going to pass to Jordan. Chris, thanks for the question. We are, for all intents and purposes, a challenger brand here in that we have a lab data capability, a different type of data that is new. You have those who have adopted it and are along that adoption journey. The likes of Ryan Hutto on the call here is absolutely out the other side of that and understands the true value. For other customers, they're still using existing data insurance claims or things.
So part of our mission here is to get out there and extol the virtue and the opportunity of a different type of data, which is different and challenges the current status quo in some instances, in some use cases like we described. So that's part of the adoption. Where we have clients already using it, very few of them ever turn it off. So our renewal rate is in the high 90s%. We're going to publish a renewal rate. It's part of our H1 update in a few weeks' time, about a month or so time. But it's part of just getting in there. They maybe don't have a budget for it initially, so we need to convince them, show them why. And then once we get in, then it's pretty much runs from there. And I'd say that's the kind of largest prior.
Jordan, would you have a view on that? Do you want to add anything?
Yeah, thanks, Ryan. I agree. For me, there's two elements of this. One is those clients that are perhaps more traditional in nature using claims-based and how they do their call planning, and they're doing a scheduled system rather than a precision system where you would need lab data in those. I think they're becoming less and less overall, but some of them do still exist. The other part of this may be the actual infrastructure of the pharmaceutical company to be able to process that data internally at the speed needed to be able to then get that to their field team on those things. Again, all things that we are supporting clients with are easy ingestion, making sure that it's a seamless integration to theirs. But sometimes those pharmaceutical companies simply just don't have that data infrastructure there as well.
Those are the two big barriers that I would see that we overcome. And we are getting there with each and every brand. And it's certainly something we are educating Jill's KAM and business partner team on, is how to overcome those barriers to that sale.
I can add a little flavor to that too as well from my side. I know it took us a little bit of a while to buy in on the concept that this is actually real data, that we could actually act on it, and it was accurate and as timely as you said it would be. I think we're all creatures of habit in general. So you go with what you know. And I think establishing a proof of concept that you can measure and get results back from, and then echo that across the organization of the benefits of having it, I think that speaks louder.
I think for pharmaceuticals, depending on the nature and the scope of how big or small it is, it can be a little more of a complex sale only because you've got marketing in one silo, you've got sales in another silo, you have data and informatics in another silo, and what you need is all of them talking and hearing about the success of this. And so typically, it would probably be marketing, I would say, that would typically drive this. And as soon as they try it, I think the value is easily recognizable because it is different from claims. It's not reactive. It's proactive. You're changing the game and the landscape for messaging to providers, so.
Thanks, Ryan. Right. Thanks for that. That's really helpful. And then secondly, something we've touched upon in the past is how you're addressing the non-U.S. growth opportunity. Obviously, the business is largely set up to tackle the U.S. market, but there's an equally big market outside the U.S., if not larger. Again, maybe one for Jillian, how are you structuring the commercial teams and how you're approaching the non-U.S. opportunity here?
Yeah, absolutely. Let me begin by saying the opportunity that we have outside of the U.S. is equally large, and the data that we have outside of the U.S. is equally impressive. So if we take a look at how our team is structured, our business partners are well placed to go and work with the global parts of organizations where we've got, leaving our key account managers in that established U.S. precision medicine field. As we expand that team, we're also able to then adjust our account team size based on the need or the opportunity in the clients that they work with. So we can again scale and add more business partners who are required to work with those global teams.
One of the things that we find really helpful, and Ryan and the team at Pfizer have seen it, where we can begin by talking with one group and then move and speak to another. Those introductions from a U.S. approaching you either a U.S. marketing team to a global marketing team are really important to us. So kind of working together as an account team gives us a really good opportunity to do that. Our lab network in Europe in particular is strong, and we often get asked to do very bespoke small projects. And those in turn can be the door opener to something much larger. So we're very aware of it. We're very focused on it, and we're building to ensure that we can capitalize that as much as possible.
Thank you, Chris.
Thank you.
And we will now take. Sorry, go ahead. We'll now take our next question from Hayley Palmer at Canaccord Genuity. Hayley, please unmute and go ahead.
