Guardant Health, Inc. (GH) Earnings Call Transcript & Summary

[Presentation] Please welcome to the stage, the co-CEOs of Guardant Health: Helmy Eltoukhy and AmirAli Talasaz.

Well, thank you for joining us at our inaugural Investor Day today. It's been 5 years since our IPO. And looking back, it's really remarkable how much we've accomplished in those 5 short years. Given where we are today, we felt it's a good time to refresh the story and share what we expect the Guardant road map to look like for the next 5 years. Here's our safe harbor statement. We'll be making some forward-looking comments. And here's the agenda for today. We have a pretty action-packed day. We are going to dive into smart liquid biopsy and talking a little bit about how that technology works. And then we'll give an update on each of our businesses: Therapy Selection, MRD. We'll talk about our platform for commercialization on the oncology side and then give you a chance for a little bit of Q&A. Short break. And then AmirAli will take us through a deep dive in terms of our Screening business. And then we'll have a very esteemed panel today to really talk about some of the work that's being done in the field in terms of epigenomics and really how important that aspect of human biology is. And then Mike will walk us through a financial road map for the next few years. And then we'll close it out with a look into the future, followed by Q&A. So let's get started. We founded Guardant Health 11 years ago with a bold mission of giving us all more time free from cancer. Too many people we knew were blindsided by the disease, and we wanted to create tools that would help safeguard our families, friends and loved ones from the disease. So we had this crazy, audacious goal of conquering cancer and knew that the greatest equipment in our fight would be data, lots and lots of data. We didn't know how much data would be needed but knew that the more we collected, the better our chances were for success. So how do we unlock orders of magnitude more data? Every technological revolution that we have enjoyed over the last century has been the result of a major paradigm shift. We know one of these technological improvement curves is Moore's Law as it relates to the integrated circuit era of computing. Yet the era of integrated circuits actually represents a fifth paradigm shift in a long string of exponential increases in computing capabilities over the last 120 years. Each paradigm shift unleashes an S-curve that ushers in a fantastic era of new applications and technological progress. And we realized to get to the data that we needed, we needed to do the same thing for cancer. That is unlock a new S-curve or a series of S-curves to enable us to acquire a lot more data than ever before. This is where the liquid biopsy paradigm was born. By being able to track tumors via blood rather than through surgery or invasive tissue biopsies, we realized that we could greatly speed up the rate of biological data acquisition. And if we started with commercializing liquid biopsy at scale for advanced cancer patients, we could use that data as our compass to lead us towards maybe one day achieving the moonshot of early detection of cancer with a simple blood test. But paradigm shifts aren't easy. If they were, they would have already happened. Like clockwork, history repeats itself, and almost every paradigm shift has its nay-sayers and its doubters. Many of them represent the incumbents of the current paradigm, trying to hold on to their existing business or way of life. Liquid biopsy was no different and continues to have vocal opponents. Over the last 10 years, this is a small sampling of what we have heard many so-called experts say about liquid biopsy, that liquid biopsy cannot detect late-stage disease in blood. That's when we first started. It's too expensive to run at scale, is unproven and unreliable, only detects uninformative cancer information in blood that are not representative of the tumor, will only be used for niche applications, cannot achieve high performance for MRD without tissue and cannot detect early-stage cancers with high sensitivity. But time and time again, we have proven these so-called experts wrong.

And since founding days of Guardant back in 2012, we delivered on the promise that we made, first to ourselves, second to our community to build several products across continuum of care. Starting with Guardant360 that we launched back in 2014, OMNI in 2017 and then delivering on the promise of the IPO, getting the FDA approval, first FDA-approved CGP liquid biopsy test, and launch of a bunch of other products, to deliver products across continuum of care. And finally, at the end, fast forward into last year, with launch of INFINITY as the next-generation liquid biopsy assay, which right now is available for biopharma and Shield. Now we are the only company and the first company who has really good offerings across continuum of care. And this is what we are serving across continuum of care. We started from advanced cancer sites strategically to gather the data that Helmy talked about, where the tumor levels are much higher and we can gather this insight much faster. Then we went to survivors, 15 million people that could potentially benefit from our offerings. And finally, average risk cancer screening with a big potential for 120 million people to basically answer these simple questions. And this is the products that actually we develop across continuum of care and how they are getting mapped to this cancer journey. For 700,000 patients, Guardant360. Guardant360 CDx, TissueNext, Response for residual disease monitoring, Guardant Reveal and finally, as I mentioned earlier, Shield for the field of cancer screening. And where are we now? More than 500,000 tests has been processed in cancer patients, ordered by over 12,000 oncologists with the data treasury for Guardant of over 20 petabytes and also 500 -- more than 500,000 clinical samples in our biobanks. And this is just Guardant at a glance. 2023 revenue mid-range, about 550, more than 160 biopharma partners being in more than 60 countries, and a very innovative company, with having more than 600 patents and patent application at the global scale. And our values is what unites all of us at Guardant. The value drives us to a common goal. We are putting patients first. It has been our commitment and will be our commitment to treat patients as our own family members. We are stronger together. The teamwork, spirit and culture of caring at Guardant is amazing. We are trailblazers. We are committed to innovate and not afraid of taking calculated risks, and we make every moment matter by our commitment to excellence, velocity and impact. This what describes what Guardant is about. We are pleased that this year, Guardant got certified as the Best Place to Work, based on employee approval rating of 80%. We are over 1,700 strong employees, with over 195 MD PhDs, with strong gender and ratio diversity of 56% female team members and 60% ethnical diversity. What I talked about proudly is mainly about what Guardant has done so far. I'm even more excited of what Guardant can do and will do in the next chapters. And this is just the beginning for us. With that, I would like to introduce Dr. Darya Chudova, our Chief Technology Officer, to come to the stage and talk about the technology. Darya?

Good morning. I hope we are prepared for a little bit of excursion into biology and science, that underlies what we do in our technology. I'll take you on the journey of what we were able to accomplish over the last 10 years, with evolution of our technology that radically changes how we can see cancer in blood today. By the end of it, I also hope that you see that the data generation, that will be enabled by this platform, by this technology, will enable our future expansions and new products as well. Since Guardant pioneered liquid biopsy 10 years ago, we've developed -- we have returned 500,000 patient results that inform physicians and patients about clinical care decisions in advanced cancer. We also delivered what was believed to be impossible at the time, due to scant amount of tumor in circulation. We couldn't go and pick a technology off the shelf that could do that. We had to step outside of those boundaries and develop proprietary biochemistry and proprietary analysis to reach that goal. And with the sensitivity and specificity of that technology, we created a new category of tests that has become synonymous with adequate cancer management in late-stage disease. As much of a progress as it was, we quickly realized from the data we were generating, from the scientific development at the cutting edge in the literature, that what we have is not enough to extend into early-stage disease and early cancer detection. In order to do that, you had to enable 10- to 100-fold increase in sensitivity for tumor detection. And that's what we were able to achieve. We achieved that with the power of our smart liquid biopsy platform. It rests on 2 keystones. One is the concept of liquid biopsy itself, where you can rely on simple blood draw that's accessible, and gets a lot of patients able to access the tumor. It's agnostic to the tissue side, where the tumor originates. It captures whole body heterogeneity and it allows you for temporal sampling of the tumor over time. But the key breakthrough to get through that 100-fold increase in sensitivity that was needed, was adding epigenomics components to our platform. It allows deeper tumor sensing, which is what you need, in order to reach early-stage patients and impact lives. It allows wider biological view, which is what you need to have full of representation, not of just tumor genomics, but also of the whole body response to the tumor. We deliver that with high performance using a revolution in how we do the biochemistry of the assay and analysis of the data. We made critical design choices in that platform, given the richness of data that it generates, we're able to generate it with high efficiency and low cost. That in itself is the reason why our commercial data generation with commercial testing is able to yield volumes of data that we continue to use to optimize the system, and make the next leaps forward. Today, these 2 technology cornerstones deliver 100x genomic breadth and 50x higher sensitivity at no additional cost, in comparison to what Guardant360 could do 10 years ago. So we talk about epigenomics as a solution here. Let's walk why -- through why this is so useful. There are 37 trillion cells in your body, and they all share the same genome, which makes you immediately ask, how come my liver cell is different from my heart cell and different from my blood cell and what they do, if they all have the same genetic code. The reason for that is epigenomics. Through that lens, every cell type in your body looks different. Moreover, through that lens, disease state for a cell, looks different from its normal cell, state. And that's what we're able to harness, to get that power of detection that we need. Let me walk you through a little bit of underlying biology. So we can all start appreciating how the data that we keep talking about, reflects the complex biology of the tumor in blood. So we'd say epigenomics, and epigenomics is what controls how our cells function. If you look at your blood cell, which protects you from infection, or your liver cell which generates bile among other things. The way -- by which this is happening in the cell is through functional activation of certain genes that allow 1 function in 1 cell and silencing of that gene in another cell. The silencing is implemented through the methylation control, as a key determinant of that cell type. These methylation switches effectively, either enable a gene to be functionally active when the control regions are unmethylated unmet weighted, or require the gene to be silence, when those regions are methylated. And so we'll use epigenomics and methylation a little bit synonymously here in the stock, even though they're not exactly the same. But we will use the power of these switches to understand what happens in the tumor, and to understand what's happening at the system response level. This is a single gene. You can step outside of that into the whole genome, and that's where you find the power. The power is there. Tens of thousands of these epigenomic control sites in your genome, that together, define the fingerprint of each of the cell types. Your blood cell and liver cells will have a lot of these switches turned on and off in common. They will have enough of them to be distinct, where you can differentiate each cell based on that information. And as we mentioned, if you look at the liver cancer cell in comparison to a liver cell, you would almost, in the same manner, find unique fingerprints that differentiate cancer state from healthy state. The power of this is that there are thousands of differentially methylated regions that differentiate cancer from a normal cell. This is real data on the left-hand side of what happens when you measure that in blood. Here, you have a number of colorectal cancer patient samples, profiled with our technology and contrasted with healthy patients. Showing this differentiation at a pretty wide genomic level, allows us to see clearly through that blood sample. So let's talk a little bit about the reason why is the fact that there are thousands of these markers is so important. Imagine a test that relies on genomic analysis of the tumor, and whether it's Guardant360 tests that were developed initially, or a tumor-informed assays that are sampling up to 50 mutations in a sample, you are fundamentally limited to measuring 10 to 50 mutations in a given patient sample. When you open the epigenomic aperture, you're going to be able to see over 1,000 tumor alterations. So now imagine that you're diluting that sample down, and for early-stage disease, you're shedding less cancer into the circulation. You're that much faster going to lose the signal, from 10 to 15 -- to 50 alterations that you're going to lose the signal from 1,000. That is the why epigenomics allows us to be here where we are today. So let's switch now from why we want to do this to how we do this, and walk you through a couple of insights into that process. Smart liquid biopsy unlocks both genomic and epigenomic state from a single sample using a single workflow. We do this by extracting the circulating tumor fragments from the bloodstream, and in order to access genomic and epigenomic information simultaneously, we had to develop proprietary methods that do 2 things as their most important components. One, we tag cell-free DNA molecules with specific barcodes based on their methylation state. And we also deplete molecules that are believed to be noninformative to what we do -- want to do with the inference from that system. Once we've done the stacking and background depletion, we can do regular sequencing and then extract from each molecule information about it's genomic composition and methylation state. An attempt to restore the fingerprints that we talked about, that separate cancer and noncancer samples, disease and not disease state of the cell. That creates, given the basis of information for an individual sample, and millions of molecules that are getting sequenced and interpreted in this manner. And clearly, you need to have pretty heavy machine learning, statistical methods, AI-inspired technologies to interpret that data to come up with simple answers that quantify and characterize the cancer. Well, you can say people have done genomic testing for a while, people have done methylation-based analysis for a while. What's so special about what you do here that cannot be replicated? Let me walk you through a couple of aspects that we believe are key to that answer. We talked about single simple workflow. That's not easy. Traditional bisulfide methods will be destructive to the genomic component that you were trying to assess methylation, and if you're dealing with advanced cancer patient, who needs a treatment decision, you clearly need genomic information. And so you need to be able to non-destructively preserve your genomic cancers and epigenomic cancers in the same sample. That's what we're able to do. Second, and we went a little bit deeper into that already is genome-wide profiling, where you need power of thousands of alterations to overcome the dilution of the signal in a blood sample, and being able to see the top of the iceberg, when the bottom becomes invisible. You need highly efficient molecule capture. Every molecule that comes from cancer in that sample matters. We spend a lot of time optimizing our workflows for efficiency, to be able to recover as many cancer molecules in that sample as we can. Today, we generally generate 3x as many signal molecules in our sample prep as you would expect to generate with a conventional bisulfide workflow. We're also far ahead of some of the newer enzymatic methods, that have been developed in the recent years to increase that efficiency. We talked about costs, and that's where very, very specific background depletion comes into place. So we don't have to sequence molecules that are not going to be informative to our answers. We're 99% efficient in that depletion, which allows us to, again, reduce the cost of the assay -- of sequencing part of the assay by about sevenfold in comparison to, again, conventional workflows. Now on a little bit of a different angle, in comparison to some of the biochemistry improvements here. We are heavily relying on continuous improvement, powered by samples and data biobank, that we generate in our commercial testing. Over the years, we've gone through multiple series of improvements in how we can do variant detection, how we can maximize signal to noise in our samples, how we can learn from different complicated biological corner cases, in order to improve our sensitivity of detection. And so being ahead on that exponential growth curve, absolutely helps us get outperformance to the levels that are hard to attain, if you are a new entrant into the space. So we talked about why. We talked about how. Let's talk about so what, which is probably more relevant to some audience here. And with that, I want to take us back to the questions that AmirAli shared, that are driving us to work every day. Do I have cancer? Do I still have cancer after intervention? Has my cancer returned? Am I responding to therapy? What therapy choice is best for me? Let's see how the power of liquid biopsy allows to answer these questions, with more clarity and with more precision. Let's start with screening. We're showing here clinically relevant analytical detection capability of our platform for screening. What makes it clinically relevant? Let's look at that chart. So widely known that late-stage disease sheds more into the bloodstream. The Y-axis here shows how much shedding has it earned, roughly on the order of 0.1% to 1%. This is well within the detection capabilities of traditional genomic panels at this point in time, 10 years later. And so these methods are fully adequate to assessing blood samples for mutations in that range. What you also see, is if you go to Stage 2 and Stage 1 disease, there's a 10 to 100-fold lower level of tumor shedding into the bloodstream. What we show here is with our epigenomic components of smart liquid biopsy, we're able to attain detection limits that allows us to see samples above that line, which goes very deeply into early-stage disease. That's the 50x improvement in sensitivity that we started the presentation with. For the second part of the question, "Do I have cancer?" This is a clinical context for early-stage patients, who has had intervention to remove the tumor, and is interested to find is there any molecular evidence of residual disease to inform the best course forward in terms of therapy or subsequent treatment. For the first time, we're sharing today that clinically relevant minimal residual disease detection can be attained by the tissue-free assay at high specificity, above 98%. The data shown here takes us into multiple cancers, and approximately 0.1% detection limits, as estimated from our analytical data. I'll present a lot of analytical data in this part of the presentation. We'll leave clinical performance to the sections where we talk about products. But this is the basic foundation on which our clinical detection capability rests, and provides a way to understand how we're able to get there. Now the performance that I show here is estimated for the most challenging samples, samples that yield the lowest amount of cfDNA. This is roughly a 5-nanogram limit. The reason why this performance data is relevant, is that over 95% of clinical early-stage patients have enough DNA to meet the 5-nanogram requirement. If you look at samples that would have 30 nanograms or 60 nanograms of material available, you're looking at the tail of the distribution of clinical samples. And so when you talk about performance, it's important to be able to describe it in the relevant domain of sample input. So we can detect cancer, whether that be in a symptomatic individual or post intervention. The next question that is relevant, is quantification of the disease. "Am I responding to therapy?" That question very closely correlates with how the dynamics of your tumor in circulation looks like over time. Responding patients, which show a declining level of tumor in circulation and vice versa. So what's important here is that only can you sense the tumor deeper with those methods. But can you measure the tumor fraction with precision to be able to say when there's twice as much tumor in my post-treatment sample than before? Is that a reasonable change? Is that valid change? Am I within the noise of the system, and I can't really tell you where you are? Or I'm going to have enough precision in that estimate to know that a twofold change really tells me you are responding to treatment. And so epigenomics, with access to thousands of biomarkers, gives you that precision that you need to manage patients based on the dynamics of the tumor response. Not only is it important in clinical cancer management, but it also opens up opportunities in translational research, where you could start using precise estimate of tumor fraction at low levels, to assess response in early phase trial is a much faster readout. You can start developing surrogate endpoints, around quantification of tumor fraction, based on more precise estimates. And finally, you can explore novel clinical trial designs, which switch patients away from standard of care, based on lack of response and enable clinical trials to go in a faster truck. So there's a lot of applications that are opened up, when you can measure the amount of tumor in circulation with precision. Now we've finally come up with the penultimate questions of where we started, "What therapy is best for me?" This question is answered with Guardant360 for the last 10 years, and has been a product that's leading the market with best-in-class performance today, for informing therapy selection decisions. We haven't stopped there. And in liquid biopsy, we're opening up new genomic modalities that we will be able to see with the help of that platform. That includes enhancements in a lot of the [indiscernible] classes that are listed on the slide. We're going to tackle hardest genes that are in the genome. We're going to look at typing HLA. We're going to look at HLA losses, which are all known to be resistant markers for I/O, and open up a lot of other applications with that shift. We are adding novel components to that system for viral detection. Regulatory epigenome is something we'll talk about a little bit on the next slide. And we're starting to see glimpses of immune system response through the data we generate with that platform. So on the epigenomics side, what do we see differently in that smart liquid biopsy output, in comparison to what Guardant360 can do today. It's well known than some mechanisms of mutations will deactivate genes through genomic mutations. It's also known that those genes can be deactivated by methylation of these controlled regions. That's completely blind to the genomic testing. And so you are able to uncover the mechanisms of gene deactivation, that are blind in both tissue effectively, and liquid testing today. And maybe that's an important point to make. It's not only opening up accesses to that information in blood. It also, for the first time, provides a clinically reliable sample material, which is a blood sample, to assess it as methylation analysis, otherwise would require fresh tissues that are much harder to obtain, and not regularly part of the workflow for a majority of the cases. So this is your first attempt. It's unlocking, for example, 25% of triple-negative breast cancer patients, whose cancer genomics is explained by the promoter methylation of the BRCA gene. Without analyzing that, you'll be missing patients, who are eligible for PARP therapies, and this opens up that view. You can extend this to other cancers and talk about colorectal cancer, where MLH1, promoter methylation, similarly would give access to therapies to patients who were previously not seen through the genomic lens. These are examples of traditional biomarkers that are known in this space, that help us fundamentally change how we answer questions on this slide. With that data, we can also start asking new questions, which is, what kind of cancer do I have? What is the subtype of that cancer? How my immune system responding? And I'll show you just proof of principal slides on some of this, but there's a lot of work going on internally, to interpret this data in the sense of new signatures and new biomarkers that could be uncovered by the epigenomic profiles. The first one is just figuring out the source of the tumor, which is called tissue of origin. So tissue-specific fingerprints are known in the literature to be very distinct between different tissues. We're also able to see it in blood on the right-hand side, where you can see the different cancer types produce different patterns of epigenomic signals when we measure that in blood. Into a little bit more esoteric area, let's look at subtype in cancers. This is an example of a breast cancer, and we show for the first time that fingerprints differentiating breast cancer subtypes, which traditionally will be assessed through IHC of the tumor, are detectable with smart liquid biopsy. What are we talking about? We're talking about hormone receptor positive and negative breast cancer, which confirms very different prognostic and therapeutic modalities for management of that patient. What this tells us is by measuring liquid -- the patient with liquid biopsy, we can see and identify that. That's a mechanism to expand precision diagnostics. That's a mechanism for potentially identifying all response predictors in that data as well. So all of this technology can be unified and deployed against different applications, different disease states and different aspects of continuum of care, which means that in our labs, we can unify the process by which we answer these questions at scale, by deploying similar technologies across the continuum of care. It has 2 implications. Number one, you are able to leverage performance improvements and learning from the data. One of the things that exceptionally difficult and diagnostic development, is obtaining relevant cohort for training and for generating your signatures. We have been successful already, by cross-pollinating across these applications, and enhancing our performance in this way, and we'll continue to do so. The second leverage is obviously operational advantage. And so if you imagine any improvements we can do in screening to bring it up to work at scale, and lower the COGS and lower the operational complexity. They would apply to our oncology suite of products as well. We are a technology team that is committed to going from simpler to more complex, more complex biology, more complex science and more complex engineering. We're learning from data for continuous improvement. And we're looking for technology paradigm shifts to radically change our capability. We have done this twice, as you see on this slide, when we developed initial liquid biopsy and when we added additional capability with epigenomics to reach deeper into the bloodstream. We're going to continue to do so and bring new applications and new S curves to this image. Now the landscape of biomarkers in blood is exceptionally rich. We've started by uncovering genomic features with Guardant360. We've just shown how we can go to the second layer of that richness, through analysis of epigenetic features, we're not done. We're going to explore that layer further. We're going to explore the third layer, with other derived targets that are known to be present in blood. There are 3 courses of diagnostic development. One, a small sample size. The other one is lack of relevant cohorts for development, and the third one is confounding, that often makes you think you have the signal, when you actually don't and you're observing confounding effects. With the biobank that we have accumulated, with the experience we have accumulated, sifting through that noise, we're able to explore the layers of that circle and have high fidelity answers to what works and what doesn't. With that, I hope you can see the value of what we have been able to achieve with a paradigm shift and the value that will continue to come from the data that we start generating at scale with that new platform. Thank you. [Presentation]

