Illumina, Inc. (ILMN) Earnings Call Transcript & Summary

Welcome to the GRAIL Capital Markets Day webcast. [Operator Instructions] I will now turn the call over to Bob Ragusa, Chief Executive Officer of GRAIL. Thank you.

Thank you, operator. Good morning, and welcome, everyone. It's a pleasure to be with you today for our Capital Markets Day. Next slide, please. Before we begin, I will remind you today's presentation will contain forward-looking statements, and more information can be found in the SEC filings. Next slide, please. Joining me today are Dr. Josh Ofman, President; Sir Harpal Kumar, President, Biopharma and Europe; and Aaron Freidin, Chief Financial Officer. GRAIL has built an exceptionally strong team across all levels of the organization. We are incredibly proud of the achievements that our employees have driven to date in data science, computational biology, medical affairs, laboratory operations, IT, commercial as well as other areas. We are pleased to represent the company here today. Next slide, please. Today's agenda will begin with a short introduction to GRAIL, and our investment highlights. Josh will describe the promise of multi-cancer early detection, GRAIL's progress to date and Galleri, our first-of-its-kind multi-cancer early detection screening tests. We'll then move to our commercial strategy for Galleri. Harpal and Josh will discuss the scientific evidence that GRAIL has generated plus ongoing clinical and real-world data collection to support adoption and upcoming regulatory submissions. Harpal will then share GRAIL's opportunities beyond asymptomatic screening, including symptomatic detection and a number of precision oncology opportunities such as pretreatment prognosis and MRD. Finally, Aaron will present GRAIL's financial profile before we open the call for Q&A. Next slide, please. Moving now to the company's background and investment highlights. Next slide. Since its inception in 2016, GRAIL's mission has been to detect cancer early when it can be cured. Next slide. We know that current recommended screenings with test for single cancers is limited and most deadly cancers are found too late. We believe that multi-cancer early detection is a solution for effective population screening. GRAIL is uniquely situated to address one of the most meaningful opportunities in health care. Galleri, our first-of-its-kind multi-cancer early detection test was designed for population-scale screening. Our expansive clinical evidence program is setting the standard for the multi-cancer early detection field. GRAIL has a first-mover advantage in an expansive global market. We have completed more than 180,000 Galleri commercial tests and are expanding the commercial adoption of Galleri in the U.S. We have a large global opportunity. We're investing to enable commercial scale, and finally, we have a proprietary methylation platform that yields a product portfolio across the cancer care continuum. Next slide. Since GRAIL was formed, we have developed an exceptionally innovative technology, growth market development of a new cancer screening category and built out scale to support the transition to population scale. We are looking today at a number of critical near-term catalysts that drive the next stage of growth. We are looking forward to these upcoming catalysts, including a potential NHS pilot, final data from our pivotal studies, the FDA approval and broad reimbursement for Galleri as well as additional product launches. Next slide, please. The ultimate opportunity for multi-cancer early detection is very significant. The total addressable market in the U.S. is over 100 million individuals. That TAM expands quickly with 19 million in the U.K. where we are running the NHS Galleri trial. Additionally, across the EU, there's a TAM of approximately 160 million more individuals. And in Japan, we see a TAM of 50 million individuals. Clearly, we're at the very beginning of an exciting journey. Next slide. In delivering our mission to detect cancer early when it can be cured, GRAIL envisions population scale multi-cancer early detection. Achieving such an ambitious goal requires significant investment and resources directed towards the broad reimbursement we anticipate in the future. To that end, we are laying the groundwork today to intercept that eventual opportunity. We have already made large investments to support broad access such as establishing a laboratory footprint built for scale. We are making significant strides in market development. MCED represents a new potentially transformational category. Our commercial and medical efforts today are designed to build the education and awareness of MCED drive adoption of Galleri and prepare the market in order to capitalize on the larger opportunities as they materialize. Next one. GRAIL was formed in 2016 as an idea and since then has made tremendous progress. We've invested heavily in transformational science, enrolling what we believe is the largest clinical program in genomic medicine. We have presented analytical and clinical validation data in world-renowned forms and published our filings in the leading academic journals. We have successfully developed and launched the first clinically validated multi cancer early detection test called Galleri. We've also begun to expand the application of our methylation platform capabilities to precision oncology. Next slide. We are proud with the rigor of our data. We have generated more than 260 scientific and medical publications to date, presenting at major conferences and publishing in leading academic journals. Galleri has found strong commercial reception in a largely pre-reimbursement market. There's robust interest from providers and commercial partners. We have already completed over 180,000 Galleri commercial tests. We have signed over 100 commercial partnerships and our progress here spans a number of channels, including health systems, employers and life insurance. Importantly, we have had -- we have over 10,000 ordering providers. We have also had high-profile recognition by Fast Company, the Atlantic, Time and Fortune magazines for our high level of innovation and impact on the world. Next slide. In addition to the size of the investment required to develop a population-scale MCED test, the time scale is analogous to that of drug development, our clinical and real-world experience provide a time advantage in the order of years. Over the past several years, we have significantly derisked our business. We have generated critical data in our PATHFINDER study that demonstrated Galleri can detect twice as many cancers as standard of care screening alone. We have launched our commercial product, Galleri. We have delivered over 180,000 Galleri commercial tests. We have unlocked new product opportunities, utilizing our methylation platform. We have scaled our laboratory infrastructure, and importantly, we have progressed discussions with the FDA on the evidence requirements for our PMA, primarily supported by PATHFINDER 2, where we have enrolled over 30,000 participants, and the NHS Galleri study that is fully enrolled and on track to finish final study visits in Q3 of this year. Additionally, we have gained approval of the REACH study for 50,000 participants in the Medicare population across 3 years. We believe we are well positioned in the field. We have made the investments required to drive a new paradigm in early cancer detection and are looking forward to years of growth ahead. We recognized early on the complexity and scale of the opportunity in front of us and have brought together an executive team based on that knowledge. We've built an exceptionally strong team to take advantage of this -- take this company forward. Our leadership has extensive experience and a proven track record of execution at industry-leading organizations. We're also very pleased to announce our new Board members, Greg Summe, Steve Mizell and Bill Chase. We're excited to work with these 3 experienced leaders as we take GRAIL forward. Now I'll turn it over to Josh to describe the promise of multi-cancer early detection.