Hello. Can you hear me?
Okay.
Wonderful. Thank you so much for the presentation. Just the first question, please. Looking again at how you might expand your opportunities, but I guess I've got in mind the continuum of precision medicines that was on Alasdair's slide earlier. There's obviously a really significant opportunity in terms of along that continuum from the risk assessment side through to diagnosis and then monitoring at the end. How do you see that opportunity to expand? And I guess, how do you fit that into your product roadmap? Is that a route that customers are kind of guiding you towards as well along the continuum?
Yeah. Thanks, Hayley. Great to have you on the call. I'll take this one, if I may. We talk a lot today and in general about the opportunity around the DXRX Signal and some of the other things we mentioned today, testing the T racker, etc. But we have been building, and ostensibly, a large part of our business starkly has been targeted at that pre-launch phase. Really, the goal for us as a business is to have a suite of services that we can switch on with a customer pretty early on in their development, more or less around the start of a Phase 2 trial. That's where the biomarker or the diagnostic stratification is likely to be implemented as a strategy where they're thinking about diagnostic partners that they may want to work with, lab partners, etc.
We have effectively a suite of services that can be provided as an end-to-end solution from that point right now through to multi-years after launch. That's what Signal has enabled the post-launch piece. Historically, our business more or less got to a point of launch, and then it was handed off to commercial teams and a sales and marketing job from there. And so that's what we're building. And the entry point for that can differ. And we're very open to having multiple ways in to pick up a brand anywhere along that. The earlier, the better. And that's why it's really important for us also to have a global solution because at that stage in the development of a new therapy, it's typically driven out of the global pharma organization. They're looking for global solutions. So that's global market research, global insights, global landscape, global partner.
That really talks to the global nature of our business and I think sets us aside. Then as you get closer to launch, that's where it's really important to have the company-level data and the company-level information as those company teams get brought in. Working with partners like Ryan on this call, who represents a global organization, but ultimately has internal stakeholders himself that he services in terms of the country teams, large U.S. team, but also European teams, etc., from big markets like Germany that want a German solution, a German-shaped and appropriate for a German market, which is very different from a U.S. market. Our setup here, as I said, global in nature, is to allow for that because we know that the system works differently in different parts of the market. So it's not just about having that end-to-end solution.
It's also about having nuances within that that are suitable based on the geography that we're operating within. Anyone from my team or anyone else on the call want to add anything to that? Okay. Next one, Hayley.
Sorry, I think I went back on mute. Apologies. Thank you. And then as precision medicine becomes increasingly important to the pharma industry, I'm wondering how that's evolved in the competitive landscape. I know, Ryan, earlier you mentioned that Diaceutics was the only company to be able to offer those Signal alerts and to have that kind of rich infrastructure of lab data. Previously, you just get a list of labs. Is there any kind of evolution in the market in terms of the competitive landscape? And I guess how far ahead do you think you are?
Yeah. Maybe first I will turn to you, Jordan, if you're comfortable. And Ryan, if you wanted to add anything to it, feel free. If you don't, that's okay as well. Jordan, do you want to jump in?
Yeah, I will do. Thanks. So there are a number of competitors that are coming there from different angles. There are laboratories that use their data, but they have a single laboratory, single site coverage list. There are claims providers out there that provide large sets of claims data like IQVIA and others. There's your EHR data providers like COTA and other things like that that are doing different studies. But there's no one coming at it from that diagnostic precision medicine angle like we do, being able to combine all of those different data sets with that tokenization, including social determinants of health, really with a focus on precision medicine. Because we do have to think about precision medicine slightly differently than other diseases around understanding the diagnostic pathways of those and the intricacies of the lab data compared to EHR data and others.
So I'm not going to say that there's no competitors out there, but there's definitely not one competitor that takes the angle that we do and has that differentiation in the data and our precision medicine expertise. And then the global nature of what we do and being able to have data in Europe and the US out there. But perhaps the best validation of that is Ryan to say that as well.