Please welcome to the stage, the Chief Medical Officer of Guardant Health, Dr. Craig Eagle.

So one of our core values, that Guardant is putting patients first. And we think about each patient, as if they're a family member. And you heard on the video, some of the examples that the physicians are experiencing, with precision medicine and therapeutic selection. And what I want to do through this section is just walk you through in a bit more detail, how this impacts patients and how the technology is really changing the way we think about cancer therapy and treatment. So I just want to start. You've seen this slide a few times. I just want to highlight a few aspects of the slide. Obviously, this is a patient journey from left to right. The size of the bubbles represent the bulk of the tumor as measured molecularly. The different colors represent different subparts of the cancer, based on the molecular diagnosis. And you can see in the line below, with the solid gray bars, the treatment sections. And as that tumor responds to treatment, treatment started when it's at its bulk, the tumor shrinks away. Traditional oncology relied on a tissue biopsy right at the beginning of the journey, and then CT scans to measure the bulk of the disease, with no way of telling the molecular subtypes without repeat biopsy, and trying to find the tissue somewhere in the patient's body. So as we think about cancer care, the products that have been mentioned before are listed below, that I'm going to walk through in this presentation. So just to remind you of some of the products that we have. So we've already talked about 360 CDx, how it was the first liquid biopsy FDA approved. A simple blood test to give critical information about the biology of the cancer at the molecular level. Guardant360, similarly. As we move across and think about the CAT scan and response, how do you monitor disease molecularly, but through response. And you heard from Darya, that can be genomic or even potentially, bring the power of epigenomics into that measurement. And finally, cancer can't be complete without continuing with tissue, because a lot depends on tissue. And so when you start to combine the information in blood, with what you combine in tissue, then you'll end up with a very powerful look of what drives cancer at the molecular level. All these products are currently reimbursed and Medicare approved. So therefore, physicians, and as I mentioned, the impact to patients, is easily accessible now. So the real question becomes, how does it get used? So that leads to this particular case. This is a young lady who presented with some visual disturbance and abnormality. On further investigation, she was seen to have a tumor in her eye. Neither that -- on further examination, she had cancer in the lungs, in the bones. The biopsy of the lung tissue and you have already the first example of getting tissue was a challenge, when you think about trying to get something from the lung, revealed that she had a mutation called ROS1. This is a gene that controls cell growth under normal circumstances, but in the cancer, it's linked to other control mechanisms that allow cells to grow out of control. And as you can see from the time line across the top, you can see the different time points, if you look at the blue dots of where her cancer changed and progressed. And you'll note that at times it progressed, it was in the brain or the bones. These are very difficult areas to get tissue. Down the bottom, you can see that you went through different therapies. Most of these therapies are FDA approved for ROS1. But through her journey, you can see that there were changes in her cancer has highlighted, particularly by the red changes. So you got F2004. This is just a single amino acid change in the cancer driving protein of ROS1. That single amino acid change determines how a drug binds and blocks that growth protein. And so as a cancer responds to therapy, clones and subclones of that cancer start to survive, that have amino acid changes that make that drug irrelevant. So you can see at the bottom at multiple time points, each time point that her disease progressed. A repeat biopsy, liquid biopsy to identify the molecular driver of her cancer progressing was taken, and then the drug responds and gets around that mutation, that resistance was prescribed. And interestingly, if you go all the way to the right, she ended up on 2 drugs, cabozantinib and alectinib. Alectinib gets into the brain, where the cancer is a problem, but it doesn't treat the mutation that she had. That mutation required a drug that's traditionally not used in ROS1, called cabozantinib. The 2 drugs were combined based on the liquid biopsy that demonstrated these 2 amino acid differences as sub claims to control both the disease in the brain, and the resistant disease. And then she proceeded to have a molecular response, as measured by the molecular amounts of the mutation in the blood. So overall, she got 7 different treatments, multiple cancer assessment biopsies all with the ease of a blood test and Guardant360. Similarly, she had molecular response measure, how is she going with the treatment. Also taken from a simple blood test. So this is the real impact that the technology that Guardant's working on in the future of cancer care, because 5, even 10 years ago, this would not have been possible without continuous molecular assessment of a patient with cancer. So I just want to change a little bit now and say, well, how do you get there? So one of the things that's absolutely critical from our perspective, is putting the scientific literature and scientific proof out in the community. So we've delivered over 425 scientific publications in collaboration with 45 national cancer institutes across the country. And many of those publications have been about patient outcomes, how to treat them better to get better outcomes, like the case I showed you. They've changed guidelines, and they've convinced payers to reimburse the products for the users that are intended. So we are actively driving the conversion of the sites to where it impacts and that's the patient life. Here's a recent example, only about 6 weeks ago, of some of this evidence in real-world data. This is from University of Pennsylvania. They looked at 326 lung cancer patients. And they looked at how soon or rapidly -- they had a test to look for the molecular driver of lung cancer. And if you had the test done upfront and straightaway, your response to therapy is the blue line. If you couldn't get the test results before needing to start therapy, it was the red line. Now this is real-world clinical practice in lung cancer. So this demonstrates a survival benefit, when you get the CGP testing or the complete genomic profile upfront as rapidly as possible, before starting any therapy. The other interesting piece about this paper, is it also suggested that you're more likely to get it if you combine the tissue and the blood test at the same time. And you heard in the video, one of the cases where they couldn't find it on tissue, for example. So the speed of getting to the right molecular diagnosis, to get the right therapy selection, makes a big difference. Just focusing now on response. So that's great. We selected the therapy. How could we change the paradigm of cancer care, with following up on response to that therapy? So as I mentioned, a lot of that is related to CAT scans. So really, the question becomes on a molecular basis, what is it that we want to achieve with a molecular basis? Well, first up, we want to be able to accelerate insights, leverage that insight and the future insights that Darya talked about with epigenomics. Response, response to what subpart of the tumor? To what tissue is responding? Also, this will help with clinical trial that was mentioned in methylation and breast cancer, colon cancer, identifying patients that we couldn't identify before. We have a tissue-free approach, just a simple blood test to see how you're going, with a lot of information, improved sensitivity, and with the speed of return real-time response information for the physician and the patient. So the question becomes, how does that compare to CT scans, and so you can see here that a simple blood test measuring response delivers the same equivalent information, as currently available to physicians with CAT scans. Is my tumor responding or not? Remember, it gives extra layer of information that we're just building out now as well. So it even gives more than what a CAT scan will give you. But importantly, you know it nearly 2 months beforehand. Now most therapies in oncology historically have been a month cycle. So we're talking about knowing if someone is responding with a molecular test, while someone is still getting chemotherapy for 2 more months before the CAT scan tells them, it's not working. So the molecular response is also another way that we're thinking about how to enhance that impact on cancer. And finally, tissue. So as mentioned, we're looking at tissue and liquid, and combining this information is critical for cancer care. And so we've developed the first CGP, tissue biopsy, and it's improved PD-L1 scoring and diagnosis by 20%. More patients are identified. It's now validated, and it's across multiple cancers, and it's available also through reimbursement through Medicare. So combining these bits of information from blood and tissue and bringing the power of response, really helps determine therapy selection and the outcome. But where to from here? So this is just to illustrate that the world is rapidly increasing the number of therapies, the number of targeted therapies and the number of choice and the selection gets more and more complicated, just purely on the number of options available. And you can see just over roughly 15 years, how it's grown and is continuing to grow rapidly. So the need for precision therapy selection is only going to increase and get greater. Here's a recent example. ER-positive, HER2-negative breast cancer. Breast cancer, one of the most common, sadly, cancers in the community and one of the ones that sadly, still to this day, has a poor prognosis. Recently discovered when women are given hormone therapy, if they're not responding to hormone therapy, a molecular driver called ESR1 becomes mutated and keeps driving the cancer through that hormone therapy. These mutations are seen in up to 40% after they start therapy. Again, how do you assess that? You can't get tissue easily. A very simple, quick blood test to pick up ESR1 and put them on a specific therapy for this mutation is only something that's recently come out at the beginning of this year. So now in breast cancer, there's a dire need to diagnose this in women, who are progressing on current therapy. So really, you can sum up where we're going with precision medicine and therapy selection in this sort of diagram. So I've demonstrated that we're basically going to more lines of therapy. Think of that case, that young lady, 7 drugs, even down to a drug that wasn't traditionally used for lung cancer, unheard of 10, 15 years ago. We're going across more tumors, I just shared with you about breast cancer, ESR1, something new for this year, that now requires a molecular test if people aren't responding. And then if you go deeper into the beginning of the cancer process, as we learn deeper into the technology with blood epigenomics, we're able to bring those therapies earlier and earlier into the cancer journey for people. So this is a rapidly changing environment. And for me, a rapid and changing environment that is really bringing immense benefit from satisfaction to conquering cancer. So really, we're still going to be part of that forefront. So where is the future from here? We're still committed to expanding with research in the therapy selection area. As Darya and her team bring the new technology forward and we learn more and more about what's going on the blood and cancers, we've got research programs already gearing up to demonstrate the benefit to patients, spanning multiple tumors as well as with multiple partners and collaborators. Thanks for your attention. [Presentation]

Please welcome Co-CEO of Guardant Health, Helmy Eltoukhy, back to the stage.