Thank you, Bob. Next slide. So now we're going to talk about multi-cancer early detection. Now as many of you know, the human and economic toll of cancer is enormous and is simply devastating. Nearly every one of us has a story about somewhat important to us, who's been impacted by cancer. In fact, there are 19 million new cases of cancer globally every year, along with 10 million deaths. Today, cancer is considered the #2 cause of death globally, but is projected to become the #1 killer very soon. And a recent WHO analysis forecasted the number of new cancer cases will rise 77% to a total of 35 million cases by 2050. Next slide. There is simply nothing acceptable about the status quo today in cancer screening. Most deadly cancers are simply found too late. This is both a problem statement as well as what we view as one of the most enormous public health opportunities at population scale. On the problem side, current cancer screening is extremely limited. The reality is that 80% of the cancer deaths are coming from cancers we are not even looking for and do not have standard of care screening in the United States. We also know that 86% of cancers are not found through screening at all, and that proportion is even higher outside of the U.S. On the opportunity side is that we know that we have a 4x improvement in survival rates when cancer is detected early in its localized stage. So how do we capitalize on this opportunity? Next slide. While multi-cancer early detection is the way to enable early cancer detection at population scale, we simply must find more cancers through screening before they present symptomatically. This may be our only hope of really bending the cancer mortality curve. Today, most people receive 2 or 3 single cancer screening tests. And current cancer screening is not finding enough cancer in the population. In fact, these 5 screening tests, 1 cancer at a time, are only finding about 14% of incident cancers in adults at elevated risk. That is just not going to do the trick. It is clear that we need to find many more cancers early, and we need to screen for many of the less common cancer types. As you may know, there are over 200 cancer types. So it's simply impractical to add 10, 15 or 20 more single-cancer screening tests to our current single-cancer screening paradigm. This would result in very high cost and high cumulative false positive rates that would be prohibitive because they would really overwhelm the health care system with all these false positives. And I'll show you some data about that in a moment. Single cancer screening tests are simply impractical for most of the less common cancers, and they will never be cost-effective. And remember, these less common cancers cumulatively account for the majority of cancer deaths today. So we believe that a single MCED test that finds a shared cancer signal across many cancers and can identify where in the body that signal is coming from is the best solution to this vexing health care problem. Next slide. This is the illustration. Simply adding single cancer tests, more and more of them, will not get us to where we need to be. If you look at the results of the PLCO study, a large trial sponsored by the NCI, sequential screening with a number of single cancer tests for only 4 cancer types led to an individual's false positive rate of over 50%. And if you look at this illustrative example, you can see why. For each single cancer test, they each carry their own false positive risk, which you have to add up at the individual level. And once you add a few of them together, you see that this false positive rate quickly becomes unacceptably high. Next slide. So when evaluating the screening test, one of the most important criterion is to look at the number of cancers detected the yield relative to the number of false positives generated. So let's look at what the world looks like with and without Galleri. Without Galleri, today, in the top row, standard of care screening identifies less than 200,000 cancers in elevated risk adults, and in the process will generate over 8 million false positives every year. According to our modeling, when you add Galleri, we could identify approximately 460,000 more cancers. And because Galleri has been designed with such high specificity, it will minimally increase the number of false positives, making multi-cancer lead detection testing one of the most impactful opportunities in health care. Adding Galleri to standard of care screening completely improves the signal-to-noise ratio from approximately 1:45 to a combined ratio of approximately 1:15. So here, you can see that by adding Galleri to standard of care screening, the entire screening system gets much more effective and much more efficient. We can identify many more cancers much more efficiently and reduce the cost to diagnose a single cancer by approximately 65%. Next slide. So through this comprehensive research, GRAIL has confirmed that our methylation platform can identify a cancer signal that is shared by many, many types of cancer. This is the fundamental breakthrough that marks GRAIL's innovation and leadership in this whole field. The test is designed to be used in asymptomatic adults at elevated risk for cancer as a complement not a replacement to single cancer screening tests that are highly recommended today. This is to drive earlier detection of cancers to enable more treatment options and better outcomes. Abnormally methylated DNA is a hallmark of cancer. And additionally, that abnormally methylated DNA can also tell you where in the body that cancer signal is coming from. In other words, it can predict the cancer signal's origin. Galleri was designed to have a very high specificity to limit false positives and to drive a very high positive predictive value, one of the key clinical measures that I'll talk about more in a minute. Our technology also has a number of other benefits, including a very low clinical limited detection, a cell-free DNA signal that preferentially detects highly shedding cancers that are typically invasive and very aggressive. Next slide. Positive predictive value is perhaps the most important clinical measure. And just to recall what that means, positive predictive value is among those who have a positive test result what is the likelihood that they will have invasive cancer at that time. You can see here that the PPV for single cancer screening tests is often in single digits and that the Galleri test stands out among all of these single cancer screening tests with its very high positive predictive value because of its low false positive rate. These features support the impact for population screening. Next slide. Critically, Galleri is actually working in the real world. As you can see from the quote here, our commercial use of Galleri is finding lethal cancers early in the real-world setting. In this case, Roger talked about his early pancreatic cancer that was found. The majority of these early-stage cancers that we're finding do not have any screening tests. And remember that when you find localized solid tumors, not only are there effective treatments, but they're often curable treatments, typically with surgery and radiation. We're immensely proud to be able to help patients and providers find these cancers early and enable positive outcomes for patients. Next slide. So what does the test report actually look like? It's not a 20-page report of hundreds of mutations. The test is meant to be easily implemented into clinical practice. It is prescribed alongside recommended screening and the test results are communicated back to the provider. We designed the test report to provide valuable information for a positive or negative signal, and importantly, it shows the signal origin, the prediction to allow the doctor to get a very directed and efficient diagnostic evaluation. Next slide. And because this is so new, GRAIL provides a variety of support services to providers to optimize the path to diagnosis. After a positive signal is reported, GRAIL's medical science liaisons are in contact with physicians within hours to provide support material and other resources. We have resource and navigation services available to the physician and the patient. Physicians can elect for peer-to-peer consultations. And for those unusual but very difficult cases, we have a tumor board and a retesting program that is also available. And now I'll hand it back to Bob.

Thanks, Josh. Shifting now to our commercial strategy. Next slide. In the short term, our commercial strategy is focused on multiple stakeholders as we work to build awareness and capabilities to enable scale, once broad access is available. Our focus today is on wellness driven clinician engagement and innovative value-oriented partnerships, and we are encouraged by the engagement we are seeing in the market. We are seeing enthusiasm from a broad set of health systems, employers and life insurance partners. To date, we have more than 10,000 ordering providers and more than 100 commercial agreements in place with leading health systems, forward-looking employers and life insurance partners who recognize the value of detecting cancer early. We are gaining insights about the MCED market today as well as meeting the early market demand. Our targeted commercial sales force promotes the physicians as we also have business-to-business teams in place driving partnerships and supporting pull-through. In addition to our other channels, we have established partnerships with early adopter payers as well as groups with potentially higher risk for cancer, such as unions and first responders. Next slide, please. Our focused commercial team drives adoption through direct promotion to clinicians in partnership with the enterprise team, customer service, health system sales and marketing. We have approximately 200 sales personnel across our channels, and we are taking a targeted approach in the short term to maximize the opportunity before broad reimbursement is available. We're also focused on market education as we are the leading player in MCED, with the largest share of voice. Next slide. Beyond the U.S., the NHS England rollout would represent a substantial commercial expansion. The ongoing NHS Galleri trial is a randomized controlled study of 140,000 participants aged 50 to 77 in England. We have an unprecedented commercial agreement in place with the NHS which could enable national scale implementation after the full study results in 2026. National rollout will be deployed by an NHS invitation system, enabling significant scale with limited commercial resource requirements. The test is already UKCA mark and no additional regulatory processes will be necessary to initiate market deployment if the NHS decides to initiate a pilot. We anticipate that the NHS implementation could carry major influence on markets globally. Next slide. We have already built out laboratory infrastructure to scale to enable future growth. We have 65,000 square feet of [indiscernible] and CLIA certified facilities between our Research Triangle Park, North Carolina sites, and our Menlo Park, California site. In addition, our RTP site alone has approximately 200,000 square feet, enabling us to continue to scale laboratory capacity substantially with sufficient capacity to support multiple years of growth. In our next version of the Galleri test to be launched at the end of this year, we've integrated significant automation, which supports both large-scale testing and scale as well as driving down COGS significantly. We have already demonstrated significant scale as we've run approximately 450,000 Galleri commercial tests and research tests to date. We also have office sites in Washington, D.C. and London and over 1,300 employees. Next slide. We are looking forward to a major inflection point with FDA approval of Galleri. We anticipate FDA approval will enable broad access with commercial health plans. In addition, we anticipate passage of the Medicare legislation that would authorize CMS to cover multi-cancer early detection tests that are FDA approved. Following passage of that legislation and FDA approval, CMS would be able to cover Galleri. Broad access enabled by commercial and Medicare coverage is expected to transform the MCED opportunity. And the work we are doing today will help us prepare for the scale to meet that opportunity. Now I'll turn it over to Harpal to walk through GRAIL's scientific background [indiscernible]. Harpal?