Yeah. I would say that over the past five or so years, things have evolved a bit in this space. I think labs have recognized the value of their own informatics and have created departments to sell it individually. I think from an efficiency perspective, pharma would prefer to go with an aggregator that has a partnership with a large net of labs and understands what to do with that information. A lot of labs will sell the information, but it's about how they deliver it to pharma that can empower the field teams or marketing teams from that perspective. Diaceutics has had a track record of building up and scaling with all the partnerships that they've developed over the past five or so years, from my knowledge. They are the number one, I think, the leading provider from laboratories and informatics.
I can probably count on a hand, just a handful, to have a few different lab offerings that don't compare in scope and scale to that of Diaceutics. So from that perspective, I believe that they're leading the market also. I've also heard from a lot of my counterparts in the industry that Diaceutics is a preferred name. So I think for me, I like, I enjoy working with Diaceutics, but at the end of the day, I have to do what's right for patients, and I'm going to go with whoever has the most data and has the most utility behind the data. And today, that company is Diaceutics from my perspective. Thank you.
Thank you. That was really useful.
Thank you, Hayley. We'll take our next question from Natalia Webster at Royal Bank of Canada Capital Markets. Natalia, can you unmute and go ahead?
Great. Thanks, Simon. I have a couple of questions. So I'll just start with questions for Jillian and Alasdair, and I'll jump back in the queue if I have time. So firstly, Jillian, you said the addressable market's much larger than what you're currently achieving. And I know that you say you can achieve GBP 1 million per year per brand at the moment, and you're looking for sort of GBP 3 million per brand opportunity by 2030. How do you see this progressing over the next 6 years and sort of how much of this is reliant on getting new products versus your kind of cross and upselling of existing solutions?
Within this sort of centralized product development strategy, I appreciate that this will take some time to develop, but are there any obvious gaps in your offering that require solutions that either you or pharma customers have identified so far?
Yeah, let me dive in, and then Alasdair, and then perhaps Nick would also want to come in. When we look at what we're doing today, you can see with Signal that it's a very obvious entry point for our clients. Our current base of business is not insignificant, but there's a much wider base to go at. If I look at some of our enterprise engagements, for example, we started out offering one Signal and very quickly added on Signals 2, 3, and 4. We met most recently last week at ASCO with some of our enterprise clients who told us that they had new products coming to the market, and they wanted to start new Signals as soon as those products were nearing their registration dates. So there's a clear opportunity to continue and grow and deliver more from the clients that we've got.
Our approach with our business development team to add in new smaller pharma and biotechs that are entering the precision medicine space still gives us a long way to go in terms of adding new clients. That's before we've cross-sold and upsold what we've got. When we look at our product pipeline, we've got a large number of products that take us right from the very early phases of clinical development for our pharma clients right through to the end of commercialization. There isn't obvious gaps in there, but there are ways in which we can enhance those products. The work of the product team will be to determine how we best modify and present those products to maximize the opportunity that we have in the market. That's really where we're focusing on first and foremost. Jordan's also shown and demonstrated the dashboards.
We're rolling those dashboards out to all of our clients. Those dashboards in themselves will help us explain to clients some of the other insights that their data shows them that will help us in turn then to position some other products alongside. And I feel that we've got a relatively open runway, certainly out for the next 3-6 years, as you described. Alasdair, do you want to come in? And then Nick, if you've got anything to add.
Nothing to add from my side if Nick does. Otherwise, I can take the second question.
Yep. Happy to. So just to add to that, and thank you, Natalia, for the question. So as we published recently in our full year results for 2023, the average revenue per pharmaceutical brand that we currently generate is around about GBP 380,000. A significant amount in its own right. But when we compare that in terms of pharma's overall spend on marketing and commercializing a drug asset and in terms of our overall deployment of our overall services, it's actually quite a modest amount. You reference GBP 1 million per brand available revenue to us at this point in time. And yes, we are able to potentially extract that from one pharma brand just deploying all of our services. But it's worth noting that pharma brands that actually take all of our services at one point in time and continue to do that is relatively small at the moment.