Okay. Let's dive deeper into our MRD business here. As we mentioned before, MRD is really for a market of about 15 million early-stage patients, cancer survivors, really trying to answer the questions that they're worried about. Do I still have cancer, and has my cancer returned? Really trying to give those patients what we call quantitative peace of mind. So we have Guardant Reveal in the market today. It's the only tissue-free MRD test that is available in this space. We launched it in 2021, and it's the only test where no tissue biopsy sample is required. It's currently available for colorectal cancer, breast and lung disease. And we continue to make rapid progress with the platform, powering Reveal. As an example, we recently introduced precise quantification into the assay, and we are on track for a major upgrade to smart liquid biopsy this year. As a reminder, this is a $20 billion market opportunity and is still in the very early stages of development. Product market fit is a key to winning any new market category. We believe that product market fit for MRD tests rests with an assay that is a true liquid biopsy. That is a test that does not require tissue. This is because it's faster, not requiring a tissue biopsy for the initial results, enabling results in days, rather than weeks. It's easier enabling monitoring of patients that don't have tissue in the neoadjuvant, adjuvant settings and for survivors that are years out from surgery. And finally, it's in a category of its own in terms of power and utility. Rather than just telling the physician if the cancer has recurred, Guardant Reveal and our smart liquid biopsy platform will uncover the why and what to do next. Tracking of disease in high precision, regardless of its continued evolution or if new clones have emerged. It will work seamlessly with other tests in our portfolio to reveal the underlying actionable mutations that can tell a physician what treatment option to apply next to their patients. And this is just the beginning of MRD testing powered by smart liquid biopsy. There has been a lot of noise around tissue-free MRD. Lots of people saying it's hard, it's impossible, has low sensitivity or low specificity. And it's true, tissue-free MRD detection isn't easy. Just like wireless technology or reusable rocket technology was hard. Every major technology shift has many naysayers. But when these shifts happen, it's magical. A beautiful thing that was suddenly obvious to everyone. I saw this with the shift to NGS from Sanger and hybridization arrays and with liquid biopsy for therapy selection a few years ago. And we will do it again for tissue-free MRD. So there are 3 steps to making this happen. The first is the technology, which, as I mentioned, is not easy. There's nothing off the shelf here in terms of the approach. One, it takes a revolutionary methylation chemistry that Darya walked us through earlier today. Petabytes of data to achieve the right classification accuracy and lots of machine learning, powered algorithmic development to achieve high sensitivity with very high specificity. Two, it takes mountains of clinical data to achieve reimbursement across dozens of tumor types. This is a requirement for any MRD test, not just ours. And three, a strong and well-established multi-hundred person commercial team to serve as a 12,000 oncologists in the market. So let's dive a little bit deeper into number one here. We can achieve high performance since our methylation chemistry is tracking over 1,000 alterations per patient, versus just the less than 50 or so that tumor-informed assays are tracking. This leads to high sensitivity. We have a low background methylation chemistry that leads to ultra high specificity, and we maximize overall accuracy by applying machine learning to thousands of clinical samples. Two, as I mentioned before, it takes really a mountain of clinical data for validation of any new technology, just to gain initial Medicare reimbursement. As you see in this graph, mapping a dozen-plus indications against dozens to hundreds of patients per indication and against multiple monitoring samples per patient, with 2 to 4 years of follow-up, one faces what is known as the curse of dimensionality and the need for collecting tens of thousands of samples over a number of years, to establish a business with an adequate reimbursement rate in the MRD space. I'm pleased to announce that over the last 4 years, we have been quietly accruing thousands of samples across 17 indications. We have now secured over 80,000 clinical MRD study samples comprising 18,000 patients, to help us establish the validity and utility of our smart liquid biopsy assay. As we speak, we have been diligently running these samples with our smart liquid biopsy technology, and have generated some really exciting data. And we promised earlier -- as we promised earlier this year, we'll be presenting a number of these cohorts, including cohorts in colorectal and breast cancers later this year. And I'm pleased and I'm very excited to share some of this data with you today. This is data that is hot off the press from our COSMOS colon study. This study comprised stage 2, 3 receptive colon cancer patients, and we achieved 80% sensitivity for detection of disease, with 99% specificity. This data is being prepared for publication, and we expect it to form the basis of our CRC surveillance Medicare submission for Guardant Reveal on smart liquid biopsy. I would also like to highlight a few additional studies, 1 in breast cancer that has been submitted for presentation at the San Antonio Breast Cancer Symposium later this year, and aims to establish clinical validity for Guardant Reveal in a cohort of 300 early-stage breast cancer patients. I want to note that the median follow-up for the patients in this study was 66 months or over 5.5 years. Another study we are excited about is Pegasus. This is a Phase II deescalation clinical utility study in colorectal cancer. This has been submitted for presentation at the upcoming ESMO conference this year, and we are excited for the results of that study. And on the longer-term side -- in terms of longer-term readouts, we have a larger study that was announced earlier this year TRACC, which is a Phase III deescalation study in colorectal cancer that will comprise over 1,600 patients. And last but not least is number 3. One of our biggest assets as a company is our oncology commercial team, whereby we can continue to cost efficiently commercialize Guardant Reveal, by tapping into our current field force and eventually by tapping into our screening commercial team. We will continue to gauge promotion, based on achieving successive reimbursement milestones and associated ASP increases. In addition to the CRC data, we believe we will have data readouts, as I mentioned, in breast, and potentially other indications that will enable submission for Medicare reimbursement next year. So where are things going in the oncology space? As we look ahead at our therapy selection MRD franchises, it is clear that the future of oncology is one single workflow paradigm. Therapy selection will move earlier and become a standard of care for all cancer patients, not just the metastatic ones. Better therapies will extend lives and patients will require testing to determine the next best choice for multiple lines of therapy. Disease will be managed adaptively and proactively, enabled by monitoring at all stages from the neoadjuvant setting for each line of therapy and onwards through survival. Our smart liquid biopsy platform sets us up well for this emerging paradigm, whereby a physician can just push a single button anytime he or she needs additional information and be guided to the next best option. But this is only the beginning. Our test is often compared in an apples-to-apples fashion with those of our competitors, where we are going with our technology is just not possible with other tests. Our tests built on this new platform will enable a simple blood test, to not only tell a physician if disease is present, but where it is and what to do next. The equivalent of a full body workup in CT scan within a simple blood draw. Darya shared a bit of how this was possible, due to all the epigenomic data we extract from a single test. To put it into perspective, we generate 10,000 to 100,000x more informative data per Guardant Reveal smart liquid biopsy test than a tissue-informed MRD test. And so when we say conquer cancer with data, we really do mean it. And in the coming years, that extraordinary difference in data will be obvious to every clinician that orders our test. And so very soon, our smart liquid biopsy platform will make that ambitious vision I just shared a reality. Thank you.

Please welcome the Chief Commercial Officer of Guardant Health, Chris to the stage.

Good morning, everybody. So I'm very excited to be able to talk about our commercial efforts. This morning, you've heard about the amazing advances we've made from a technology side, from data generation. And our remit is to be able to have equally world-class commercial capabilities and customer experience. And so when you look at the entire portfolio and how we interact with customers, that happens across a whole host of different tactics and channels and team members, across different products, different parts of the patient's journey. And we look at that collectively as Guardant Complete. And you saw this mentioned in a few of the videos earlier today. And what I'm going to talk about are a few of the pillars of Garden Complete. Of course, it's predicated on amazing products. But behind those products is world-class operations, helping bring them quickly to patients, quickly to providers. Of course, we have white glove wraparound service with a number of field teams and different groups across the organization spend a moment about that. And then, of course, ensuring that our technology, that our tests are accessible across all the different payer groups so that at the end of the day, patients can get the information they need to optimize their care. And so this is an exciting opportunity. I've been in biotech for a little over 20 years. I've had the good fortune to work on a number of blockbuster therapeutics. And none of them have the potential, even collectively, to impact patients to the same degree that Guardant does with this portfolio. And this is 700,000 patients annually. And in addition to helping so many people, we are also in a unique position to be able to transform the organization. Because if we're successful, we'll be able to reach into what we believe is an addressable market of around $10 billion. The good news is, we have a really strong foothold in the major tumor types right now. And so this is giving you a look at what our Guardant360 adoption is across non-small cell lung, breast and CRC. In liquid biopsy across all solid tumor types, Guardant maintains about 50% share in the liquid biopsy market. And so we're entering this new phase from a position of strength and on a really solid foundation. However, there's still significant opportunity to grow. There's also a number of market tailwinds that all play into the Guardant Complete portfolio. The first, as we've mentioned, is the increased utilization of both liquid and tissue CGP to inform treatment decisions. The next is the entire universe of great companies that are working to identify new use cases, new targets and expand the utility of CGP, and then as we talked about, we're seeing physicians increasingly utilize our tests in earlier lines of therapy, to get baseline genotyping and to have that information earlier than historically we've been seeing it used. So the first aspect of Guardant Complete is obviously the products. And we're blessed with a number of best-in-class, first-in-class innovative technologies across the portfolio. And so if you think about that last slide and what are the 3 big drivers of market expansion, the first liquid and tissue, check. The second, the ability to detect emerging markers or extend the use cases of current markers, check. And then the third, moving to earlier lines of therapy, as we've talked about the application, the ability of Guardant Test to detect the appropriate genomics in earlier-stage disease, check. And so when we talk about the desire to use both liquid and tissue, you saw some of that referred to in the video. Craig talked about the publication, which I'll mention in a minute. We see that also in real-world data. And so we track this. And if you look over the last few years, the adoption of both liquid and tissue and the preference for both liquid and tissue genotyping, prior to initiating therapy, is being -- is going up dramatically. And every data point that we see that comes out, whether it's the JCO publication or other real-world data, continues to reinforce this premise. But what's especially relevant to Guardant is the fact that doctors are overwhelmingly telling us, not only do we want liquid and tissue, but we want liquid and tissue done by 1 lab. We want to go to 1 preferred partner. And so as a result of this portfolio and as a result of our ability to deliver what the market wants, we're now to the point where we've helped assist over 0.5 million cancer decisions to date. But the products themselves are just the beginning. What really makes Guardant special is our ability to operationalize and deliver this information consistently and quickly. And so if you look at Guardant360 CDx for example, the median turnaround time is a little bit over 5 days. This is critically important to providers. If you think about a patient's experience or how a practice operates, typically, you have clinics on certain days of the week, let's say, Monday. So on Monday, a patient comes into the office, has a conversation about their cancer and the doctor recommends CGP. They schedule the follow-up for the next week on Monday. It's critical that these results are in hand, so that the patient knows what treatment they're going to go on, and the doctor is unable to initiate that as quickly as possible. If the information isn't there on time, one of 2 things happens. Either number one, you completely disrupt the office operations. They have to reschedule an appointment, hassle factor goes up significantly. Or two, even worse, the patient is initiated on therapy, which may not be optimal without the insights of genotyping. We know this is important to doctors. They tell us repeatedly, the majority of which that they are highly motivated on selecting a CGP partner, based on the speed at which those results can be delivered. And since the entire time I've been at the organization, this is an area that Guardant rates at -- meaningfully rates that # 1. And the reason that quality of information and speed matters is because this really does change lives. When I talked about our ability to impact people more than any individual therapy I've ever worked on, this is the reason. And as Craig mentioned, this is the most recent data that just came out in JCO, but there's a number of other studies that all reinforce the same benefits, quality of insights and the speed at which they're delivered, that's the secret sauce to delivering results like this in patients. So we've got great products. We've got amazing operations behind them. We also have a world-class commercial team. And so here, you can see around the top of the chart, all the different groups that we have that are deployed to help patients, to help providers be able to navigate this complex space, figure out how to use the products, how to help interpret the results, how to get access to them. But it's a lot of different groups. And so we've done 2 things to try to really streamline the customer experience. The first is, these teams are geographically assigned into pods, if you will, so that both the teams internally have significant increase in efficiency because they all know the accounts, they all know what one another are doing. And two, from a customer point of view, when they pick up the phone, if they have an issue, if they have a question, they know who's going to answer on the other end from Guardant. And the second thing we've done, is we've unified the platforms, whether it's CRM or other data sets across all these groups. So everyone at Guardant has seen the same information in real time, so that when they're engaging with customers across some of the different channels, they're all operating with the most up-to-date information possible. And that, in part, drives some of the stats that you see on the bottom. Every quarter, we ask providers what they think of us, what they think of other teams, what's their experience with different organizations that they interact with. And every single time, the Guardant field team is rated #1. The collective experience working with Guardant in terms of the support that we provide to our customers is rated #1. And that, in turn, gets us access. We have the highest share of voice, the greatest ability to get into offices, whether that's face-to-face and live meetings, or even in those instances where people still prefer to meet virtually. Another thing we're doing to streamline the customer experience is to meet customers where they are at and where they are increasingly at is within their system's electronic medical records platform. So we're currently in the process of integrating with the 3 largest EMR systems in the oncology space. These 3 groups represent approximately 2/3 of the business. The great thing about this is the electronic ordering process allows for significant efficiencies to be gained. It's easier for customers. It also dramatically reduces some of the burdens and hassles, errors that can be made when you're doing things manually. And it provides both the order and results within their health record system. And by the end of this year, we expect to be fully integrated and live in more than 400 of our accounts. All right. I'm moving on to coverage. You may have seen this year that we've had a number of significant commercial payer wins against our core business, Guardant360 CDx, Guardant360. Collectively, our core business now is covered by over 300 -- or has coverage for over 300 million lives. We're also seeing rapid coverage extended to TissueNext. And this is something that we continue to focus on for the rest of the portfolio, with confidence that we'll be able to bring our products to more patients in the future. The other thing we're doing to help ensure access is at the state level, and Guardant has helped to champion and drive a number of initiatives that have led to biomarker testing at the state level. To date, there have been 12 states that have enacted biomarker coverage laws. And you can see that there are a number of other states, including California, that are in progress that we're optimistic are going to follow soon. And the benefit of this is that any of these -- or the majority of this legislation impacts, not just the treatment selection business, but also MRD. And so the benefits here, we can amortize across the entirety of the portfolio. So switching gears a little bit to the MRD space. This is also a huge opportunity to impact patients. We talked earlier about potentially 15 million people that could benefit from understanding the current status of their cancer. That represents just over $20 billion market opportunity. And this market is in its absolute earliest stages across everyone in the space, we believe it's less than 3% adopted at this point. And so all that great infrastructure that it's taken the organization 10 years to build on the back of treatment of therapy selection. The field teams, the databases, the EMR systems, the digital ordering, the access and reimbursement, biomarkers legislation, all of that we can take and turn on and apply to the MRD business. Our reach into over 12,000 oncologists and our world-class sales team can be shared and deployed across the entirety of this portfolio. So now that you get a sense of what Guardant Complete is, and you get a sense of how we're up-leveling our capabilities, this also changes the way that we're able to engage with a number of our customers. And so I'm going to talk a little bit about what we're doing with key accounts, and then I'll get in a little bit more to biopharma and how we're expanding our global footprint. Before I do that, speaking on key accounts. So historically, all the growth you've seen at Guardant, everything that we've done has been very grassroots-driven. It's been traditional sales and marketing, knocking on doors at the HCP level explaining Guardant's products and value proposition to customers. We're now investing in key account teams that are going top down. They're engaging with large networks. They're engaging with health care systems, and what we're finding is those systems want to engage with us, for the reasons that I talked about before. We can be the one-stop shop that they prefer. We can provide all the insights for today and for where they see the market going. And we're increasingly integrated into the systems that they have. And so we're very excited about the opportunity to untap from a top-down approach, the partnerships and expand that within a number of major key accounts across the country. So now focusing in a second on biopharma. As mentioned before, to date, over 160 partnerships or partnerships with different organizations. Right now, we have 19 of the top 20 pharmaceutical partners we're working with, and that's across a number of different collaborations, many inclusive of CDx opportunities. And one comment on the CDx opportunities. Craig talked a little bit about ESR1, which was a recent CDx approval that we saw. In that case, the manufacturer asked Guardant to assist with some of the promotion driving awareness of this new marker. The collective efforts, in this case, we're able to more than double from Guardant, the number of breast tests that we saw. And so that's a proof point of when one, we bring novel technology to the market. But then you support that with robust sales and marketing effort, we can really move the needle quickly. And our biopharma partners are increasingly seeing that. And so we're increasingly changing the conversations from just getting access to our tests to how do they partner with Guardant and tap into the totality of what we can do. And then finally, taking a look at how Guardant is expanding globally. A lot of the work that I just talked about was rooted in our efforts in the United States. At this point, we've now expanded into a number of other geographies. We currently have labs, either operated or lab partnerships in place, in the United States, in Spain at Vall d'Hebron, U.K. at the Royal Marsden, in China, in Japan. And if you look at our commercial footprint worldwide, it's just under 400 people. Two countries I'd like to deep dive into really quickly. We're very excited about the potential for Guardant in our EMEA region. First, focusing on Japan, number of new incidents. This is a country where, again, Guardant is leading the way with our recent approval, the first of its kind in the country, getting reimbursement. We view this as a significantly untapped market and the commercial team there is well-positioned to take advantage of this new opportunity. In China, also, obviously, a really large untapped market. Here, through our partnership with Adicon, we've seen the biopharma opportunities, a number of pharma manufacturers are increasingly interested in this region, a number are based in the region. And so our partnership here has started to open the door and tap into or align with the interest of a lot of our partners. So we're really excited about some of the progress that's being made outside of the United States. So I'll leave you with anything. It's that Guardant has the best, not just of the products. And you can see, we have the #1 viewed products. We have the #1 market. We have the #1 field team. We have the #1 share of voice. So when we talk about the ability to turn these great products into commercial reality, we are very confident that we're well-positioned today to continue to drive this into the future. Thank you very much. That will conclude my section. At this point, I'd like to invite some of the speakers from this morning, back up to stage, and we can address any questions that you might have on the first half of today's program.

Yes. And we've got a couple of folks walking around with microphones. So we have -- there's one here in the front row, I can already see, all right, lots of hands are going on.

So great presentations, and thanks for the insights on epigenomics and smart liquid biopsy. But Helmy, maybe I'll start with you. Given where the field is today for CGP and now for MRD, I appreciate it's still very much early days. But what do you -- how does this translate to adoption by oncologists? How -- what can you do differently this time in terms of generation of that data, the speed of generation of that data into publication, so the adoption rate maybe inflects faster, versus what we have seen with MRD over the last 3 years, because I think you did that successfully with G360, has been a decade to 425 publications now. But how do we accelerate that in this market, which is now looks at a different sort of benchmark and time frame versus technology only?