Thank you, Bob. So let's now talk a little bit about how our technology works. Next slide, please. So many of our cells shared fragments of DNA into the bloodstream as they turn over or die. And this is also true of cancer cells. And DNA from those cancer cells contains information that can tell us something about the cancer. So the first step is that we look for these DNA fragments and isolate them from the blood plasma. We then sequence these DNA fragments using next-generation sequencing, looking particularly at methylation sites across the genome. Next slide, please. Now the role of methylation in normal biology is to tell genes when to switch on or went to switch off, and methylation is a process that silences those genes. And although methylation is established during our normal human development, we know that methylation patterns are modified during aging, by disease or by our environments. And this enables us to distinguish cancer from non-cancer. What we have found is that there are patterns of methylation associated with cancer that are different from the patterns that we see in normal cells. Increased methylation, which turns genes off, we see in regions which usually suppress tumor development. By corollary, we see reduced methylation, in other words, turning genes on, in regions which usually promote tumor development. And what we've seen is that these patterns are shared across many different types of cancer. Now abnormal methylation and epigenetic reprogramming in general is a hallmark of cancer. And moreover, epigenetic programming is also a fundamental process which determines how individual cell types are formed or differentiated from a starting embryo. And so these methylation patterns can also give us a fingerprint of the cell type that is giving rise to the cancer signal. And this enables us to predict the cancer signal origin as I'll come on to in a couple of slides' time. Compared to other genomic alterations, methylation is a much more ubiquitous signal. There are around 30 million methylation sites across the genome, which provides a rich basis for interrogation, whereas mutation panels typically only examine a relatively smaller number of sites. And for all these reasons, methylation seemed like an excellent opportunity to look for a cancer signal. Nevertheless, GRAIL wanted to be absolutely sure that this was the best approach. Next slide, please. So we started with a completely unbiased discovery program. We explored multiple different approaches to see which approach would give us the best signal-to-noise ratio when looking for a cancer signal across a diverse population of people with different backgrounds and different potentially confounding conditions. We explored mutations, fragment lengths, chromosomal changes and methylation. And in exploring these different approaches, we were inspired by the concept of limit of detection from analytical studies, and we looked for a clinical limit of detection to understand our clinical signal detection performance. And we defined this as the value where the probability of detecting a cancer case was 50% at 98% specificity. And you can see in this chart how the different approaches performed in that context. The arrow bars, you can see of the 95% confidence intervals for each approach. And if you look down towards the bottom of this chart in the beige, you'll see that whole genome methylation gave us one of the lowest clinical limits of detection. And what we want to see in terms of limit of detection is the lowest value possible. And then with further development and deeper sequencing, looking at a smaller number of methylation sites, we developed what we call our targeted methylation panel. And as you can see in the blue here, at the bottom of the slide, this gave us an order of magnitude further improvement. And really importantly adding approaches to this targeted methylation approach did not improve performance any further. Next slide, please. So the way our test works is that having sequenced the DNA looking for these methylation patterns, we then run this information through a 2-stage classification process using advanced machine learning. The first stage is that we look for patterns that enable us to discriminate between DNA that's coming from a tumor from DNA that might be coming from normal cells or other signals in the body. And this enables us to call a cancer signal. The second step then is if we have detected a cancer signal, we use that same methylation information to predict where in the body a signal has come from, and we call this the cancer signal origin because we can predict the cell type that's given rise to that signal, as I touched on earlier. Next slide, please. Now cancer signal origin prediction is increasingly recognized as a critical component of a multi-cancer early detection test. What we want to be able to do is to efficiently guide the next stage in the assessment of whether and what type of cancer a person has once we've detected a cancer signal in their peripheral blood. Because until this point, we have no knowledge of the location of the disease in the body. What you can see on this slide on the right-hand side is statements from a number of opinion leaders on the importance of having this CSO capability and accuracy. And what you can see on the left-hand side is a quote from the FDA summary report following an Advisory Committee meeting held in November regarding multi-cancer detection. The panel believes that multi-cancer detection tests should have a tissue of origin component to the device as it would guide targeted diagnostic workup and minimize the risks. So that's a bit about the science and the technology. Next, we have to prove that this approach works in the real world. And so in developing Galleri, we've undertaken one of the largest clinical evidence programs in the space designed to validate our approach and generate the evidence we need to secure regulatory approvals and reimbursement. Next slide, please. This is a program that's involved multiple studies totaling over 385,000 participants overall. More than 21,000 of these participants were included in studies that supported the development and launch of Galleri summarized on the left-hand side here. A further more than 170,000 individuals have been enrolled to date in interventional studies, which will support our PMA, summarized in the second column here. So let me start with our discovery and clinical validation work. So the first study we undertook was our foundational study called the circulating cancer genome Atlas study, or CCGA. This was an observational study, a case control study with around 15,000 participants. The first 2 parts of CCGA were focused on deciding which technology to use, what I've already summarized in terms of our unbiased discovery effort that led to us choosing methylation as the technology to move forward with. CCGA enabled us to further develop that targeted methylation assay to improve sensitivity and specificity. We then used the third part of CCGA, to validate this clinically in the case control population. And it was this that established our initial performance parameters for our multi-cancer early detection test. PATHFINDER was a study of more than 6,000 individuals in the U.S., and this was our first implementation in the intended use asymptomatic population. And what we were really pleased to see was that the performance replicated what we had seen in the CCGA case control study and what we had predicted for our performance. Importantly, we did not see the degradation in performance that's typically associated with the transition from case-control studies to asymptomatic populations. And this speaks both to the quality of our test design, but also the rigor of our science. CCGA and Pathfinder have both been published in peer review journals and the results have been presented at major conferences, including the American Society of Clinical Oncology and the European Society of Medical Oncology, or ASCO and ESMO. Moving to the second column here. We are currently conducting 2 registration-enabling studies. NHS Galleri is a study of over 140,000 people being carried out in England. It's a randomized controlled trial designed to demonstrate the clinical utility of our MCED test at population scale. The primary objective will be to demonstrate a reduction in the incidence of late-stage cancers, what is sometimes referred to as stage shift. Because this is also a very large study, we'll also be able to use it to confirm our performance. We'll be able to generate large-scale safety data, including understanding what happens with post-positive diagnostic investigations. We'll be able to model the mortality benefits of implementing a screening program using our MCED test. We will be able for the first time to look at the value of screening annually because NHS Galleri involves screening people over 3 rounds, spaced 1 year apart. NHS Galleri is fully enrolled, and we're very close now to completing that third round of screening, and we will complete the blood draws in July of this year. PATHFINDER 2 is a 35,000-person study being carried out in the U.S., of which over 30,000 have already been enrolled. PATHFINDER 2 will generate additional U.S.-based safety data in a much larger study and will also be able to demonstrate data across a number of different diverse groups, including a number of ethnic groups. So these 2 studies collectively will support our PMA, which is currently in process with a rolling submission under a breakthrough designation. Over on the right, we'll soon launch our Galleri Medicare study. This is a real-world evidence study, which will enroll 50,000 individuals, again, allowing for 3 annual tests in this case, in a Medicare population together with a synthetic control. Galleri Medicare will provide additional evidence on the clinical validation and utility and support a Medicare reimbursement decision after FDA approval. And I will stress here that Galleri Medicare is intended to be a post-PMA study, and you'll hear more about this study from Josh in a little bit. So these are some of the critical studies that are involved in validating the performance, but also then generating the evidence that will support approvals and reimbursement. So let's now look at some of the data, starting with our CCGA study. Next slide, please. So CCGA demonstrated that we can detect cancer signal across more than 50 different types of cancer. Importantly, we've been able to do this with an extremely low false positive rate of 0.5%, which compares with some of the much higher false positive rates that Josh showed you earlier. And together, this means that we have modeled with CCGA that we would have a positive predictive value of 44%. In terms of our ability to predict the cancer signal origin, we've been able to do that with an accuracy of just under 90%. And really critically, are we finding cancers early? Well, we prespecified a group of 12 types of cancer that represent just under 2/3 of all cancer mortality in the United States. And what we found was an almost 70% sensitivity for finding these cancers at Stage II, which is regarded as an early stage cancer, for which almost always there is a curative treatment option available. So CCGA enabled us to establish our critical performance parameters for MCED testing. And I'll now hand over to Josh, who can tell you y what we saw in our Pathfinder study.