So where Jillian was explaining about the land expand opportunity, where we already work with a brand and a brand team, we may need you to be deploying one or two of our products. So there's the opportunity there to talk to them about the lab networks, testing rates, other products that we have, advisory, and layer in those to help with the commercialization challenges. Ultimately, we believe if we were to deploy all of our current products and services to one brand post-launch, say for a period of around about five, six years, that would be somewhere in the range of GBP 2 million-GBP 2.5 million per year in revenue to Diaceutics. So there is the possibility at this point in time to realize the sort of levels of revenue that you mentioned.
I think the challenge for us as a business is to continue to educate the market and our pharma customers around our capabilities to deploy more of those services.
Great. Thank you. Can you still hear me okay? Great. Yeah, that kind of leads me on to the question for Alasdair, actually, because I just wanted to ask if the sort of types of solutions that Diaceutics is offering is something you've experienced customers in the market sort of specifically looking for in the past, or if sort of the issues within precision medicine and the potential return on investment that Diaceutics' solutions can offer is something that you think you'll need to sort of more proactively raise attention to.
So I think clients need data, right? As Ryan alluded to earlier, that the market's very complex, very fragmented. It's a challenging ecosystem to navigate at the best of times, even if you're an expert in the field. And I think that the Diaceutics data fills a huge hole, as Ryan alluded to earlier. And what we hear from our clients. At KPMG, we tend to do a lot more of the kind of corporate-level strategic work rather than the brand-level tactical work that Diaceutics does. But Diaceutics, from our perspective, is a leader in that lab ecosystem, and we hear the name across all of our pharma clients. So as far as we're concerned, as far as I think our clients are concerned, they're a leader in the space.
Thank you, Natalia. Is that all?
I do have one follow-up question if I have time, but happy to jump back in the queue if not.
Okay. That's great. Thanks. We'll take our next question from Dr. Julie Simmonds at Panmure Gordon. Julie, please unmute and go ahead.
Can you hear me?
I can hear you.
Perfect. Yeah. Just wondering, in terms of sort of we've been talking a lot about what you do in sort of the helping on the marketing side and then also what you do in helping at the early stages of the research side. I'm just trying to understand how many of the products go through from one end to the other and how much is sort of the pharma companies coming in at either at the beginning of the process or when they're about to launch? Or is it a sort of continuum, or is that where you're trying to get to? Does that make sense?
Yeah. Nick, why don't you take that one?
Yeah. No, absolutely. Hi, Julie. So I think it varies. So if we think about when we launched a platform and really the data offering, that was only really in 2021. So as Ryan mentioned, before that point in time, we were very focused, I'd say, two years before launch and then maybe a short period, maybe a year after launch. And what the platform, things like Signal and additional products have allowed us to do is extend the timeframe which we can work with our pharma customers. So when I say it varies by customer, it really varies depending on how long we've been engaged with the customer or the brand team, when we're able to talk to them about the opportunity.
Obviously, as Ryan said, the earlier we can get in, then it tends to be quite a sticky offering, so we're able to stay with the pharma customer for longer. And now having subscription services, we can stay with them year on year and help them launch their therapy. So I think that there's more for us to do in terms of being able to cross-sell into more brands and interact with them earlier in the process.
Excellent. Thank you. And then I was just sort of wondering about sort of you were talking earlier on about precision medicine, particularly in oncology, being particularly siloed in the States. Does that cause a sort of problem in terms of trying to get out of that once if that's your sort of entry point? Are they the more difficult ones to move on, and it's easier if you're sort of starting somewhere else with the client?
I'll take that one. And again, anyone else, feel free to add to it, Alasdair or Ryan. We're talking about global pharma, huge organizations, Julie. So I don't think it's specific to oncology or it's any harder than the others. I think it's a lot of our customers set up an oncology part of their business because the way oncology is developed and ultimately marketed and treated is different from other perhaps general disease. But equally, you'll have similar for neurology. You'll have similar for big franchises within. So I think it's more nature of how pharma are set up. And of course, that changes company to company. But I think what benefits us here is that we have the testimonial, the evidence, and the customer context of our existing customer base.
I think we're getting better at leveraging that and using that to help articulate our value in other parts of their business and obviously led by where precision medicine's going, etc. So just to recap, I don't think it's an oncology challenge or it makes it more challenging. I think it's just a virtue of what is a very small company like Diaceutics trying to work with a massive company like any one of our big clients. Alasdair or Ryan, maybe Alasdair from one massive company trying to work with other massive companies, I imagine it's a challenge as well for you guys.