You're saying on the MRD side or the smart liquid biopsy side?

On the MRD side.

Yes. I think it starts and frankly ends with a sample acquisition. Getting those really precious cohort of samples that have years of follow-up. And that's one thing we couldn't have done 10 years ago is the scale of partnerships and relationships we have with key opinion leaders around the world, has allowed us to accrue now over 100,000 samples across late-stage and early-stage disease. That -- and these aren't just random samples. These are sort of critical cohorts that we need to establish reimbursement. And so we're very confident in terms of the trajectory that we're going to have now, in terms of really establishing reimbursement for -- not just for MRD, but for a lot of the sort of new applications and smart liquid biopsy over the next few years.

Yes. I think it's a great question, and I agree to samples. And we have a network around the world as well now. You saw the commercial footprint, the research footprint is the same, and our reputation connection into all leading academic institutes, and we've got multiple protocols now looking at these cohorts. And not just cohorts for CGP today, but cohorts that are in preparation for the assays that Darya's developed in the future, and there will be biobank inside Guardant, really just to roll the publications out. There is another approach too. We're also looking at exploring, as I shared some real data. So another approach also as we collect the serial follow-up of patients, connecting to that real-world follow-up as they use the Guardant platform within those samples. So we can quickly turn those samples into long outcome data as well very, very quickly. And so we're looking at how to turn that machine up and make it very, very efficient as well from a data generation point of view.

Okay. Just a quick follow-up on reimbursement side. Does the smart liquid biopsy introduction change the reimbursement for MRD that you currently have? Is there any risk to that reimbursement? And do you expect to submit further data set that maybe enhances reimbursement on at least on the Medicare side for Reveal?

I think that's why that COSMOS data I showed is very exciting, is the fact that it establishes a much larger sort of reimbursement indication that encompasses series C surveillance, which is the full sort of indication. Obviously, we have to see if we're successful with that, but it's that data that I think will be critical for establishing with smart liquid biopsy, much wider sort of indication of reimbursement. And as I said, we have breast cohorts, kind of not far behind and even other cohorts as well. So we're going to see that engine really running really quickly on smart over the next few quarters.

Jack Meehan. I was wondering if you can elaborate on the COSMOS CRC data that you showed, the 80% sensitivity, 98% specificity. What's the right comparator versus old reveal data you've had in some of the competing assays? And just confidence this is the level that the Moldex team is looking for, for surveillance approval.

Yes, we think it's best-in-class in terms of where that data sits. It's very apples-to-oranges, depending on cohorts and so on. So it's very hard to take separate studies and compare them. But from what we see, this 99% specificity is kind of interesting. We've seen that some of the cases that we're positive with our test, even though they might be considered sort of false positives, they are actually patients with -- recurrent with lung cancer or like other cancers that have occurred. So we're finding that what we're able to detect with the test, is really a cut above in terms of what other tests are able to provide, because we're able to see the sort of the whole picture in a tumor-agnostic fashion. I would say the other aspect of it is -- you see the sensitivity that we're achieving on the screening side and MRD side. And a lot of that knowledge and know-how has really gone into smart liquid biopsy and from that really improving the performance. So yes, we think it's kind of way above the bar that's required for reimbursement.

Great. And just a follow-up. Sorry to linger on Friday update. The issue with the ctDNA falls positive. Is it possible to explain just fundamentally what's going on here? Something that we've heard is that some patients might have ctDNA, but the immune systems care of it. So maybe the test was right, but the patient didn't have cancer. I was just curious if you could maybe explain a little bit more what was going on there? And then for Darya, just like some of the additions that you're making to the panel. Do you think there's ways to -- are there any indications that you've seen to really finally tune that, where you think it can be differentiated versus in the competition?

Yes. So we've seen with sort of -- there is a phenomenon that happens actually with all tests, including tumor informed tests, where -- in the beginning, there's a little bit of a clearance that happens and there's essentially some tumor DNA that lingers there. And that's why it's important to sort of watch the patient and see that clear out. So that's -- I don't know if there's anything else.

No. I mean, look, why is the DNA clear? That's -- it's a great scientific debate. There is evidence on immune generation to tumor if it's not just clearing the DNA. So you either test too early, it could be residual or it could be just the tumor clearing. Obviously, they establish as false positive, because there is no tumor at the end of the day, right? And so I think this is an area that we're going to also learn more and more about with these MRD assays, in fact. And hopefully, with some of the more expanded assay, tapping to the immune side and, therefore, start to really unravel what's happening in those patients that maybe we can use and transfer to others. So there's a lot of great exploratory hypothesis, but it's evidence in the making at the moment.

Maybe to quickly answer your question about what we can do over time. As we accumulate more data, if you think about sort of multidimensional data that we're acquiring. There are various biological factors that contribute to the background we may be seeing. And so as we started shielding our LDT labs, since then we generated over 10,000 patients worth of profiles of mostly average risk population. And as you can imagine that data is informative to continue to refine biological background that we see, and we think there's a lot to be uncovered learning from that data to continuing down that continuous improvement path on that new technology. So there's definitely more biology to be thought about and tuned into those tests than we have done today.

It's Kyle Mikson from Canaccord Genuity. So on that point, Darya, the multiomic kind of strategy, you guys have used methylation, I think [indiscernible] in the past. But now talking about proteins, exosomes, nets as well. And there's a lot -- if you look in multiomic testing is very important for screening, for example, I feel like as well as these other aspects of testing and you have competitors that are dealing with RNA or other kind of markers. So maybe doing it like how do you review it over time, getting to that sort of the layer -- the third layer of that [indiscernible] you had and why that's important, and what's that for lot the specs maybe to?

Yes. Thank you. So maybe let's take it 1 layer at a time and talk about epigenomics layer. We've relied very heavily on methylation as the stronger signal, that persistent blood is very stable in blood and easy to measure. We've also have fundamental IP related to the pragmentized distributions that we have explored within our products. It's been published, and we believe that methylation has a stronger footprint for assessing tumors with lower fraction in circulation, but that's the domain we can explore with technologies we have. If you think about the outer layer, what has been sort of very difficult in this field is various pre-analytical factors that impact how we can measure that in blood and contrast to methylation, which is a very stable signal. And so lots of noise in the field over the last year or 2 on what that third layer can actually do. Careful methodologies for assessment of these modalities are reviewing various compounding factors that often sort of create signal where it didn't exist. And so we're sifting through that right now with, as I said, powerful biobanks that we've accumulated, to figure out what's real and what's not. And that methodological process will hopefully yield clarity on what's viable in that layer, to fundamentally enhance beyond what we can do with epigenomics. But so far, definitely, the stronger signals we see in terms of reaching deep into the tumor fraction at low level is that layer today.

Okay. And then maybe, Helmy, how do you think about decentralization in MRV and CGP over time? Is that possible to do with NGS? Just [indiscernible] the steps to be there that really [indiscernible] you, because like there are some maybe PCR-based companies that are getting there.

Sure. So like kits and kitting and that kind of thing. So I don't know, I mean, I thought people would stop asking the kit question after a couple of these companies went out of business or share and resolution and so on. I think this -- the process has to be simple for a kit to work. There has to be a platform that has a large menu, that's high throughput and so on, and just -- it's still very difficult, I would say, with NGS-based approaches. I think if you're talking about PCR for MRD, that requires customization and acquires a bespoke panel. If you're thinking about tumor informed. So it's -- I think it's unlikely that decentralization will sort of be a major component of this space, at least for some time to come. And I think a big driver for that, at least on the therapy selection side, is the fact that pharma is spending tens of billions of dollars a year in R&D, continuing to drive the pipeline, drive development of new biomarkers. And so that requires continual renewal of the tests and the assays and lots of investment there. And so we really do think of ourselves as a company that has a sort of tech mindset, where you're thinking about an 18-month product upgrade cycle. You're always coming in. You have to provide the customers and the people we serve something new, new options and so on. And that's going to be the case for us on the MRD side. I think -- you saw some of what I was suggesting we could do with our MRD test, in terms of telling you where the tumor is, what to do next and even additional information that is really going to redefine what it means to do MRD. And so the question is, are you going to be using sort of the PCR-based kind of walkie talkies of the field or using smartphones and so on. And there may be applications for both at some point. But we want to sit in this sort of high-value, high-gross margin, leading edge of the oncology space.

Dan Leonard from Credit Suisse. Two questions on Reveal. First off, on COSMOS, you mentioned 99% specificity at the sample level. Can you tell us what specificity was at the patient level? And then secondly, I just want to make sure I caught all the reimbursement time lines or at least your planned submissions to Medicare. I heard the expanded CRC submission by year-end 2023. But I want to make sure I caught the others if you could just revisit what you communicated?

Yes. I think I'll start with the second question, which is -- we talked about sharing breast and CRC data this year. Obviously, we just shared some of the colon data, and we expect, hopefully, at San Antonio to present some of the breast data. And we think that those data sets, including maybe some other cohorts, we have would make up Medicare submission, and we're hopeful that would happen next year. The gating item there is publications. So we have to get the data published. We're having the COSMOS data. I think manuscript is being prepared as we speak. Hopefully, it will be submitted sometime this year, and we're hoping for a timely process. In those 80,000 samples, I would say, the majority of those are clinical validity cohorts, which can be used for Medicare. And a large number of those samples are being sequenced as we speak over the next few quarters. And so it's just a matter of what the data looks like, obviously, after we get through it and then how fast we can present that data and submitted. This -- the -- in terms of the specificity, at the patient level, it was also very high in the -- very high 90s. I don't have the number off the top of my head, but it's -- like I said, some of that was confounded by -- actually, if you take out most of the patients that had secondary cancers that were detected, specificity is approaching 100% very, very high.

Helmy, when we -- when you were talking with some of the analysts on Friday, post the corporate news, you had mentioned that the PEGASUS trial does not include smart liquid biopsy. You've now got the early COSMOS data and you'll be presenting PEGASUS. Can you just talk to bridging the conversation with clinicians on a smart liquid biopsy data set and then kind of stepping backwards, I guess, with PEGASUS and whether you see there being risk in the conversation on just oncologists, who I think they try to pay good attention, but sometimes you're not up to speed on all the latest details.

Yes, we -- it's a good question in terms of whether the results in PEGASUS and sort of an older version of the technology would translate into something that can be used sort of where the technology is going. And we think it can. I think you really have to look at the design of the study and what it's trying to measure. And in that study, it's a de-escalation study, where it's really -- what's important there is a sensitivity of the assay and having sort of reasonable specificity. And we're very confident like in no way do we feel that the assay was ever sort of kind of not performing well. And in this case, we went from an assay that was performing well, to smart liquid biopsy and one that's performing even better. And so as long as we can show positive results with PEGASUS, we absolutely think that it translates to an even better performing assay with smart liquid biopsy.

Helmy, one sort of big picture question for you, just around the lifetime cost of all the repeat testing, right? How do you think about breakeven for health care systems in terms of qualities, hospitalization, treatment cost savings, et cetera? And what about sort of locking in patients by either sort of demonstrating benefits of staying on the same platform over time, or perhaps a bundled price solution for what you're calling Guardant Complete?

Yes, that's a great question. We think about that a lot in terms of really balancing sort of utilization of the tests with cost and the sort of health economic arguments, and we always want to be at a place where we're net positive, in terms of the information that we're providing, sort of lowering health care enough, costs enough to sort of make up for the expense of our tests in the system. Because there are some companies out there that kind of like an algae bloom kind of charge as much as they can. And hopefully -- and it's -- we've been a company that's been around for 11 years. We're going to be here for another few decades, at least, an iconic company in the diagnostic space. And so we're always -- we always have that long-term mindset of making sure we're doing things that are right for the space, right for patients, right for the whole ecosystem. And so I think that's where the frequency of testing is going to be really important. I think that's still something that's up in the air, in terms of exactly what is the right frequency for each cancer type. And it's a matter of really providing information that changes decision-making. And so that's how we look at it. And I would say that -- the second aspect of it is the sort of ecosystem lock-in, and we think about that quite a bit, which is when you think about companies like sales force or so on that have been able to sort of retain customers really well, one of the stickiest things that around is data. If a customer has a lot of data, sort of locked in with a company, it becomes very hard to sort of move to another player. And that's why you see that everything we have here, there's so much data embedded with every test we run. And so the way our MRD tests are going to work is that when a patient gets a positive result, that's not the end of the journey. Now everyone's springing into action thinking, what do I do for this patient. There's cancer there. We need to treat the patient. We need to come in with some kind of intervention, and if you can press a single button where you may not even have to send another tube of blood, but all of a sudden, you get a Guardant360 result coming back with that information right there, that is just a very different sort of experience that you can have. Or the idea that not only is the Guardant Reveal test positive, but let's say, for a colorectal cancer patient. It's telling the physician it's positive, and it looks like there's some liver metastases. Those patients are often curable. You can actually come back in. And if it's just a single site and the liver to come back in and take that out and cure that patient. And so that's what these tests are going to provide is that sort of added level of really information and actionability. And they're going to really work together in that fashion to sort of make it very compelling for physicians to stay partnered with us.

Got it. That's super helpful. And I actually want to just follow up on that comment you made about data lock in. Outside of these studies that you have reading out COSMOS, PEGASUS, et cetera. Is there anything else you can do to sort of negate first mover advantage here with sort of [indiscernible] being on the market ahead of you? There is this perception, right? But on the other hand, the market is only 3% penetrated, as you pointed out. So is it more sort of focusing on that 97% white space? Or anything else you can do besides waiting for these publications to win sort of mind share?

I think it's -- if we wanted more volume, we could get more volume too, right? It's not -- it's a matter of making sure that we're both focused on the top line and bottom line of our business. We have some pretty ambitious goals as a company in terms of, not only continue to drive therapy selection and MRD, but obviously, as we're going to talk about later today, our screening business, which we think we're in a sort of unparalleled place right now in terms of where we are with that franchise. And so it's really a balance between all of those pieces. And that's why I talked about reimbursement being really that sort of gating item in terms of how we throttle the commercial volume we have. We have an oncology commercial team that is really second to none in terms of the breadth we have, in terms of the number of touch points we have with the space. And so we can turn that on at any time. I would say the other thing, too, is back to the sort of apples-to-apples versus apples-to-orange comments, where what market are we talking about? Are we talking about the sort of kind of very simplistic MRD testing market? Or are we talking about the sort of smart MRD market where you have these additional capabilities that are possible with our platform. And so we think we're redefining that market. We're taking it from people with iPods to people with smartphones that sort of replaced the iPod and basically took it out from existence.

Right. That is going to conclude our first Q&A session. We will take a 10-minute break and reconvene at 10:25. [Break]

Please make your way back to your seat. The program will resume in 3 minutes. Thank you. Please make your way back to your seats. The program will resume momentarily. Thank you. [Presentation]

Please welcome Co-CEO of Guardant Health, AmirAli Talasaz back to the stage.