Thank you, Harpal, next slide please. What I really want to emphasize here and reiterate what Harpal mentioned is that we did an important interventional trial called PATHFINDER. And we show here that the data in PATHFINDER actually replicated what was seen in our case controlled study. And just to emphasize what Harpal said, this is very unusual to see in this field. In fact, it's not been seen in this field until now. So PATHFINDER showed that our positive predictive value and CSO prediction were consistent with what we saw from our case-controlled CCGA study. We did not observe the degradation that so many in the field have seen and that was quite honestly expected. Specifically, our PPV at 43% is in line with what we published and modeled from CCGA. And so this evidence together supports the generalizability and the actual robustness of Galleri in our interventional study, involving Galleri return of results on the clinical diagnostic and care pathways in the intended use population outside of a case-controlled study, really, really important. Next slide. In PATHFINDER, which we presented at ESMO in 2022, we showed that Galleri more than doubled the number of cancers identified when added to standard of care screening. And we're really pleased that these studies continue to demonstrate consistent results across all of our observational and interventional studies. Almost half of the cancers detected by Galleri were in their early stages I and II. The PPV as I already mentioned, was 43%, again, an order of magnitude higher than the PPV seen from leading single cancer screening tests shown here on the slide in green. The localization accuracy, critically important, and the CSO was also very high, leading to very efficient diagnostic workups. Critically, there were no serious adverse events related to the diagnostic workups in the study, and patient satisfaction scores were uniformly high even among those who had false positive results. Next slide. So we believe that the reason our test performance is so consistent has been enabled by the fundamental biologic features of circulating cell-free DNA. Biologically, we know that higher levels of tumor cfDNA are associated with more aggressive cancers across all stages. So there are early-stage cancers that are shedding lots of DNA, and there are late-stage cancers that may not be. So it's very stage dependent. Because of this, our MCED test preferentially detects the more lethal cancers, the invasive and aggressive cancers, which may help avoid over-diagnosis. And of course, this is what we would want. We would want an MCED test to preferentially detect the cancers most likely to result in death, aggressive and clinically significant cancer warranting treatment. This is what Galleri detects. Next slide. This slide is a little complex, but it illustrates the point, I think, very well and has now been published. Data across our clinical studies suggests that although Galleri detect signals for some of the most aggressive cancers, the detection of cancer signals for slow-growing or indolent cancers, which people are less likely to die from, is actually quite low. These are Kaplan-Meier survival curves, which show survival over time. Cancer is detected by Galleri, seen here in blue, have a very similar force and prognosis to that expected based on our analysis of the SEER database, which are shown in hash lines. So you see the blue line of Galleri detected cancer is really sitting on top of these hash lines, which is what you would expect based on SEER. At any given stage, survival was worse with cancers detected by Galleri compared to cancers that were not detected by Galleri. More specifically, the blue curves, which represent the Galleri detected cancers are steeper than the purple curves, which represent undetected cancers, meaning that cancers detected by Galleri had a prognosis similar to SEER, whereas those not detected by Galleri had a prognosis much better than what would be expected. These findings were consistent across stages and across age. What these data suggest is that indolent cancers, the ones that people are worried about that we are overdiagnosing and overtreating, the ones that people may die with not die from are unlikely to be detected by Galleri. Thus, Galleri is unlikely to contribute to this problem of overdiagnosis and the harms associated with overtreatment of these overdiagnosed cancers. Next slide. Now we're going to go into a little more detail on our registrational program. Next slide. These studies are progressing well and are on track. We have enrolled more than 30,000 of the planned 35,000 in PATHFINDER 2 and in the NHS Galleri study. It's anticipated to complete the third and final round of blood draws in July. Study results for the NHS Galleri trial are anticipated in 2026. Interim results from PATHFINDER 2 are expected in the second half of '25 after we have a full 1-year follow-up on the first 25,000 participants. Together, as Harpal mentioned, these studies include approximately 175,000 participants and will be the pivotal package supporting our PMA submission. I think you can all appreciate the depth and breadth of our clinical genomics program. Next slide. The NHS Galleri trial is really an unbelievable study trying to address the long-term ambition of the NHS, which is to reduce the proportion of cancers detected in their late stage and increase early-stage detection. This is the first randomized controlled study of an MCED test of 140,000 participants between the ages of 50 and 77 to evaluate the clinical utility for population screening. We're on track to complete final study visits in the third quarter of this year and final results anticipated in 2026. Next slide. PATHFINDER 2 is a multicenter study in the United States with return of results in our U.S. health care system. It's enrolled over 30,000 participants to date, and this is really our pivotal U.S. performance and safety study. It is not -- while the NHS trial is 3 consecutive years of annual testing, this is 1 year of testing, with 3 years of long-term safety follow-up. Next slide. In November, we've announced the REACH Medicare study. Here, as you know, Medicare beneficiaries are among those most at risk for cancer due to age and other risk factors. So there is an enormous unmet need for earlier cancer detection in the Medicare population. We announced the Galleri Medicare study called REACH, which is a prospective multicenter study to assess the clinical impact of Galleri when added to recommended standard of care screening in the Medicare population. This study will recruit 50,000 individuals who will receive usual care plus Galleri for 3 consecutive years. Because this study was approved by the FDA as an IDE, the cost of the test and the related services for study participants will be covered by Medicare. The individuals receiving Galleri will be compared to a similarly sized cohort from EMRs to understand the clinical impact of Galleri in this real-world cohort. Next slide. Now real-world evidence is a critical part of our entire evidence program. We launched Galleri in 2021 and have been committed to studying the impact in real-world use. We just mentioned the Galleri Medicare study. That will be a real-world study to help us understand the actual clinical impact of Galleri under usual care conditions. In addition, we designed the reach Galleri Medicare study with a focus on underrepresented communities and minority populations. Beyond that study, we have an ongoing clinical surveillance program, which enables us to assess performance and safety from cases that are -- that we follow to generate data and to systematically evaluate evidence from our commercial use. These learnings are critical to enable our own test performance improvements over time, but also to enable the paradigm shift in early cancer detection. Next slide. Importantly, we are making great progress in our rolling modular PMA. As you know, we're in a breakthrough designation with the FDA. We have an ongoing modular submission that is progressing well. Importantly, all of our product development efforts that support Galleri updates and our PMA submission have now been aligned. They are all occurring under full design control to ensure we meet the regulatory standard. And now to talk about the opportunity beyond asymptomatic screening, I'll hand it back to Harpal.