Yeah, it is. I mean, big pharma is so siloed. I just echo what you said that there's groups that even within oncology don't necessarily interact with one another on a day-to-day basis. I think it's just a case of kind of navigating these large matrixed organizations.
Yeah. I think from my perspective, at least in oncology right now and from my experience, you look at the global markets of where you want to make an impact, but you also look at the U.S. because typically, or I will say from my experience, we've launched in the U.S. first or gained approval first, and then outside the U.S. follows. And so our unmet need begins in the U.S. And it's very tricky to navigate. Many complexities at large. You've got many pathways. You've got EMR systems. You have ways of working and streamlining the way diagnostics, workups, and therapies should be delivered. And so from my perspective, Diaceutics has an immediate need to fill. And so that's why I think at least U.S. makes sense.
Thank you very much, Julie. I hope that answered your questions. We will now take a question from Colin Smith at Capital Access Group. Colin, please unmute and go ahead.
Yeah. Can you hear me?
We can hear you.
Fantastic. Just coming back to the addressable market point that Julie made and putting it in the context of the amount of development you've put into the DXRX platform, both in its own capabilities and the additional volumes of data you've added to it, and also the significant changes you've made to the marketing organization. My question really is, is the future more about marketing rather than the data platform? That'd be my first question.
Let me take that one. I think it's clear. Thanks, Nick. Yes, to answer your question, we feel this business is getting to a level of maturity where we have scale, we have the data, we have the data pipelines, we have a customer footprint that we can build upon. Our key goal and our drive now is to get out and tell this story to more people. Okay. I think it was Chris earlier mentioned, what does this look like beyond oncology and how do you go there? This is about putting boots on the ground and building our marketing presence, building that testimonial. I talked about the Challenger brand and that you see that emerge in our new marketing strategy that's coming. The core thing that we need to do there is show people the difference, show people why this is better.
It's not something that we've shouted about enough historically. To your point, going forward and marketing this differently, but shouting about the opportunity is front and center for myself and Nick as we look to how we guide the business forward.
Thank you. And then second question is, of course, the structure of the U.S. and European markets, that's very different. I think about much more central position in Europe than what you might have in the U.S. Is it easier to push this whole ethos of precision medicine through in Europe or not? And at the moment, I understand Signal isn't a daily product in Europe, but I'm just wondering when it might become one.
Yeah. Again, let me take that one. I know we're almost up on time. Apologies for that. It's a different opportunity in Europe. It's a different opportunity for our customers. Health systems are, in general, very differently set up in Europe, even down to the fundamentals of the drug even available and reimbursed in some markets. That's not always going to be the case. We have to navigate it differently. The precision medicine adoption is strong in Europe. It's well understood and absolutely endorsed. In fact, where healthcare markets are squeezed from a budget and cost perspective, actually, precision medicine presents the future. While the drugs might have a cost attached, not having that trial and error approach is ultimately beneficial to the system. It can be very decentralized in Europe, so you really need to know your markets.
You really need to know how those markets work and the need for pharma to partner and really leverage the types of data we have, etc., is strong. I think that's the direction. This business will always be U.S. first and precision medicine and healthcare in general, typically, as Ryan said, we launch first in the U.S. and we go from there. That's the story for Diaceutics. There is a compelling story for Europe as well.
Okay. That concludes the Q&A session nearly on time. And apologies if we didn't get to you, but I will follow up offline or please do contact us at investorrelations@diaceutics.com, and I'd be happy to pick up anything that we missed. Ryan, we'll hand back to you now for closing comments.
Yeah. Again, just thank you all for joining us online today. We hope you found the event useful. Please reach out if there's anything that you'd like to discuss in more detail. We're very happy to revert. We hope you feel this was successful and informative. We plan to run more similar events, do these more frequently than we have. And again, just to thank you all for taking time out of your day, come and listen to our story. And I thank my colleagues and partners who joined us for doing a great job. And thank you. And good afternoon, everybody.