Welcome back to our second half of this meeting. We are very excited to talk about where we are with screening division. At Guardant, as you know, we are pioneering a new category of cancer screening with this blood-based test. Guardant now is the first and the only company that now with Shield has offerings across continuum of care. Guardant's mission has always been improving patient lives. One of the best ways to offer more time to the patient is to detect these cancers at earlier stages of the disease. When we are looking across 26 cancer types, comprising 87% of all cancers in the United States, the survival rate is just 14% when the disease is getting diagnosed at late stage. However, if you diagnose the patient at the localized or regional stage, the survival goes to 65% to 90%. Now to really down-stage cancer at the population level, we do need a test that can detect these cancers at early stage with good performance, and really generate a favorable and good patient experience. So those tests could get done. And we believe blood test has this potential. When you look at existing screening modalities, we have learned a bunch of lessons about the reality of successful factors that goes behind successful screening brands. First, obviously, the screening test needs to have good technology performance and can detect early-stage disease with good probability, like having a blood test that can detect less than 20% of early-stage disease is not useful. Second, the test needs to be accessible for all. As a result, there should be meaningful and existing pathways for broad reimbursement. Third, pleasant customer experience. If the test does not get done, you are not going to impact lives. And the test needs to get done longitudinally over the lifetime of these average risk patients. And finally, a positive unit economics in order for the test to be scaled to the population level. Now when we are looking at standard of care for many cancer types, there is no screening option. And for the ones that have some screening options in a bunch of them, the modalities are not patient preferred. And the adherence rate is pretty low. And mainly the adherence is low, because the experience from patient's side is unpleasant. We believe Shield has this potential to detect cancers with high performance in early stage, have accessibility pathways, generate pleasant patient experience in getting the test done through a routine and seamless test, and also, it can be a scalable business with a favorable unit economics. As an example, let's just look at Shield in the field of CRC indication. We strategically started with colorectal cancer as our first indication. When we are looking at the current landscape of CRC screening, there are 50 million people who remain unscreened. Although there are modalities with very high performance who have been around for many years. And mainly, again, it's related to the poor patient experience that generated pretty low longitudinal adherence to completing the test. We showed Shield in terms of technology has high performance in detecting it early stage. We know that the pathways of reimbursement is out there for Shield to be accessible to all, because of Medicare beneficiary can get access to it post-FDA approval because of national coverage determination by CMS, because of the private pay access that exists post guideline inclusions by American Cancer Society and U.S. Preventative Services task work. And finally, Shield could have favorable unit economics because of the faster ramp in the gross margin that we are going to talk about later throughout this session, which would make the business scalable. Let's go deeper into CRC indication. Despite having multiple screening options, still more than 50,000 lives are lost every year to CRC. And as we heard, 76% of lives lost are individuals who are not up to date with their cancer screening. This is the real unmet need of having a test that at the end gets done. So let's go around the circle, and we start with the technology side. We had a session on the technology. We are not going to go deep into this differentiated epigenomic technology, smart liquid biopsy that we have. But at a high level, we are just looking at thousands of regions with very high sensitivity and specifically at low cost that generates good performance for our blood test. But let's look at our clinical readout at high level. We ran ECLIPSE trial, a registration on grade 20,000 patients, a study called ECLIPSE that generated the first of a kind data in terms of having high efficacy for the first blood test that was shown in a very diverse study of over 200 enrolling site of over 20,000 patients enrolled. This generates at least 1-year time advantage for us, relative to any other competitors in the field. At high level, in EquipShield demonstrated 83% in detecting CRC at 90% specificity, which we believe exceeds the requirements for FDA approval and Medicare coverage, which, as you know, are the 2 critical milestones and headed those for a test to be -- for a test to become successful and accessible. And now with this data, we set a new bar for other computing blood tests, in terms of their data readout. Importantly, the performance that we just talked about is in range with other guideline recommended CRC screening test, where the CRC performance ranges between 74% to 92% in terms of sensitivity with specificity of 87% to 96%. We believe the data that we've seen so far for this first generation of Shield is meeting the bars for building a very successful -- commercially successful brand. Moving to reimbursement and reimbursement pathways. And the reason that we started with CRC as our lead and first indication. In order to really change the outcomes for better, the screening tests need to be run at population level, which means we need to have equitable broad access for testing for all patients. Almost obviously, a testing would not be durable and scalable. And for colorectal cancers, there are established and clear pathways to generate this accessibility for over 120 million people at age 45 and above. And once we pave this access, and 120 million people get access to Shield because of CRC screening, then we can build on top of CRC indication. And when we are running the same sample, for Shield or CRC screening, look at other cancer types, and that would be our accessibility pathway for Shield. There is no other established and easy access pathways for other multi-cancer based test unless they get FDA approval for CRC indication. Going into a little bit more details about this. Maybe very familiar that there is already a national coverage determination or NCD by CMS that generates access and reimbursement pathway for Medicare beneficiary with $0 co-pay. For private plan beneficiaries, several states have state-level mandates for coverage for colorectal cancer screening as long as that colorectal cancer screening is included in American Cancer Society guidelines or ACS guidelines as a recommendation. And at the end, once the test is included in USPSTF guidelines, all private payers are mandated to give beneficiary access to that test with $0 co-pay. Talking about USPSTF, let's talk about how do they come up with their recommendation. The recommendation by the task force are primarily based on the clinical evidence, coming from research studies and real-world data. And after that, some modeling exercises to fill the gaps in those real-world and research studies to look at the harms and benefits of different screening methodologies. What you're seeing in this slide is a modeling results that recently we presented. Modeling parameters are shown on the right. We built this discrete event simulation model, integrating real-world adherence for different screening modalities. And we look at, okay, what's going to happen in terms of the life year gains, meaning benefits versus harms or additional colonoscopies that's going to get caused by running our test as the screening modality. So what you see here is favorable actually position for Shield, in terms of life year gains relative to other modalities that Shield is in range, if not favorable, relative to colonoscopies and stool-based test. We are also, for the first time now, looking at our -- talking about our colorectal cancer debt aversion, a number of the debts which are getting reduced as a result of that screening test coming from the same modeling exercise. And what you're seeing let's say, in 1,000 individuals that are getting screened with Shield throughout their lifetime, there would be about 15 CRC debt averted, which is on par with colonoscopy and much better than stool-based testing. The good thing of Shield relative to colonoscopy and the harm factor is 60% of colonoscopies would not be necessary anymore. And this is the value of longitudinal adherence to completing a blood test, versus doing a test that a good fraction of the patients would not complete at the end. This gives us actually the confidence that Shield will detect nearly all CRCs at curable stage, and we will really offer favorable outcome to patients. And we are very hopeful that Shield would get added to the guidelines as a new option for physicians and patients to take this optional blood test in conjunction with other modalities, which exist in the field. Talking about another parameter of accessibility, since NCD requires FDA approval. We have submitted our premarket approval application for Shield earlier this year, and we are making steady progress with agency. We are very pleased with the collaborative and collegial interactions that we have with the agency and continue to expect approval and launch in 2024. Post-FDA approval, effectively, all patients at the age of 65 or above would get access to Shield with $0 co-pay. We talked about American Cancer Society guidelines on some state-level mandates and access pathways as a result of it. We expect ACS guideline inclusion to be a few quarters after FDA approval, and continue to expect USPSTF guideline inclusion sometime in 2026. This would drive private payer reimbursement for commercial plan beneficiaries to get access to tests with $0 co-pay at that time by end of 2026. So we talked about the performance. We talked about accessibility. The third important factor for a successful brand is if the patient at the end will complete that test. The best test is the high-performing test that gets done. People are looking and asking for more convenient options for cancer screening. When we just look at the whole market, patient aged -- people aged 45 and above -- 45 to 85. There are 137 million people, which 120 million of them are -- have average risk for colorectal cancer. The latest estimate continued to show that 70 million out of 120 million people are getting screened, and 50 million people still remain unscreened, after all these years of having all these modalities in the marketplace. Majority of these 70 million people, which are getting screened, are through colonoscopy and about 15 million people are getting screened through stool-based tests. Now what are the challenges with current modalities for CRC screening? And maybe that would be just a good add exercise for you in audience to think -- do you prefer a colonoscopy? Do you prefer to get a stool test done? Or do you prefer to get the blood test done? And what's the reason for it? When we are looking at it, there are multiple challenges in the field of CRC screening for colonoscopies in terms of long wait time and staffing issues and resource -- lack of resource associated with it unpleasant experience to colonoscopies, perhaps or even sample collection of stools, and the time consuming and the commitment that really requires on the consumer side to go through all those processes. And for blood, it's just a routine simple blood test. Based on the results from a patient survey study about 2,000 people that we've done, we found that even in compliant patients who have done cancer screening before, 7 out of 10 people who have done stool-based colorectal cancer screening, they do not want to do it again if they get the option of blood-based testing. When we just focus on unscreened patient population, the favorability of blood tests relative to stool test is 5:1. While we are just looking at the real world LDT experience that we have with our Shield over the last 12 months in the marketplace, we continue to see strong adherence rate, meaning completion rate by patient of more than 90% in completing Shield at the scale that we have right now. A potential bottleneck that sometimes comes up to get the screening done in unscreened patient population is, would unscreened patient population or patients in general, see their doctors. And this is interesting when we are looking at the National Health Interview Surveys or NHIS, which conducts an annual surveys, 27 people actually go through it. These are the findings, that about 90% of people age 50 and above have seen their doctor during the last 12 months. 87%, 50 to 64 and higher in 65 and above. And in fact, in the survey that we've done in parts like 2,000 patients, we found 85% of the patients have done some blood work during the last 12 months. This just shows a sign of what all of us we believe in that how seamless and routine is getting blood test -- is to get blood testing done. In comparison, for stool-based test, just 10% of eligible patients are getting stool testing done per year. And finally, positive unit economics at scale. In order to really have a scalable business, you need to have favorable unit economics in order to extend the outcome benefit to all eligible patients. So let's talk about what's going to happen to Shield post FDA approval. We expect post-FDA approval for Shield to get qualified as advanced diagnostic laboratory test or ADLT, under Medicare clinical laboratory fee schedule. Why is it important? Because once the test has the ADLT status, there would be favorable Medicare pricing pathway which would accelerate Shield's ASP to about $500 in just about 1 year post FDA approval. Just powered by that ADLT pricing for Medicare and Medicare Advantage beneficiaries. On the other side of the table, on the clock side, based on the technology and automated operation that we have at Guardant. At scale, we believe shield COGS would go down to about $200 per test. At scale means once we are getting about 1 million tests and beyond. So that's favorable kind of gross margin pathway. Let's talk about on the commercial side. Why commercialization of Shield could potentially be more efficient, than let's say, stool-based commercialization. Now let's just do a simple exercise. I assume physicians order 100 Cologuard tests and order 100 Shield tests. When the sales and marketing engines sells and gets these 100 orders for stool, just 65 stool samples would get delivered to lab. One out of 3 kids would never come to the lab because of patient adherence. That would result into 65 potential billable cases. For Shield, with a favorable adherence rate of 90%, 90 of those tests would become potentially billable. That would just translate into 40% increase in the efficiency of the S&M engine when they sell tests. As we prepare to launch Shield in 2024 as an FDA approved test, we're going through a very targeted approach to optimize -- to further optimize the efficiency of our commercial team. We will have deeper presence in regions with higher concentration of Medicare beneficiaries. We are going to have higher coverage in states with favorable coverage mandates post-ACS guidelines. And also, we would mainly target early adopters and heavy users of noninvasive stool-based CRC screening tests and accounts which have easier access to blood-based testing done, basically just in-office phlebotomy. We believe the efficiency of commercialization would go even higher and this would help to have more favorable unit economics, enabled by higher efficiency commercialization, as I mentioned earlier, higher efficiency and more favorable gross profit road map. I would like to just take a moment and talk about our milestone gated investments in the commercialization of Shield in the PCP market and the channel expansion. We are planning to have about 100 to 150 field force people, contingent on receiving FDA approval, and then gated by the commercial success in terms of volume and revenue generation. As we get closer to USPSTF guideline inclusion, we would expand our field team to about 300 people. We expect to be included in USPSTF guidelines in 2026. And after guideline inclusion, we would further expand the commercial team. And at scale, we are going to have about 700 FTEs in the field. As we scale, we will continue to gather data, biobank, clinical insights. We are a company that believes in conquering cancer with data, and data would shed light on how we can even improve our products and technology stack over time. This is what we've done with Guardant360 over last many years. We started by launching a best-in-class liquid biopsy, but Guardant360 today is very different and Guardant360 of 10 years ago through many rounds of continuous improvement. And we are taking the same approach with Shield. We are confident the performance that I talked about earlier for the first generation of Shield is meeting the bars for approval, reimbursement and commercial success. Also, we believe this would be just the beginning for what Shield can offer to patients and physicians. So let's talk about Shield V2, a new generational shield that we have. Since we froze our device for PMA studies for FDA, we -- that was more than a year ago, a year ago, we continue to generate data, better insight, and make progress in having a better version of Shield V2. Based on the insights we got around early stage CRC, especially around the malignant polyp Stage 1s that we are missing in ECLIPSE. Shield V2 is the same assay, same chemistry, same workflow, same technology, just an upgraded algorithm. Previously, I talked about Shield V2 having higher improved analytical sensitivity, meaning that it can detect tumors even when the tumor levels are about 2x lower in samples. Sometimes, analytical sensitivity translate to clinical improvements and sometimes it does not. I'm excited to actually see and share the performance of this test in a new prospective clinical sample cohort that came from colonoscopy screen study. And this was actually what happened. This is a study of 45 CRCs, the performance of V1 in this cohort prospectively collected in U.S. colonoscopy screen CRCs. The performance of V1 was 84%, with specificity of 91%. As a reminder, the ECLIPSE readout for V1 was 83% at 90%. And the performance of V2 in the same cohort was sensitivity of 91% with specificity of 91%. The early stage performance, Stage 1, 2, with V1, was 76%, for ECLIPSE, we saw 72%. And with V2 in this cohort, we saw 88%. And the sensitivity in detecting advanced adenoma was similar between these 2 versions of the assay. We are excited and pleased with this clinical validation results, but it's important to note, this is not a regulatory grade data that we can submit to FDA. But definitely, it's a very relevant clinical validation data that continues to give us confidence that V2 really can detect CRCs, especially at early stage with better performance. I forgot to mention like Stage 3, 4 performance was 100% in both versions. And this is just a performance boost that we are talking about when you capture the data and you listen to the data and biology and figure out how to improve the performances. And the same data, not only would over time, improve the performances in CRC, I'm confident it would improve the performance in other indications over time. Now let's talk about actually, okay, what does this mean in terms of potential label updates and upgrades for the PMA package that we have with FDA? We are focused to take the Shield V1 to the finish line in collaboration with the agency. As I mentioned, we are pleased with the progress, and we are still in active review process. Pending a successful regulatory-grade data for V2, we are planning to submit a supplemental PMA for Shield, and we expect potential approval for V2 in 2025. So, Shield CRC was not our mission when we started working on Shield. We wanted always to have a blood test that can detect cancer at early stages for many different cancers when the clinical outcome benefit could get offered. CRC was our leading indication, as we talked about, for accessibility and FDA approval pathway. And over time, we are going to expand indications on that approved and accessible tests. Our second indication, strategic indication, is lung, but we are not going to add cancer types one by one. We are also working on adding a whole panel of MCED cancers into the same assay in Shield. Same tests, adding lung -- adding large MCED panel, doesn't matter, same assay, same Shield, but with some kind of simple algorithm upgrades. This was our founding vision and what we are focused on delivering in the future. I would like to invite our CMO, Dr. Craig Eagle, back to give you a quick update on where we are in some of our studies for other cancer types. Craig?

Thanks, AmirAli. So really when we start to think about reinventing screening for lung cancer, again the same sort of logic applies as in colon cancer, with a simpler test that has -- creates more accessibility to patients. And so just to remind everybody that lung cancer is probably one of the leading causes of cancer deaths. There's over 150,000 lung cancer deaths in the U.S. And 86% of individuals who are at high risk of lung cancer are unscreened. These are people that have a very long and heavy history of smoking. And that equates to about 12 million individuals unscreened. So really, where does that lead us? That leads us to the Shield lung study. This is a study that we're enrolling currently. USPSTF defined patients are included. So it's on track to meet the criteria. And we currently have over 7,000 patients, and we're on track with enrollment and excited to see what this study brings. Just to remind you a bit of the study design. This is a study design that basically enrolls patients, collects the blood. They have a low-dose CAT scan, which is currently USPSTF approved screening modality. And then we'll have a readout, we're hoping to be expected sometime in 2026. As AmirAli mentioned, it doesn't stop there. We're moving obviously into multi-cancer early detection. And our aim over the course of 2023 into 2024 is to kick off a prospective interventional multi-cancer study that's looking at about 10,000 people. And that study, we're aiming at this stage, thinking through the proposals and the protocols, but the thought process is about 10,000 individuals with a baseline blood test, but then triage as on the diagram where, if they're positive, they go on and have further diagnostic workup looking for the cancer, and if they're negative, they're followed for 2 years. If the diagnostic workup can't find cancer on the positive patients, they will continue to be followed up also for a 2-year period. And again, this is something that we're rapidly moving towards with a multi-cancer early detection device. Thank you.

Thank you, Craig. Let's summarize. We are blazing a trail for Shield to be the first FDA-approved reimbursed multi-cancer screening test. And in these slides, we are analyzing our road map for CRC lung and just the MCED panel that we talked about that we are starting the interventional study later next year. In conclusion, I believe we are in a defining moment in the history of cancer care. What we are working on is once in a lifetime opportunity to reinvent cancer screening and save many millions of lives. I am proud of dedicated, passionate, resilient team in this company. And this thing would not settle till we get the mission accomplished. That concludes this session, this section of the talk. We have great panel conversation about epigenomics. Maybe we set the stage back up here, maybe just give it a minute. And the moderator of our panel is our own Dr. Justin Odegaard, our Vice President of Product. I would invite Justin to come on the stage until we are setting up the stage for the KOLs. Justin, please.