Thank you, Josh. So everything we've spoken about so far has been asymptomatic screening. But as we think about what we've developed in GRAIL, we've developed not just a product but a platform. Our targeted methylation platform can enable us to provide solutions across the continuum of cancer care. And we're really excited about 2 areas in particular, symptomatic detection and precision oncology. Next slide, please. So let me talk about symptomatic detection first. As we have already alluded to through this presentation, the vast majority of patients who are diagnosed with cancer, over 80%, first are detected because they present with symptoms. Now sometimes those symptoms can be very obvious, for example, a breast lump or a skin lesion. And in those cases, the clinician knows what to do next and knows which investigations to undertake. But in a very large number of cases, the symptoms that a patient presents with can be very nonspecific. So these can be things like unexplained weight loss or anemia. And in these cases, cancer might be the reason that the patient has symptoms, but it could be something else altogether. And if it is cancer, it could be many different types of cancer. Now because cancer is one of the possibilities, these patients typically undergo extensive investigation. We know that more than 70% of these patients will undergo some form of imaging. Over 1/3 will have a biopsy, and in many cases, patients will have several different investigations. But in practice, only around 4% or fewer of these patients will actually be diagnosed with a cancer. And we also know that many of these patients over a quarter can take many months to get to a diagnosis because they go through a sort of diagnostic odyssey as they go through these multiple different investigations. And so we believe that multi-cancer early detection offers the opportunity to realize this unmet need to accelerate diagnosis where a patient is presenting with these nonspecific symptoms, but also to avoid harmful procedures where cancer is unlikely to be the reason that the patient has those symptoms. And this is a very large unmet need. We estimate that between 15 million and 20 million patients every year in the United States are presenting with these nonspecific signs and symptoms. The other really interesting and exciting opportunity with this unmet need is that there is the possibility to pursue a reimbursement approach using existing coverage pathways because this would be a molecular diagnostic test. So because of this opportunity, and because we believe our technology is ideally suited to this opportunity, we've already started generating evidence for this group. Next slide, please. So we've carried out a study that we call SYMPLIFY. This was carried out in the U.K. in partnership with the University of Oxford and enrolled more than 6,000 people. And we were very excited by the results that we saw. First of all, our PPV with this group, as you can see here, was over 75%. We also had an extremely high negative predictive value. And this is really important in this population because we don't want to miss a cancer if a patient does indeed have it. As you can see towards the bottom there, we also had a very high accuracy in our CSO prediction. And this is really important, again, in this population, remembering that these are patients that are presenting with nonspecific symptoms. So if I go back to the example of unexplained weight loss, unexplained weight loss can manifest in up to 15 different types of cancer. So being able to direct the next stage of clinical investigation if someone does have a cancer signal becomes increasing -- becomes incredibly important in this population. And indeed, we know that often the cancer type that the patient was ultimately diagnosed with was different to the 1 that the physician initially expected or suspected from the way that the patient presented. Interestingly, we saw the highest performance in patients referred for a suspected upper GI cancer, which, as it turns out, is where the largest unmet need is in this population. Next slide, please. So the second area that we're really excited about is precision oncology. So this is the notion that once a patient has been diagnosed with cancer, how do we optimize their treatment to drive the best possible outcome for them. Now precision oncology is a rapidly growing field, with a significant unmet need, and therefore, a significant market potential. And we see applications for our targeted methylation platform across this continuum. Most of the market focus so far in precision oncology has been in what we call MRD, which is the advent of tests to detect the presence of microscopic disease after curative intent treatment because often, this can presage a higher risk of recurrence or relapse. But we also believe that there are real really important use cases, first of all, in pretreatment prognosis because if a patient has a much worse prognosis, we might want to intensify treatment at that earlier stage, in being and being able to detect recurrence before symptoms reappear or before there's clinical evidence of recurrence because, again, we might want to start treatment earlier in this population. And last but not least, in monitoring patients when they are on treatment to see if they're still responding to that treatment or not, or should we change the treatment regimen that they're on. Next slide, please. Most of our work so far in precision oncology has been in partnership with biopharma companies, and we've been working with a number of the leading oncology companies to explore the potential of our technology in their clinical programs. And this area of work is also starting to generate meaningful revenue for GRAIL. One example is a strategic collaboration with AstraZeneca, which we announced in 2022 to develop companion diagnostics for patients with earlier-stage disease. And indeed, we recently announced the start of a prospective clinical trial with AstraZeneca in Japan in Stage I non-small cell lung cancer using a customized GRAIL test. Importantly, we also see significant potential to expand beyond biopharma with our own clinical products, for example, in MRD, and we're in development for the first of those. Next slide, please. Now we believe our technology has a number of significant advantages in this space. First of all, our platform doesn't require us to develop a bespoke panel for each patient. And neither do we require a tissue sample. We just need a blood sample with limited plasma input. We're able to deliver a very quick, between 7 and 10 days, clinical turnaround, which is critically important when we're dealing with cancer patients who may have aggressive disease. And we can also provide a quantitative measure of the tumor burden so that we can track how patients are doing over time, particularly in that clinical monitoring phase. And of course, because of everything else we've already described, this has application across multiple different types of cancer, which is attractive both to pharma companies and clinicians because it means that they can work with and get familiar with a platform that they can use across multiple different types of cancer. Now we validated our performance, and we have demonstrated, indeed our pharma partners tell us that we have sensitivity on a par with the tumor-informed methods that they often use. We have robust and reproducible test performance, and we have an extremely low assay failure rate, which again is critical in this population. And again, it's something that our biopharma partners tell us is very important vis-a-vis some of the other platforms that they use. And so what we do in the precision oncology space is that we're able to optimize classifiers for specific use cases and indications. And we're very excited with some of the data that we're seeing. Next slide, please. And we've now started to present and publish some of this data at key conferences such as the American Association of Cancer Research. And what you can see summarized on this slide is some of the different use cases and cancer types on which we have already presented data. But let me talk about 1 example specifically on the next slide, which is data that we presented at the North American Lung Conference last December. Next slide, please. So this is a lung prognosis test that is carried out prior to surgery with Stage I lung adenocarcinoma patients. And what we would demonstrate -- what we were able to demonstrate with this study is clinically meaningful risk classification. So on the left-hand side here, you can see a Kaplan-Meier curve similar to the ones that Josh showed you earlier. And what this shows is the relapse-free survival of patients who either did have a positive test, those in purple, versus those who had a negative test, in the yellow there. And what you can see here is that this clearly discriminates patients at high risk of early relapse from those at lower risk of early relapse. And the conclusion here was that test positive Stage 1 patients experienced recurrence rates similar to unselected Stage 2 patients, suggesting that these patients would benefit from intensified therapy at the earlier stage. And this study had a hazard ratio of 3.8, as you can see here on the right-hand side. And it's this assay that we're using in the Japan study that we're carrying out with AstraZeneca that I alluded to earlier. So really very excited by the possibilities that we see beyond asymptomatic screening to further build the GRAIL business using our core platform. And this is a key part of our story going forward. And with that, I'll now hand over to Aaron to talk about some of the financial aspects of our presentation. Aaron?