All right. So certainly, this morning, I think you've heard a really strong theme of epigenomics sort of as the future of oncology diagnostics, both for patients with cancer as well as for patients that don't yet have cancer and the cancer screening. And you've heard Guardant's reasons for that, our perspective on it and our rationale for it. And you've seen the investments we're planning on making to make sure this future happens and we can capitalize on it. But for the next 45 minutes, we kind of wanted to continue in that theme, but from a different angle, and bring up a couple of experts, actually 4 of them. They are experts in epigenomics from academia, to give you a [ non-Guardant ] sort of perspective. What is the value here? What's the information that we can glean? What are the possible applications for that? And while they all sort of share a common theme of expertise, of course, in the field, they also come at it from very different angles. So first, we have Dr. Will Greenleaf, who's coming in from Stanford, very much an expert on the basic science of epigenomics, sort of the mechanisms, what are the fundamental biology that epigenomics underpin. And then on sort of the opposite end of the application spectrum, we have Dr. Jake Berchuck coming down from Dana-Farber, who really takes these concepts of epigenomics and uses them in the clinic in its translational oncology clinic to actually improve the care of advanced cancer patients. We also have Dr. Simon Heeke from MD Anderson, who uses the same epigenomic approaches and insights to improve diagnostics, obviously, something near and dear to our own hearts. And lastly, we have Dr. Yuval Dor, who is sort of well known in the field and very -- has done a lot of foundational work, looking at the blood that we have running around our bodies, all the epigenomics that it's coming from, and deconvoluting that to see where the cfDNA is coming from in circulation and really trying to see -- use that sort of tool to define sort of all sorts of different human diseases outside of cancer as well as wellness as a whole. So with that, I think I want to -- help me invite our panelists on the stage. And please come up, take your seats. All right. So -- somebody failed the test. So certainly, this is a very brief introduction, and I wouldn't want to steal your thunder. So maybe, Will, if you can give us a few minutes about yourself, your background and your interest in epigenomics that led us here today.

Yes. I'm Will. I'm a professor in the genetics department at Stanford. And I guess that comes from sort of a physicsy, biophysicsy background. And so I'm really fascinated by the physical genome, how the genome itself sort of allows the creation of an amazing human body. That sort of mystery, and that's the sort of thing that my lab investigates: Gene regulation and how cells remember who they are.

Hi, everyone. My name is Jake Berchuck. I'm a physician scientist at Dana-Farber and Harvard Med School. I consider myself sort of equally a clinician, Board-certified practicing medical oncologists. I specialize in caring for men with prostate cancer as well as people with bladder and testicular cancer. And on the other -- with my remaining time, I'm in the lab doing translational lab-based research, thinking about really how can we deploy these new epigenetic cell-free DNA assays to really address unmet clinical needs that I see in my clinical practice.

And in line with this, I'm Simon Heeke from MD Anderson, which is also a public hospital. So the idea is really to get like cancer care. And I'm working primarily in lung cancer, and the idea is really to develop novel biomarkers, but with the aim to improve clinical investigation, clinical care, and really bring them to the patient to really get the impact there. I'm also the Young Committee Chair of the International Society of Liquid Biopsy. So really dear to get liquid biopsies out there to the people and really that they help in the end improve.

I'm Yuval Dor. I'm professor of biology at the Hebrew University of Jerusalem, Israel. I trained at Harvard, but -- at my own lab there, I'm PhD Molecular Biologist. And main themes of my lab are trying to understand diseases of the pancreas, diabetes and pancreatic cancer. And over the last 15 years, we've dedicated much of our time to epigenomics and in the context of liquid biopsies. We pioneered this approach of detecting the tissue origins of cell-free DNA molecules according to their methylation patterns, which we'll elaborate later on.

Excellent. Well, again, welcome, and thanks for spending some time with us. So obviously, the audience has heard from Guardant at great length about epigenomics this morning, but you all spent your careers as being the experts in this. So maybe, Will, if you want to start us off, just give us the basics. What is epigenomics? Like what can we look at it with? Why do we care?

Yes. I think it's a great question. The way I think about the epigenome is it's sort of the software layer of the genome. It's sort of how cells remember who they are and how they execute their function. Maybe you can harken back to when the human genome was sequenced around, whatever, 2001 or so, everyone said, we did it. We figured out the mystery of human life. It turns out it's really complicated. That was just the beginning of actually unpacking that sort of mystery. And you can think about it, that it's complicated, because obviously, there's hundreds or thousands of different cell types in your body, and they all use different parts of the genome. So in certain sense, the genome is a very poorly organized compendium of different instruction manuals with different pages from a helicopter and fighter jet and Bugatti, all stapled together with no real instructions about exactly how to do everything. So that keeps us academics busy trying to understand exactly how cells remember, and figure out how to use this instruction manual to become who they are. And I think to really understand the problem that cells have, you have to think about the genome as a physical object. It's actually 2 billionths of a meter wide, but in a single cell, if I stretched out that DNA, it would be 2 meters call. And it would be compacted and sequestered into a 5-micron nucleus. Am I -- sorry? Yes. So that's a spectacular problem that the cell has to deal with every day. It's as if I had a telephone cord, you guys remember what a telephone cord is, right? And it was stretched from the West Coast of the United States to East Coast of the United States, and I packed it into sort of a normal 2-story house. That's what the cell has to deal with every day. So -- and of course, if I'm a blood cell, I have to express and use different parts of those instructions in a very different way than if I'm a fat cell. So how can I do that? How can I manage this nightmare of organization? One of the big ways that cells do that is marking the parts of the genome that they need to use with this sort of epigenetic mark methylation. It's like the fifth base of ACTG. Remember that? There's also C Prime, effectively. This fifth base that tells the cell this is part of the genome that I don't really need to worry about. And honestly, that's on the order of lower traction of the genome that any cell specifically needs to use or might not need to use. So it's sort of spray-paints the parts of this telephone cord that it doesn't need anymore. And then that helps it sort of understand what you're doing. And of course, in cell-free DNA, what you got to do is look at the fragments and sort of read parts of that marking, right, that software program and understand that, that fragment came from a cell that needed that portion of the genome or not. And so high level, the epigenome is effectively how cells operationalize the underlying hardware of the genome and bring about their cell state and their function that they need to do to live. So that was long-winded, but that's my [indiscernible] trying to convert you. I'm used to speaking to graduate students and convincing them this is an exciting thing. You guys are all lost causes, unfortunately, but that's fine.

So I think we very much obviously share the excitement over like the functional aspect. You can actually access phenotype, now I'm not -- instead of just the genotype instruction. And there's a lot of tremendous potential there, but sometimes that can get really abstract. And I think, Jake, one of the things when I think of what you do on a daily basis is to take that abstraction and make it completely concrete for Ms. Jones in front of you in the clinic, or actually, sorry, Mr. Jones...

I was about to say Mr. Jones. So yes, I think, when I think about diagnostics in general, as oncologists, we're only as good at treating a tumor as we understand what really drives it, what makes it tick, so that we can leverage that therapeutic vulnerability, understanding how we can exploit a weakness of an individual tumor to treat it, elicit response in the individual patient, and ideally help them live longer. And so historically, that was done through tumor histology. What I mean by that is taking a biopsy of a tumor specimen, looking at it under the microscope and deciding is that an adenocarcinoma, a tumor of gland-forming cells, is that a squamous cell tumor, a small cell tumor. And that we've been doing for 50, 60, 70 years. And then I think there was the genomic era for the last 15, 20 years or so where we really started to understand the blueprints and the typos and the blueprint that led to oncogenes alterations that were driving tumors and that led to the precision oncology era where we were using targeted therapies, tyrosine kinase inhibitors. And I think we're really entering this new era where we're going to have precision oncology built around our epigenomic understanding of tumors. And that's starting to make its way into the clinic. And so maybe I'll sort of use an example from some of our work where, in prostate cancer, where we recognize there's this subtype of prostate cancer called neuroendocrine prostate cancer. It's a particularly lethal form of the disease that develops in about 15% of men once they've become resistant to our standard therapies. Why do we care? Well, the NCCN guideline says, if you find neuroendocrine prostate cancer, here's how you treat it, and you treat it differently than sort of your run-of-the-mill tumor. In clinic, we don't have a great way to find it other than to stick a needle into a presumed metastatic tumor that's oftentimes the bone, painful to biopsy. Oftentimes, lymph nodes in the back of the bell, really kind of high risk to biopsy. And so what we sought to do is think about could we develop a liquid biopsy leveraging our understanding of this tumor subtype, which really we discovered is defined by, [ pathognomonically ] defined by epigenetic reprogramming. And so what we did is we performed methylation profiling of these neuroendocrine prostate tumors, identified a methylation signature that was highly specific for this tumor subtype, and then use cell-free DNA methylation profiling to demonstrate that, with high accuracy, we could detect this clinically actionable resistant subtype of prostate cancer. I'll sort of finish this thought with a comment that was made earlier, really resonated with me, this idea of sort of one-stop shop. As a clinician, you're busy. You want to get as much information in a streamlined way as possible. And so in clinic today, there isn't a provider where I can really -- or a liquid biopsy commercial assay, where I can get -- send a blood sample and get the genomics on a tumor, as well as the information into, is there development of one of these epigenetic subtypes that's evolving that is clinically relevant, something I will use to better treat the person sitting in front of me. And so if there was a provider, a commercial liquid biopsy assay, where I could get all that information in one blood draw, that would be a differentiator for me, and I think really unlocks how getting that integrated genomic and epigenomic data at the same time can and will today and even more so in the future, in the coming years, allow us as clinicians to better treat our patients.

I think this is actually a pretty great topic, which I would like, if this is okay, to expand a little bit because, for example, I'm working in lung cancer, and we had a trial where we're looking at minimal residual disease, so MRD, that we saw. So how -- can we see? Can we track cancer after surgery? Is there cancer still there? Did we cure the patients? Did we not cure the patient? And the interesting thing is we did this trial in a subtype of lung cancer we call non-small cell lung cancer, which sounds like we really narrowed it down. But in the end, non-small to lung cancer represents 85% or approximately 85% of all lung cancers. Those are different histology, different driver gene, different targets, different mutations. So it's a very heterogeneous set. And in fact, it is the epigenomics that we needed to use those thousands of markers that we have, that actually use just one assay for this big population and don't really need to put it in smaller brackets, one test here, one test for this. Especially also to keep in mind that it's not always stable. Like you say, you have the development of like prostate cancer to your neuroendocrine type. In the lung cancer we see the same. We see cancer switching from one histology to another histology. And if we don't have the capabilities to detect all of this, if we don't have this broad assay where we can use like epigenomics to see those changes, if we would just look at one mutation, for example, one clone, then we wouldn't really have the capabilities to really track what is going on. Do we see if there's still a tumor mass somewhere? Is there something shedding? Do we see tumor DNA in the bloodstream? And it's really the broader the panel is, and with epigenomics, I think we can go probably unreasonable broad even, and we really have the capability to capture all of this and not need to really go on, like, "Hey, here we have this very specific question, let's develop this assay." And for another patient, we need another assay. This is really very, very important what we see in lung cancer as well.

Yeah. And certainly, and cancer is something you've heard a lot about this morning's program, certainly. But I think you've all -- one of the things that I find very interesting about your work is that Will described something that's in every cell. It's not just in like mutations in cancer. It's in all of our cells, all of our tissues. And there's a lot of information and ways that we can use this, kind of more in physiology and outside of cancer and other chronic diseases. So I don't know if you want to say a few words, perhaps about that.

Yes. So just to take a step back really to the fundamentals of DNA, something that Will said quietly, I think, I hope it's clear to everybody, all cells in our body have the same sequence of DNA, right? Yet every cell type expresses only a subset of the potential program, right? Only a subset of the genes. And epigenetics is the mechanism that determines which genes, a certain cell type will express which genes it will never be able to express and which genes it actually expresses right now. And a classical example that we're working on as well is the insulin gene is present in all the cells of our body, right? But it's expressed only in beta cells in the pancreas and it's completely shut off forever in all the rest of our body. This is why if your beta cells are killed, you have diabetes because there's no other source of cells that can express insulin because it's shut off everywhere by epigenetic mechanisms. And of the many -- and the same is true for how brain genes are active only in brain cells and [indiscernible] muscles, et cetera. And the key -- there are many layers of epigenetic regulation, and the deepest, I think, really is DNA methylation that was mentioned here. So what is it? It's a covalent modification on certain cycles and it's in the DNA, that labels a certain part of the genome to be never be able to express, right? So when that gene is unmethylated, this is happening in a cell that can express that gene. And methylation patterns are really -- it's a highly stable modification. It survives when DNA fragments are going into blood or surviving from prehistoric times. And it's conserved among all the same cells of the same type. So all breast epithelial cells have exactly the same DNA metylation pattern. And all breasts in the world have the same pattern. So it's a very universal conserved mechanism that is really not changing in health in -- throughout the age and in disease conditions. And consequently, if you have a map describing the methylation patterns of all cell types in the human body, now you have a mixture of DNA molecules. For example, as what you would find in liquid biopsies in the DNA that you extract from plasma, which we'll discuss. So this allows you to tell which molecules are coming from which cell type, right, which is a tremendous utility we'll talk in a second. But these fragments are actually coming from dying cells. So you can essentially use that information, infer which cells are dying, which cell types are dying at a given individual at a given time. And what we have done in the lab in the last several years was to generate this essential atlas describing the methylation patterns of essentially all human cell types in the body. So it's a very powerful view into the tissue stores of DNA molecules, which goes way beyond cancer into essentially every disease that involves cell death and cell turnover.

Yes. Certainly heard about therapy selection, patient management, MRD, other cancers -- other diseases outside of cancer. Enormous amount of potential. Got to ask the question, though. So why aren't we already awash in epigenomics? Why don't we have diagnostics coming out of our ears using this already? And maybe as a follow-up, what's changed? And so maybe, Will, if you want to start us off?

Yes. I mean I think one of the biggest things that changed is the sequencing revolution, right? So the original human genome was 2,000. It costs maybe $10 billion or something on that order. Now we can sequence a genome for on the order of $100. That's an eight order of magnitude -- that's a $100 million fold improvement in 22 years. I claim that is better improvement of any -- better than any technology improvement ever in the history of technology. I used to give this talk and people and say, what about the discovery of fire? Okay, yes. Maybe you could -- other people would say, oh, what about -- I gave it to physicists and they said, well, what about the transparency of glass? And I was like, what the hell you're talking about? It turns out the transparency of glass enabled fiber optic cables to go under the ocean and brought about the information revolution that we are currently living in with respect to the Internet and whatnot. It turns out, I would argue, that sequencing is the equivalent of that for the information technology of biology, right? We now can make billions of measurements for hundreds of dollars. We can ask questions genome-wide, genome scale, and that is incredibly transformative, I would argue. So I think that's one of the biggest things. There's also molecular methods that have been developed to actually assay the changes -- the epigenetic changes that are also very relevant. But then you feed it into this amazing sort of mill that allows you to ask these questions at a scale that we couldn't possibly have dreamed of 20 years ago.

If I can add something to that. As a clinician, like that's incredibly exciting to me, sort of this -- I think any field, any new field, which I would say, cell-free DNA epigenomics, I would consider, is limited by the rate of data generation, just the amount of data that we have. And so for example, in this project I referenced earlier, when we were looking at neuroendocrine prostate cancer, we found 21 patients that we were able to study and demonstrate that we could sort of deploy this cell-free DNA epigenomic assay to detect this cancer phenotype. But that was over 20 years, we found those patients. And so just thinking about the promise of billions of base pairs of cell -- epigenomic cell-free DNA across tens, hundreds of thousands of patients, it's an incredibly rich repository to ask and answer questions that we couldn't dream of asking and -- well, we can dream of asking, but not being able to answer just because the data doesn't exist. And so I think -- thinking about the power of this magnitude of data we're generating, being able to have hypotheses, ask the questions, develop models to demonstrate proof of principle, test and validate cell-free DNA biomarkers for any clinical scenario you can imagine, I think it's incredibly powerful and really will unlock biomarkers to then apply to clinical trials, think about patient selection for novel therapies, I think, sort of coming into those trials with the right biomarker informed by these databases, is going to lead to higher success rates for clinical trials and really accelerate drug development, too. So I think it's an incredibly -- I sort of hear your enthusiasm for what this is going to unlock.

I think it's also important to add like, when we go from technology, the discovery of fire to like, in the end, implementing it to like really as an asset, I think it's also very, very important to understand that it's very, very different of having technology and bringing it into the clinics. There are a million of steps, very complicated, many of them really annoying, to be really honest. So for example, what we saw was something like a chicken and egg problem, because we had ideas and we were very confident even with the data we have that those ideas might work in a clinical context, and if we were capable of translating those ideas, for example, into a clinical trial, we were very, very confident that this might really work out. But on the other side, we didn't have an assay. And without having the capabilities of proving our ideas, so to say, usually, people are very, very reluctant to say like, hey, we just develop an assay for like your idea because who knows what's going to happen? Let's be honest, even today, many of those ideas don't turn out to work out. So it's -- there is a certain risk associated. And we were always in this weird situation where we have like, on one hand, we had to prove that we can do it to attract people to work with us, and then on the other side, being not really capable of doing it because we didn't have the capabilities. And what we did recently, well, not really recently, so we started to develop our own assay. And it took us 4 years, and it's still ongoing, to really try to develop our own assay, to get everything there, to get it validated, to have our ideas, to have our software and everything locked down. It's an ongoing and it's a very, very painful process. But the interesting thing, with a platform like the Infinity, it seems like a little bit we are breaking now kind of this vicious cycle of where we always have to go around. Because we heard about data and data generation and the data that is there. But when you have an assay, which kind of covers everything, then what you do actually is you stop assay development and you start software development. You start algorithm development. The question that we have is not do we have an assay. I mean, we heard earlier this, with like PCR, we have like design premise for like everything. But now we are in this weird situation. And frankly, I'm still struggling to really understand how profound this impact might be as we are no longer really developing assays now. We are just developing a software algorithm. We have the data. The question is just what is the question we are asking. And the weird thing that goes even beyond this is we had all those ideas, and we were developing our project, which was a little bit of better understanding, a specific lung cancer, which is small cell lung cancer, where we saw very specific phenotypes for different cancer types. It has nothing to do with genomics. Genomically, all our phenotypes were the same. It was really tumor intrinsic differences and the phenotype and the shape of the cancer. And I'm working at the Department of Thoracic/Head and Neck Medical Oncology. And I was presenting this, this data very exciting. And then what happened is that actually a colleague approached me with a cancer, I've never heard in my whole life about, say words I've never heard in my whole life about. And she was like, "Hey, this is really cool, what you do there." In our cancer type, we actually have the same situation. We have a very homogeneous, genetically homogeneous cancer type, but we see very profound phenotypical differences. And we didn't know we can do this because it was like, yes, there's only genomic testing for like liquid biopsies. And then she came to me like, hey, this is actually cool what you do. Can we do this for our cancer type? And it's crazy, we spent like 4 years of very painful work to really try to develop assays. And now that we saw the shift to actually just changing the question, changing the algorithm, how quickly we can now adapt to this. So I think the important point is the ideas are there. This is one example of one department or one institution. So I don't want to know how many ideas are there. Probably we can spend the next 2 hours just speaking about our ideas. The ideas are there. We were limited by the tools. And now it seems like that we have the tool, that we really have now a better chance to really adapt those ideas and bring them really into the clinics and at least try them out. It doesn't mean all of them will work out, but at least we have the chance to try them out.

Yes. I mean, I think one of the -- again, going back to the same theme of every cell having that same epigenomics, we talked a lot about the applications in cancer here, but as we move from advanced cancer, which we saw, doing over 200,000 of those this year, and move -- and growing. We move into early-stage cancer. We start seeing patients with earlier stage disease, but then we see patients post curative resection who no longer have cancer, but they may be developing other diseases. And then moving into screening, we might be talking about literally millions of patients, by definition, don't have cancer. But they're in the same crowd that develops other diseases, which I think is exactly sort of, Yuval, what you've been looking at. So maybe if you can comment about having this type of rich data set and how that might change things.

Yes. Happily. I just want to -- one more comment about the first question is, I think it's not just technology, it's also biology. It took us a long time to understand what's going on there. I mean people have noticed that there's DNA fragments in blood many years ago, but only quite recently realized that this reflects a process. And here is the state of the art right now. So when cells die in the body, they -- in some cases, they release short fragments of their DNA to the circulation. There is not much of that, a small amount relatively. And it is cleared within 15 minutes to an hour. That's the biology as we understand it today. In certain cases where it will never work, liquid biopsies, in some cases where there's a tremendous potential. And this is what we're working on. And the idea is that by determining the methylation patterns of those cell-free DNA fragments, you can assign their tissue of origins. And since they are coming from dying cells, you can say exactly which cells and, quantitatively, are dying now in the last hour or so in the individuals that donated blood. And this, in my view, really opens an amazing window of opportunity into essentially monitoring, diagnosis, diagnosing essentially every human disease that involves cell death and cell turnover. So some -- many, many applications, just to note here, some that we're actually working on. So we have a proof of concept for each. So for example, it turns out that in early-stage Alzheimer's disease, there's elevated levels of cell-free DNA fragments carrying the methylation mark of brain, neurons, right? This is an early indication of brain cell death in that disease, is potential because no good biomarkers for early stage Alzheimer's. Lung cell-free DNA molecules is indicative of early-stage lung cancer, but also other lung pathologies like COPD and lung fibrosis. Really whenever cells are turning over and dying, we've shown that -- the presence of pancreas DNA can be indicative of presence of early-stage pancreatic ductal carcinoma, the mostly lethal solid tumor, as well as pancreatitis. [indiscernible] heart cardiomyocyte cell-free DNAs can be a reflection of myocardial infection but also more chronic congestive heart failures, which is really a pandemic drug efficacy and drug toxicity when drugs are affecting badly organs such as the liver, the heart, the kidneys, DNA from these organs identified by methylation patterns can detect that early before organ function is deteriorated and organ transplant recipients, really endless, very exciting applications with many, many proof-of-concept studies, really, I think ready now to move into the commercial domain, really bringing noninvasive epigenetic liquid biopsies into much of diagnostic medicine.

You mentioned actually screening and you spoke earlier about insulin and the epigenetic regulation of insulin. This reminds me of something which we had to deal with, even struggled with a couple of years ago, because we were actually working with the screening population. And it was a very high-risk lung cancer screening population. And the idea that we had, that we use liquid biopsies to detect lung cancer. And it was very, very interesting. So we started this analysis. We had over 600 patients, and we worked with fantastic mathematicians at the time. And when we gave them the data, we're really looking, it was for me, it was the first product with machine learning, but it was still very, very fancy at the time. What they came up with for the first data analysis was that the patients didn't necessarily clustered with like those who had lung cancer, those who didn't have lung cancer. The patients or the data from the patient we got were like diabetes, heart disease. And it was crazy now when you speak about it for me because we get a little bit like, oh my God, this is not what we want. This is a problem. We have a lot of noise in our data. How can we filter out actually -- yes, exactly, how can we filter out this signal? We want to detect lung cancer. And when I think about this now, this is kind of a weird way to think about it because this is true data, this is real data, and we just asked the wrong question. So probably when we ask the right question, we get the right thing. And also, you spoke about screening, and I feel like we're a little bit biased or at least I'm biased from a cancer thing. And when we speak about the screening trials, we speak about healthy populations or something like this. What we mean is patients or a population of people without diagnosed cancer, without diagnosed colorectal or lung cancer. But when we look at this, you mentioned a screening trial with 10,000 patients -- 10,000 people, I'm very, very sorry. So those people will have certain comorbidities. They will have diabetes, heart disease, many, many other questions, and the data is there. So probably just need to ask the right question with the data we have to, like you say, bring it into other places and other settings.

Yes. And I think certainly, a couple of the comments you've made have echoed what I think we heard earlier from both Darya and AmirAli around establishing a panel and sort of breaking the cycle of redeveloping the diagnostic every time you discover something, and shifting that over into a software cycle. I think one of the differences that I have sort of been thinking about in terms of the epigenomic revolution, if you will, versus the genome -- advent of the genomic revolution is the concept of the scale of data. And as Will mentioned, we are making very much shiny or more transparent glass, which is awesome. That's my new -- that's my new touch stone. But at the same time, at that time, we had no clinical annotations. We needed population studies that went on for decades and everything that were clinical studies, had great cost, to really get any clinical information. That paradigm has shifted entirely for the entire field, not just Guardant, by allowing this de-identified sort of aggregation of real-world clinical data with the combined genomic and now epigenomic data. So as you wrap these things in, we're not only taking that advances in biology, but you're actually pairing it up with clinical data. And we obviously just talked at great length, I think, and really, really exciting potential for noncancer disease. But I wonder, Jake, you're an expert in these clinical trials that take forever, what do you see as sort of the advantage to not just having these massive data sets to look at in terms of the genomic and epigenomic data, but having that paired up with the fact that, out of these 200,000 patients, these 16 patients died of a myocardial infarct when they took drug X, something like that. What do you see as sort of the potential there just for patient care and sort of the cycle times and...

Yes. No, it's enormous. And I'll echo what Simon said about how it's just now just thinking about what questions you want to answer and now we have a platform to really look at these -- oftentimes, a lot of the clinical populations we want to study are relatively rare. The -- a lot of the clinical -- a lot of the patient populations that we really want to study where we really need to make inroads to do better are relatively rare populations. And think about sarcomas. And in clinical practice, it's really hard to put together databases that are large enough to make any sort of conclusions. And so I think the power of pairing this -- these epigenomic database, genomic, but also epigenomic databases, with the clinical data to be able to really study select clinical patients, or clinical scenarios where there is an unmet need that we could address with liquid biopsy, having the power of large data paired with clinical outcomes to be able to ask and answer these questions that were previously unanswerable, is incredibly exciting. And I think -- I just want to circle back to comment -- another comment Simon made earlier, but this idea of target size, I think, is really important, that hasn't come up explicitly when thinking about epigenomics compared to genomics. There are a lot of clinical scenarios where a tumor of interest doesn't have defining genomic characteristics, so the epigenomics are key to making a clinical diagnosis. But also even when there are genomic features and epigenomic features, we're often looking at a handful of defining genomic features. Whereas the epigenomic space is hundreds, if not oftentimes thousands of sites that we're looking at. And so I think adds another layer of power to these types of analyses. And then, this is a little tangential, and I apologize, but I really want to make this point because I think, again, putting on my clinical hat, this is something that's sort of easy to overlook, but it's so powerful about liquid biopsy, which is this idea that we can follow -- get blood sample serially, repeatedly, over a course of the patient's disease course or over the course of a clinical trial. That sounds trivial, obvious, baked into a liquid biopsy. But take my work for getting tumor biopsies is so challenging in practice, in clinical trials. A lot of clinical trials on enroll because they mandate biopsies before and after a patient receives the therapy. So being able to generate this scale of data, but also on an individual patient level, collecting that data at multiple time points is going to allow us to study how tumors evolve in response to given systemic therapies evolve over time to really understand how we can better target treatments or tumors as they evolve. So I think incredibly powerful as sort of the short answer. And would love to hear what my colleagues think.

I think maybe just one comment there is that, in some ways, precision oncology is a victim of its own success. It's gone from -- it's now gone to almost a management of a long-term disease. I mean, Craig showed a great patient today that was living for, I believe, 7 -- 8 years with advanced lung cancer. That just never used to happen. And so now there, I think, is definitely needing to be a shift in the tools from away from treatment and towards management because it's a long -- it's sort of -- it's a marathon, no longer a sprint, which is a good thing.

And maybe one final comment there is that, as we study how tumors epigenomes are evolving, which I think liquid biopsies will enable, it's going to allow a whole new era of precision oncology. All of our targeted therapies are based on an understanding of a genomic driver. We don't understand a lot of the epigenomic drivers. We're starting to learn neuroendocrine prostate cancer, small cell lung cancer, that transforms from lung adenocarcinoma. But I think those are the low-hanging fruit. And I think really being able to follow these patients serially, understanding how tumors are becoming epigenomically driven that's going to allow us to target sort of usher in a new era of precision oncology.

Yes. Now we're coming up at the end of our time here. So I think maybe just to riff off of the low-hanging fruit comments, I'm just going to ask the panelists to put their nickel down. And so in your own fields, look forward a year, 2 years, what is the one concrete thing that we can never go back from? What is the thing that we're going to find, that we're going to achieve, that we're going to build, that's going to change the field, and we just can't go back to the days of PCR, for example? Will, maybe start with you.

Well, that's a deep one. So I think one of the things that's happening in my field right now is really trying to understand sort of cell-type resolved information, and part of that is sort of single cell analysis. So obviously, trying to understand not just taking a piece of tissue and grinding it up and asking about the molecular details of sort of the average cell in a tissue. Actually separating out individual cells and understanding the details of the functional genomics associated with each of the underlying subtypes of cell in a complex tissue. That's becoming a revolutionary. And it allows, in terms of the diagnostic potential, really understanding specifically what types of individual cells, of which there are hundreds of thousands of types potentially, or thousands of types in the body, are generating signals and where are they in your body and what is their dysfunction. I think that single cell revolution is something that is sort of ongoing in the field in terms of phenotyping with respect to RNA, but also becoming, I think, a revolution in the epigenetic side of things to really understanding what the molecular states are that drive those phenotypes at the level of the genome.

What do you think, Jake, how is advanced cancer treatment going to change?

Yes. So I'll -- just 2 things quickly. I'll just quickly reiterate. I think the union of large data sets that pair the epigenomic liquid biopsy data with the clinical outcomes data is going to be incredibly powerful to unlock our ability to develop the next generation of precision oncology biomarkers. The second piece that -- is I think there's going to be, over the next decade, a wave of sort of novel drugs targeting epigenetic targets, drugs like [ PROTACs ] that are able to target transcription factors, these epigenomic drivers that have been historically considered undruggable, that we're going to be able to target therapeutically over the coming decade, years, decade. They're already in clinical trials in clinics, but I think really will be standard treatments in the coming years. And those are going to have epigenomic biomarkers. It's not going to be EGFR mutation. It's going to be some sort of epigenomic state that we need a clinical biomarker to identify which patients are going to benefit from this new wave of epigenomic drug. So I think -- excited to see how that shakes out.

Well, how much time you all have. I think we can spend there a couple of hours speaking about it. You just spoke about EGFR. So I think that's a good thing to pick it up. Because when we look at lung cancer, it has become the poster child of like precision oncology because we have those very active drugs, for example, against EGFR mutations. And what we saw is, with the beginning of those TKIs, those tyrosine kinase inhibitors, which are targeting EGFR mutations, what we saw in the beginning was like those work very, very well, and then we saw the occurrence of like resistance mechanisms, resistance mutations. And I think actually, that tracking those resistance mutations in EGFR is still probably the first field where liquid biopsies really impacted clinics and which was probably the first question which was adapted. Do we see resistance mutations in EGFR driven lung cancer? The thing that then happen is now we have seen a development of much more effective drugs. And we are now in the third, fourth generation of EGFR TKIs, and the drugs are becoming increasingly better and better and better. And with the performance of those drugs, we also have the complexity of the resistance mechanism. And when we look at today at like third or fourth generation EGFR TKIs, we no longer see that many distinct mutations that we can easily track with the assays we have, but we see much more complex resistance mechanism. We see chains of histology, changes from lung adenocarcinoma to lung squamous carcinoma, from lung adenocarcinoma to small cell lung cancer. We see something that we call EMT, epithelial to mesenchymal transition. So we see very complex mechanisms to resistance, which currently we cannot detect from liquid biopsy. The only reason to detect them right now are biopsies. The important thing is we connect on all those mechanisms there. So we need to detect them. And this is really a field where we have exhausted our possibility with genomics test, where we have the need for epigenomic test. But also, I think when we really managed to get this out to have the immediate clinical impact on how to act and change treatment based on this. And I think this is something we really need to get things going because it will directly impact patient life.

I know I would be last, so I would try to come up with one thing that you guys won't come up with. So a few points. There's now -- so DNA methylation encodes, among other things, also turns out it encodes your age, your chronological age. And with the advent of these so-called epigenetic clocks, we've now worked on that and perfected that in the lab, I can take a blood sample, and tell you a chronological age with an accuracy of 1 year, 1 to 2 years. This is of tremendous interest to another community forensics, right? But it turns out that there are also epigenetic clocks that detect not your chronological age, but your biological age, which can predict the expected time of death, and how old are you -- what's your rate of aging. And I think this is going to be an incredible breakthrough in terms of aging research, anti-aging drugs. You're going to have to wait for 120 years, but you can immediately assess the effect. So I think that's one big thing. Another I think of the upcoming application of methylation epigenetics in the context of actually of cancer is detection of metastasis, right? Location of metastasis. And whether a patient has local curable disease or disease with micro metastases that you guys cannot detect can be discerned with these tools, because if there's damage to the brain in individual with lung cancer, this might reflect early stage. So I think that's a big thing. And second, I think we're not done with technological -- incredible technological breakthrough. One thing that I'm thinking about a lot is that everything that we'll discuss here is relevant for diagnosis that can be delivered within days. The entire field is completely excluded from emergency medicine. But we're almost there, we can do that. So I think there is -- absolutely feasible to develop a methodology that can develop results in 1 day, in the same day, which will open up entirely new applications for people in the ICU or people admitted to emergency rooms. I think we're almost there, and that can change completely the scope of what liquid biopsies can deliver to diagnostic medicine.