Thank you, Harpal. As Harpal said, we'll now spend some time looking at the financial profile. Next slide, please. GRAIL's revenues for Q1 2024 were $27 million, which was approximately 36% growth over the same period of the prior year. Full year revenues in 2023 were $93 million, representing approximately 68% growth over the full year of 2022. As Bob has explained, we are seeing early adoption of Galleri prior to broad reimbursement. We are making an investment in building the MCED market category which will allow us to drive uptake more effectively once we have broad regulatory approval and reimbursement. Since launch, we have been learning which investments drive commercial pull-through most efficiently, and we know that sales will titrate based on our level of investment. Going forward, we expect our revenue growth to fluctuate based on the level of investment we make in building the MCED market. In the near term, we expect continued investment focused on obtaining broad regulatory approval, reimbursement and access. We are focused on making significant reductions in our COGS per test, and bringing down our operating loss over time. As we progress through major milestones, we expect to have line of sight to profitability. Next slide, please. At separation, we'll have approximately $1 billion of cash on our balance sheet. With 2.5 years of cash, we are fully funded through the end of 2026, are well positioned heading into major milestones, including NHS data readout and the filing of our PMA. We expect our core U.S. Galleri business to grow at 30% to 50% rate in 2024. This rate does not include any potential contribution from an early pilot with the NHS or other international opportunities. We are also not including any guidance on our pharma business as it can be lumpy as timing of projects are dependent on specific pharma program time lines. In 2023, our cash burn adjusted for the cash-based LTI program that will convert into an equity-based program upon spinout, was $532 million. Our cash burn for the second half of 2024 is expected to be approximately $250 million. We have levers to pull on across our P&L to manage our burn and ensure we can invest in our core value drivers, including U.K. implementation, MCED approval and a commercial rollout and growth of our precision oncology business. Next slide, please. Galleri has established commercial MCED leadership and achieved greater than 90% year-over-year revenue growth in 2023. Through March of 2024, GRAIL has sold more than 180,000 commercial Galleri tests and significant runway remains with more than 100 million individuals in the intended use population in the United States alone. We continue to make significant investments to increase market awareness, to drive expansion of the Galleri provider base and implementation of early detection clinics. Key drivers for the future include pricing and reimbursement, international deployment, establishing consistent annual testing intervals and driving screening compliance. The market opportunity will transform with FDA approval in the U.S. and obtaining national or commercial payer coverage broadly. GRAIL has invested in technological and automation improvements that will support price reductions to serve a broad population and enable an accelerated adoption. Next slide, please. There's a significant need in the oncology market to identify residual disease or recurrence early to inform treatment decisions. To date, we have ran more than 6,000 samples across multiple pharma partnerships. These partnerships are generating a pipeline of companion diagnostic opportunities. We are additionally exploring opportunities to enter the market with a clinical LDT for precision oncology use cases. Next slide, please. We've talked about our infrastructure investments and the anticipated transition to an automated platform this year, which will enable a significant reduction in COGS. Over time, we anticipate further volume-based efficiencies to get us to target gross margin of 55% to 60%, which includes a royalty we will owe to Illumina after separation. Further development and technological advantages are additionally possible. Next slide, please. Today, our revenue is primarily from Galleri in the U.S. with contribution from our precision oncology business. In 2023, U.S. Galleri revenue was $75 million or 80% of total revenue. Over the next few years, we anticipate additional diversification of revenues as we launch internationally and introduce additional products. Importantly, in markets like the U.K., where launching a national system is possible, the operating requirements are much more limited as compared to the United States. Because of this, we expect to drive strong operating margin with lower pricing. Next slide, please. We have heavily invested in R&D since our founding, which has created a competitive advantage for us. As we complete the major clinical studies and the rollout of our lower-cost automation platform, we anticipate the R&D cost as a percentage of revenue to fall significantly, even as we continue to invest in innovation and new product development. Next slide, please. You can also expect SG&A cost to become more efficient over time as we build Galleri channels and progress pre-reimbursement sales through focused initiatives. We expect our current sales force to become more efficient over time. Next slide, please. In 2016, when GRAIL was formed, we have developed an exceptionally innovative technology, driven market development of new cancer screening category, and built out scale to support the transition to population scale. We are looking today at a number of critical near-term catalysts that drive the next stage of growth. We are looking forward to these upcoming catalysts, including potential rollout of Galleri and an implementation pilot by the NHS, final data from our pivotal NHS Galleri and PATHFINDER 2 studies, FDA approval and broad reimbursement of Galleri and additional product launches. Next slide, please. And that concludes our prepared remarks. Operator, we'd like to turn it over to questions now.

[Operator Instructions] Our first question comes from Vijay Kumar from Evercore.

Thanks for hosting this and I guess my first question is -- Josh, perhaps for you. You spoke about PPV, positive predictive value. And when I look at the screening space, there's a lot of targets and metrics, which are being thrown around. For different cancers, different metrics being thrown around. Whether it's early stage asymptomatic, sensitivity. I guess when you look at MCED, how do -- what are the guidelines there on what metrics our body is going to look at. Is it PPV? Why does PPV matter for MCED test? Why shouldn't we look at traditional metrics like a sensitivity metric? And how well understood is this metric by physicians, right? When you think about test adoption, is this a well-understood metric? Maybe some thoughts on that?

Yes. No, it's a great question. So again, the traditional metrics will obviously be looked at. Remember, single cancer screening tests really focus on being highly, highly sensitive because you don't want to miss anything, and you want to find everything and you accept a very high false positive rate. You can look at mammography, low-dose CT, stool-based colon cancer screening, go down the list. That's quite different than what you want in multi-cancer early detection test, where you can detect somewhere between 50 and 70 different types of cancer, you can't accept that high false positive rate. So you really focus on specificity. And our specificity for our assay is at the cancer signal level. So we have one specificity. And then the sensitivity will vary by cancer type, depending on how much tumor DNA is being shed. So you have high shedding tumors, which will -- are aggressive and invasive, which will have very high sensitivity and lower shedding tumors kind of the slow growing indolent ones where there will be lower sensitivity. The reason PPV is so important because as a clinician, you do not know what the cancer status is of the patient. And so the positive predictive value becomes the most important thing you deal with as a doctor. So yes, doctors are very familiar with PPV, and that is what matters most to the doctor because that tells you if I have a patient in front of me with a positive result, how likely is it that they're actually sitting before with cancer. And in our assay, it's somewhere between 40% and 50%, again, in order of magnitude higher than that seen with single cancer screening tests. So the short answer to your question is we will look at all the traditional metrics, there will be a single specificity, and PPV becomes really the critical metric for multi-cancer early detection testing to avoid all the false positives. The other critical metric, of course, is the signal origin prediction, which enables a very efficient and effective diagnostic evaluation.

That's helpful, Josh. And my follow-up perhaps is on -- when you look at the catalyst you're -- it looks like the NHS study back half of this year, that's the most near-term catalyst. So what are we looking for when the study is published? Is it PPV we're looking for? Or are we looking at this cancer signal origin, what kind of metrics are we looking at? And you did mention a potential NHS expansion of the commercial rollout, do we have some hard metrics on what's the minimum bar that we need to clear before this rolled out in the UK?

Harpal, you want to take that one?

Yes, sure. Thanks, Vijay. Well, look, let me say a couple of things about this. First of all, the most important thing to say about NHS Galleri is that it's intended to provide meaningful clinical utility evidence when we get the final study results, which will be in 2026. And that will be the basis on which the NHS decides whether or not to implement a population scale program, really rolling out a full-scale national screening program. But also, as we've already touched on, provides data for the FDA PMA submission. So that's really the most important thing to focus on with NHS Galleri. And as I say, we will get those results in 2026. But what we also discussed with the NHS some time ago, was that if we see just looking at the first year only of the study, if we see some really compelling information there, then the NHS might be willing to start an implementation pilot earlier than 2026. Now I should clarify that, that would only look at the first year of the study, and they would only look at certain metrics, which is not the primary objective of the study. So that's a process that's currently underway, and we'll know this summer. I should clarify though that there's no intention at this stage to publish those results from the first year of the study. The only purpose of it is to enable the NHS to make a decision as to whether it's so compelling that they want to start a pilot implementation earlier than they otherwise would. In answer to your question about what they'll look at? They'll look at PPV, yes. And they'll also look at the number of Stage IV cancers and how many cancers we find overall. So that's the sort of thing that they're going to look at, but -- and we'll know that, as I say, later this summer.

Our next question comes from Sung Ji Nam from Scotia Bank.

I have a couple of questions that are related, so I'll ask them at the same time. So just wanted to clarify that the FDA submission will be for asymptomatic population, 50 years and older and not targeting high risk or symptomatic patient population, et cetera? And then related to that kind of -- the question was asked in terms of endpoints that the FDA might be looking for. And I think you touched on with the NHS looking for stage shifts. So do you think stage shift would be an acceptable kind of near-term endpoint for FDA and other regulators? And then kind of when -- how are you thinking about -- or how should we think about just kind of being able to determine mortality, right, longer term for tests like an MCED test?

Yes. That's a really good question. Thank you. The first piece, so we are submitting for an asymptomatic and it is 50-50 and above, which is our view of what elevated risk is. From a criteria standpoint, maybe a few things from the FDA hearing. They were very clear that mortality data was not going to be required for approval of an MCED. They also did say that capability, which the Galleri test has is a very important and critical criteria for an MCED test. And they also indicated that we would be able to use aggregated data as well. So I think those elements speak -- work very much in the favor of Galleri and the way we've set up the technology. Josh, I don't know if you want to add anything to that?

Yes. Just the FDA was pretty clear they're going to be looking at clinical validation, really not focused on clinical utility like mortality or stage shift. So we believe we will provide them with all the data that we have. And as Harpal explained, we will be looking at an absolute reduction in late-stage detection in the NHS Galleri trial, which we will submit to the FDA over time. But that's not going to be what they're focused on. They're clear that they'll be looking more for clinical validation and performance and safety. And so that's where we are with the FDA. On the NHS Galleri trial, I think we've talked about the clinical utility endpoint that's going to be really important for the whole field to understand. And there's a lot of discussion right now about what are the right types of intermediate endpoints to measure. Mortality obviously, is something that's been the standard for single cancer screening tests, but we don't believe that doctors and patients should be waiting a decade or more for mortality studies before having access to this well-validated technology. So we don't think that those studies are currently designed or powered and the NHS study was not designed or powered for a mortality benefit.

Our next question comes from Subbu Nambi from Guggenheim.

Can you guys can hear me okay?

Yes.

Perfect. On MRD, besides the partnerships with biopharma, what is the plan for clinical studies? And will you be doing single cancer studies or multi-cancer studies knowing that your test can be universal? Any thoughts on how it would compare commercial tests, bespoke and non-bespoke MRD tests?

Yes. Harpal, do you want to maybe take that one?

Yes. Thanks. So the first part of your question, yes, we would anticipate that MRD use cases would be cancer specific. But to sort of the other part of your question, but the same platform should be usable across multiple different types of cancer, but evidence needs to be generated probably on a cancer type by cancer type basis. We have not yet started any clinical studies, but certainly, that would be the plan in the future. And so that would be the anticipation. In terms of the performance, I touched on that, the feedback that we're getting from our pharma partners is that they're seeing sensitivity on a par with some of the tumor-informed methods that they're using already. So we feel very confident with our ability to have performance that's going to be acceptable in this marketplace. So I hope that answers your question.

Yes. Super helpful. And for the pretreatment prognosis product, how should we think about it commercially, mainly from a reimbursement standpoint and patients who are deemed eligible?

Yes. It's very important and good question. At the moment, the work that we're doing with AstraZeneca would be in the context of a companion diagnostic. And that's certainly the sort of development path that we're on there. As I said, it's already gone into 1 clinical study with AstraZeneca. And the idea there would be to think about neoadjuvant or adjuvant treatment of stage 1 non-small cell lung cancer patients. For those who are not completely familiar, the current standard of care with stage 1 non-small cell lung cancer is surgery and then no further treatment until there's a clinical reason to do so. So the idea here would be should we instead be invoking earlier adjuvant or neoadjuvant therapy. So at the moment, as I say, our focus is on its development as a companion diagnostic.

Our next question comes from Doug Schenkel from Wolfe.

So I do want to ask a clarifying question on data performance in a second, but I want to first talk about, I think, some business questions before we get into the data. So Bob, how would you characterize the political risk in the U.S. for GRAIL as it relates to CMS reimbursement and FDA approval hurdles heading into an election year? And how are you preparing for the different scenarios? So that's the first one. Second, and I think this is for Aaron. The company's situation with Illumina allowed it to really continue investment at a level that most others in the space haven't been able to do just because of how the world has changed over the last few years from a capital market standpoint. Keeping in mind where we are today and keeping in mind your move towards likely becoming a stand-alone company, how should we think about the pace of studies and your ability to invest at the same levels from an R&D standpoint? So let me pause there, and then I'll come back on the data question.

Yes. Thanks, Doug. A couple of things. So you saw really the FDA came out with their new guidance and rulings. We believe that Galleri is well positioned in that. Galleri already has breakthrough designation. It's out in the market as an LDT, and we're pretty deep into the PMA pathway. So we don't think any of the recent FDA ruling was going to have any significant impact on our Galleri program. On the other programs that Harpal has talked about, we are evaluating those. But kind of core Galleri, we don't think there's an impact given our progress on PMA. And so even in an election year, things could probably only improve from there. But again, we don't think there's risk on the Galleri side. So the political thing of an election at the end of the year shouldn't have impact. On our ability to invest, and I'll let Aaron jump in, in a second. But clearly, if we go as a stand-alone company, we're going to have to look very carefully at the -- certainly, any additional studies that we are doing. Many of the studies that we're engaged on are already well -- and you saw the level of enrollment. NHS is fully enrolled and its third year of study visits will end in July. PATHFINDER 2 is 30,000 of 35,000 participants already enrolled in. So we're already through kind of the bulk of it, and we're hopefully going to be on the -- getting some advantage coming out of some of these studies. We will clearly -- we'll have to look very carefully in terms of future studies and what we do there, but we're feeling good that a lot of the work has been done, and we're starting to see some of the benefit of that. Aaron, do you want to add anything to that?

Yes, I'll just add a couple of things. Doug, so as Bob laid out, the primary studies that are underlying Galleri brought access, those are wrapping up. Additionally, the study that we'll begin in is the CMS Galleri study, which, as Josh pointed out, CMS is covering the price of the test, reimbursing for it and then also the work up. So it will be a pretty efficient study to run from a capital perspective. Outside of the studies in R&D, where we mentioned we're launching the automated lower-cost version of the test this year. So that multiyear development effort will also be behind us. So between the R&D components supporting Galleri winding down or coming to fruition, we believe we've got levers through the rest of R&D and then in sales and marketing to change levels of investment as we need to as we cross these inflection points.

Okay. That makes a ton of sense. And if I can just sneak in 2 quick follow-ups. First, have you shared any data on repeat testing? And I guess in this context, define repeat testing as folks that maybe got Galleri done 1 year and then came back a year later and did it again. Essentially, what proportion of folks have ordered more than 1 Galleri test? And then just a clarification. Again, I could be wrong, and I may have misheard you, but I thought sensitivity on CCGA was around 50%, maybe a little bit higher. And then on PATHFINDER, I thought it was in the 20s. Is that wrong? I just wanted to clarify there. I think that's a Josh question. Sorry if that's off base, but I just want to make sure I'm clear on that.

No problem. Just to clarify, sensitivity was not -- the PATHFINDER was not a study that measured sensitivity. It was a small study with a 1-year follow-up. So that was not reported from PATHFINDER. In CCGA there were a couple of different sensitivity measures that were reported. One is, as Harpal revealed, the prespecified subgroup of deadly cancers that account for almost 2/3 of deaths in the United States, the Stage II sensitivity there was almost 70%. The 50% you're referring to was across all cancer types that were assessed in CCGA, including some cancers that don't shed DNA into the blood or very much DNA into the blood indolent cancer. So that's the 50% you're referring to.

Okay.

And then just to get -- you had asked a prior question about CMS reimbursement, just to share that there is bipartisan legislation that's been introduced to give Medicare. Bob mentioned this in his introduction, the authority to provide coverage for Galleri. It's not a mandate to cover it upon FDA approval. That legislation has a tremendous amount of support. Over 320 congressional sponsors, over 700 stakeholder groups supporting it. I think the stakeholders have really driven this whole process and made a great piece of legislation that is broadly supported across both aisles and in both houses of Congress. So we're very optimistic that even in an election year, that could get passed this year.

Our next question is from Puneet Souda from Leerink.

My first question is a bit of a clarification. Can you clarify what is your expectation for pricing in U.K.? And a related question on that is, how sustainable is the patient pay if the MCED reimbursement, as Josh talked about, there's support for that, but that was not to materialize. What I'm trying to understand is reimbursement is a very big consideration for any diagnostic, and how you get paid for these assays is what is the sort of protection to the downside if things were not materializing in for MCED? And if you could clarify on U.K. And I have a follow-up.

Yes. So maybe start off a little bit on the reimbursement. So right now, we're really looking at -- think about it as a phased reimbursement. We already have some large self-insured employers that effectively reimburse the test for their employees. So it's both a benefit for employees, but it's also reimbursed for them. We see similar things in the life insurance channel where many life insurance companies are paying for the test for in-force policyholders. Clearly, in the U.K., we're seeing the potential for a pilot, but then in 2026, with broad reimbursement there, the potential for that. So we're seeing across the board. There's a number of opportunities for reimbursement outside of kind of the traditional channels. Even the CMS REACH study was effectively reimbursing those tests for us. In the pathway where the legislation is, if we -- assuming FDA approval will have a pathway for the large commercial payers, but for CMS, to be able to pay, then clearly, we need the MCED legislation to go through. So there's various pieces that can get us there, can get us partial reimbursement beforehand. Obviously, CMS and the Medicare laws is an important one. If that was not to be there, then the USPSTF pathway would always be available as well, although the time frame on that is extended. Josh, do you want to add anything in there? And then maybe Harpal jump in on the U.K. pricing?

Yes. Just on the U.S., we've had numerous discussions with large national payers. As Bob mentioned, we have some progressive payer coverage, including a Medicare Advantage plan and others who are providing coverage for the test today, but that's very few. Think about this in terms of there's kind of the short game and the long game. The short game is the game we're in right now, trying to prepare the market for the eventual broad adoption, reimbursement and FDA approval of MCED test, kind of population scale. So in the short game, Bob enumerated that we've got self-insured employers. We have some progressive payers. We have a lot of self-pay, and we have the life insurance channel and some other enterprise channels that are working for us. But the large national payers have told us that they're going to really be looking for FDA approval. And so we feel like we have a good line of sight to that, and we feel like we have a high probability of success. So that's what we're looking at there. So that will give the payers -- the national payers in the U.S., the opportunity to provide coverage and serve the unmet need that they have in their populations. Medicare will be contingent upon the legislation. Otherwise, there's the USPSTF pathway, as Bob mentioned, which is a little bit longer, but obviously accessible. And then Harpal, for the U.K?

Yes, sure. Happy to do that. So look, first of all, to say, we do have a negotiated price with the NHS, but we're not releasing the details of that. So that's a commercially sensitive conversation that -- but we have -- we do have an agreed price. I think what I want to say is that, that is set at a level that would give us a healthy operating margin in the U.K. And the reason that I can say that is because we know that the way the NHS would run this, and Aaron alluded to this earlier, the way the NHS would run this is through a sort of centralized national program. So the need that we would have to invest, for example, in significant sales and marketing infrastructure is substantially lower than we need to do in the U.S. And that means that even with a lower price in the U.K., we're confident we can get a good healthy operating margin.

Got it. That's helpful. And then if I could just briefly touch on the primary care sales force. The size of the sales force needed in the U.S., if we compare it to a current peer company that has a product in CRC screening markets, those numbers are reaching in low 100s or close to almost 1,000. That would be a significant OpEx. So maybe a question for Aaron. How are you thinking about the broader sales force expansion, I would say, potentially after 2026? And potentially doing that in a more capital-efficient way. Is there -- are there -- what are the approaches that you're thinking about on that front?