That's exciting. So again, thank you very much. Appreciate your time. Appreciate your attention. And help me thank our panelists here for their participation.

Please give us a moment while we prepare the stage. Please welcome Chief Financial Officer of Guardant Health, Mike Bell.

Yes. So good morning, everyone. Great to see you all here. So now changing tack a little bit. I'm going to sort of now talk about how the many opportunities that we've talked about this morning, how they're going to translate into rapid revenue growth and then how we're going to balance that growth with financial discipline. And obviously, I'm going to give some 5-year long-range targets financial for the company. So before I go into the future, I just want to remind everybody of the progress so far that Guardant's made. Over the last 5 years, we've had very, very strong revenue between 2018 and 2022. Revenue grew almost 50%, and that's mainly come from our core Therapy Selection business. Since 2018, we have some rapid expansion across both the clinical and the biopharma businesses. We've had major reimbursement wins. We've had companion diagnostic approvals that have been driven by clinical data. As Chris pointed out, we've grown our commercial strength, and we now have one of the strongest oncology sales forces in the U.S. We've got over 160 biopharma partnerships. And now we've got the industry-leading portfolio. And turning now to the testing volumes, which drive our revenue. Again, we've seen rapid expansion over the last 5 years. The clinical testing volumes grown at over 44% over the last 5 years, and biopharma testing volume has grown 26% over the last 5 years. These charts show all of our oncology testing volume, but it's true to say that the vast majority of the volume growth that we've seen over the last 5 years has been driven by Guardant360. And as you'll see in a moment, we've still got very strong momentum with the Guardant360. Looking first at our first half of 2023, we've grown our revenue by 30% year-over-year. And again, that's mainly been driven by our core Therapy Selection business, and in particular, Guardant360. We've had multiple tailwinds over the last few months. In February, we've received FDA approval for a companion diagnostic for breast cancer, and that's driven our volumes, and we've seen a really great uptick in volumes over the last few months. Also for Guardant360 over the last few months, we've had really strong commercial payer traction, and we've got additional coverage from multiple commercial payers. In Japan, Guardant360 got national coverage in July. And in the same month, we're able to commercially launch the product. And obviously, earlier this year, we got response to Medicare coverage and, as Chris mentioned earlier, we're making great progress with our EMR integrations. We're very pleased with 2023 so far, but believe there's much, much more to come. Specifically for Therapy Selection, there are multiple drivers that can continue growth well beyond 2023. Chris has already talked about quite a few of these, but I just want to reiterate some of them again. I just mentioned the multiple reimbursement wins we've had recently, and we've got the potential to add more covered lives and commercial paid contracts in the future, which is going to lead to increases in our ASP. We've seen upticks in volume following the FDA companion diagnostic approvals and our strong development services pipeline can gain more approvals, which again will increase clinical volume. Our additional portfolio offerings will also drive volume, and we're seeing attachment rates increase for both TissueNext and Response. Chris outlined earlier, the market expansion and the need for Therapy Selection in oncology and how that is leading that market expansion. On the biopharma side of the business, we've had a huge amount of interest and traction with GuardantINFINITY. And that's becoming a major differentiator and growth driver for our biopharma business. And finally, looking outside of the U.S., today, international revenue has been relatively small, but we're now on the cusp of significant growth in Japan, the U.K. and China. And we expect these countries to start to provide meaningful revenue in the next year or so. What's very pleasing is that as we grow, we're starting to realize significant leverage from our infrastructure that we've built over the last few years. You could say that we've already built the house. Our oncology team is the strongest in the industry. Our team of regulatory and reimbursement experts have got a track record of gaining approvals and coverage. And our operations team runs our test in fully scaled, highly efficient labs that have got their capacity to handle our future oncology growth. On the R&D side, we've got an incredibly strong clinical development data engine. And with our smart liquid biopsy platform, we're going to be able to drive synergies for technical development. Finally, we've been making investments outside of the U.S. for several years. We've got in-country lab and commercial operations in Japan. We've partnered with top-tier organizations and major markets in the U.K., Spain and in China. And we've established regional hubs in Europe and in Asia. So we're well placed to start to maximize the international opportunities in front of us. In total, this leverage, together with our revenue growth is translating into improved bottom line performance for our Therapy Selection business, which is now on track to be cash flow breakeven by the end of 2023 and will start to generate positive cash flow from 2024 onwards. To emphasize this leverage, I'd like to remind everyone of our full year 2023 financial targets. We've increased our revenue guidance a couple of times this year. On our Q2 earnings call, we guided 2023 revenue of $545 million to $550 million, which is a 21% to 22% year-over-year growth. What's satisfying is that we're going to be able to achieve this growth while at the same time reducing our operating expenses. Our stated target at the start of the year was for full year 2023 operating expense to be lower than the previous year in 2022. And I'm pleased to report that we're still on track to deliver that. And then with increased revenues and reduced operating expenses, we're also on track to lower our cash burn from a peak in 2022 to approximately $350 million in 2023. Again, we're very pleased with the progress we've made so far this year. Later in the presentation, I'll discuss how we plan to further reduce our cash burn. And over the next few years, and how we'll reach cash flow breakeven. Okay. And so now turning to our MRD business. Again, we had really strong performance in the first half of 2023 and our volume grew of 100% year-over-year. We achieved this against the backdrop of closely managing our cash burn for the company, specifically for our MRD. This has meant we've proactively managed the volume of non-reimbursed test and how many talked about that earlier. Clearly, gaining additional reimbursement is going to be critical to us to be able to unlock revenue volume and revenue growth in MRD. Again, how we mentioned, we're laser focused on developing clinical data for CRC surveillance, lung and breast as well as other indications. And it's also worth mentioning again the significant operating leverage that we get from our existing Therapy Selection business, and it's going to make MRD a very highly efficient business model going forward. Now I'd like to lay out our 5-year financial targets for Therapy Selection and MRD combined. With the multiple opportunities that we have ahead of us, we're confident that we can continue to grow Therapy Selection and MRD with a combined 5-year revenue CAGR of greater than 20%. Part of this revenue growth will be driven by increasing our ASPs, which will come from commercial contracts and additional coverage for Guardant360 and TissueNext and Response and from additional Medicare and commercial coverage for Reveal. As target ASPs for 2028, Guardant360 to be greater than $3,000, Tissue to be greater than $2,000 and both Reveal and Response to be greater than $1,000 by 2028. Looking at gross margins. Our blended gross margin for Therapy Selection and MRD is currently over 60%. And our target over the next 5 years is to maintain that blended gross margin in the 60% to 70% range. Of course, this is going to be dependent on the ASP increases, I just mentioned, and it's going to be impacted by product mix. But with our plan to reduce our cost per test over time, we're very confident we can manage within this blended gross margin within this range. I just mentioned the significant leverage that we're getting from our infrastructure, and that's going to allow us to carefully manage our OpEx and CapEx over the next few years. And again, we're already seeing that leverage translate to Therapy Selection being cash flow breakeven by the end of this year. And as we look at the 5-year period, our target is to generate -- 5-year period is to generate cumulative positive cash flow from the combined Therapy Selection and MRD business. Now turning to screening. As AmirAli outlined, our expectations are to receive FDA approval and Medicare reimbursement for yield in 2024 and to be included in guidelines in 2026. If we achieved those milestones, we're very confident that by 2028, our annual testing volume will exceed 1 million tests and assuming an ASP of greater than $500 that our annual screening revenue will exceed $500 million in 2028. Now to focus on how we'll balance that rapid revenue growth in screening with measured spending and how we can manage our screening cash burn to be approximately $200 million a year over the next 5 years, starting first with ASPs and gross margins. As AmirAli outlined, we expect to be able to maintain an ASP of around $500 by targeted commercialization and by adding private payer coverage based on recommendations and guidelines. That, and projected cost per test reductions, is going to lead to positive gross margins 1 year after launch, and gross margins of approximately 60% when we reached the milestone of 1 million tests per year. At Guardant, we've got a very experienced operations team, and we've got leadership that has built and operated large-scale labs for major diagnostics companies. That team is now laser-focused on building a highly automated, high-throughput lab operation that will rapidly get us to a low cost per test and which can be done with very efficient milestone-driven capital spend. From an OpEx perspective, the major expense in screening over the last few years has been focused on CRC and the ECLIPSE study. ECLIPSE is now winding down. And as a result, R&D spend in 2024 is going to be lower than in previous years. Going forward, we're confident that we can maintain that level of R&D spend, while still making very good progress in lung and multi-cancer early detection. Also, by performing development on the unified smart liquid biopsy platform is going to allow major cost synergies right across R&D. Finally, for SG&A, as AmirAli already outlined, we plan to have a very efficient commercial model. The growth in S&M spend is going to be gated by milestones around approvals, revenue growth and reimbursement. And on the G&A side, we're also going to be able to leverage the back office infrastructure that we built at Guardant to ensure that, that spend is very well controlled. So recapping for screening, we're very excited about the revenue growth opportunities. And at the same time, we're very confident that we can manage the cash burn to our target of around $200 million per year over the next 5 years. So putting this all together, what does it mean for the overall company? As I previously mentioned, for Therapy Selection and MRD, we're targeting a combined revenue CAGR of greater than 20% over the next 5 years. And for screening, we believe that by 2028, we'll be generating over $500 million per year in revenue. Overall, this means that our 5-year total revenue CAGR will be greater than 30%, and that our total annual revenue will be greater than $2 billion in 2028. With the Therapy Selection growth drivers that we've outlined with the focus on the MRD, ASP and volume growth and the huge potential that we have with Shield, we're very confident we can deliver this revenue target over the next 5 years. Now looking at our cash and our path to breakeven. In May, we completed a successful equity offering. And as I mentioned earlier, we plan to lower our cash burn in 2023 to be around $350 million. As a result, we expect to close out 2023 with over $1 billion in cash. And as we look out to the next 5 years, we're confident that we can continue to lower our cash burn. And by the time we reach 2028 and with over $2 billion in revenue that will be cash flow breakeven. In addition, our total cash burn over that period will be less than $1 billion. Again, our main assumptions here that Therapy Selection is breakeven by the end of 2023. And then the combined business of Therapy Selection and MRD generates positive cumulative cash flow over the 5-year period and that our annual screening cash burn is approximately $200 million. Finally, wrapping this all up and summarizing our 5-year financial targets. We expect Therapy Selection will continue to be a significant growth driver and from 2024 onwards will be a profitable business. We'll be laser-focused on MRD data and expanding reimbursement, which will allow us to fully unlock Reveal volume. We'll thoughtfully balance the rapid revenue growth of Shield with measured spend. We'll achieve a 5-year total revenue CAGR of over 30% and reach over $2 billion in annual revenue in 2028. And finally, that will be cash flow breakeven by the end of 2028. Thanks, everyone, for your time. I'll be available for Q&A at the end of this, but now I'm going to hand over to Helmy and AmirAli to talk about the future of Guardant.

Okay. Let's wrap it up there. So it's -- we've been in this field now for 11 years, and we've wanted to essentially think about really what it means to stand side-by-side patients on their journey. And we often think of cancer as a linear journey, but it's really more of a cycle. Early detection is not -- and the beginning is not the end of someone's journey, but it's really the start of a whole new scary chapter in someone's lives. And it's, one, we're going to be able to guide them through with Therapy Selection and MRD and hopefully continue to stand side-by-side with them as they're cured and they become new candidates for further MRD and screening. This is really where all of our products will work synergistically with one another, and we can essentially guide those patients throughout their lifetimes. Our tests are unlocking an unprecedented amount of biological data out of a single tube of blood. And this is informing us about the tumor's genomic makeup with exquisite detail allowing us to characterize whole body epigenomics, which, as you saw from the panel, is very exciting and even get a detailed analysis of the immune system, all with a single tube of blood. And with GuardantINFORM, we are linking 90% of these biologically rich tests with critical clinical information such as treatment history, comorbidities, disease progression and survival. And all of this is linked with exquisite genomic and epigenomic data, I mentioned before. And this is something we've done many times now. We worked with many pharma companies on essentially these linkages with Guardant360. And so with the GuardantINFORM, we have established that we can synthesize in silico Kaplan-Meier curves, as you see here, that allow us to track how therapies behave in certain populations or even discover novel predictive biomarker signatures. And so this allows us to do, what we call, sort of closed-loop development where we can develop new diagnostic capabilities from our smart liquid biopsy platform and clinically validate them efficiently with GuardantINFORM all sort of in a very nice, tightly bound R&D cycle. And we're going to do this at scale. As you saw from the panel today, one of the biggest issues in healthcare that, at least from my perspective, is that it's data starved. We often don't have enough data on specific cohorts of patients to really understand what works and what doesn't. And so we're going to be able to do this at scale and allow for more precise tools as we augment that data. And so as our Therapy Selection, MRD and Screening businesses continue to grow rapidly, we will soon be reaching the scale of millions of tests per year across our business. And many of these tests are going to be in average risk individuals from our screening business. And as the testing grows, our GuardantINFORM database will grow rapidly as well. We've built the architecture in such a way that it's very tightly coupled. And so all we have to do is turn this figure on the test comes in, the data comes in that -- and the clinical outcomes come in as well. And so this is going to accelerate rapidly. We're already doubling at an 18-month rate. And it's -- I believe that's going to accelerate even further as our franchisees become more and more successful. And so this will reach an unprecedented scale over the next 5 years, rivaling some of the largest global genomic databases to date, and enable us to set our sights maybe on even some more crazier and more ambitious goals for tackling areas of continued unmet need in human health.

And the way we are looking at this data is this is the treasurer of Guardant. We can have a philosophical conversation, are we selling blood test or we are selling information to this market? Without making it philosophical, this is the treasure that we believe over time we just pay dividend for Guardant. How? As we actually heard from the panelists, this concept of epigenomic is not just related to cancer, it's the fundamental basic biology of the body. Not only we can find cancer relevant information in blood, we can find neurodegenerative disease relevant information, we can find or try this IVD, cardiovascular, COPD information in blood. And why is that relevant? Just imagine during the days that we are testing millions of people and not only we are capturing their data, as Helmy mentioned earlier, we are connecting that to the medical record. And we are finding the patients that, in fact, maybe did not have cancer, but they had Alzheimer, maybe they had COPD, maybe they had arthritis. Correlating that data to the real-world disease status of the patient is what's going to be the future of what we can do. So cancer is the starting point. We are highly focused on it, but just the database that we are gathering would pave the path for us to go well beyond oncology. The concept of screening, the concept of MRD, the concept of treatment selection is not just in oncology. It's a multiple disease criteria. And then you can imagine in your head where we are going to go. And all that is with leveraging what we have, the same data engine generation, the same commercial team, the same technology stack just leveraging and getting dividend out of this for other disease areas. And this what we believe Guardant can do, expanding our mission from transforming cancer and concurring cancer with data to guarding wellness for all. With that, this part of the presentation ends, and we are going to have some Q&A. So maybe until the stage gets set up, we can think about your questions and we will start. Maybe Mike, Hel, if you can join us.

Great. Dan Brennan with Cowen. Maybe first one to Mike. Can you separate out the revenue guide for 5 years? I think you had Therapy Selection, MRD tied together. We'll be interested to see what kind of revenues you're attributing to both and kind of any implicit like share of market memory that you guys are assuming? And then B, on the $200 million burn on screening, could you give a little bit more color what constitutes that? And if you talk about gated spending, kind of what drives those gates? Like what are the decision points that will dictate do you alter that spending?

Yes. First on the Therapy Section and MRD. And I think we're very careful to give a combined revenue CAGR of 20%. And we don't want to -- specifically we're breaking out the revenues between the 2. But I think it's fair to say, if you looked at the historic revenue over the last 5 years, that's mainly been driven by Therapy Selection. It's been growing at a rate much higher than 20% over that time. And as we've been at pains to point out this morning, there are a lot of opportunities ahead for Therapy Selection. So I think that can continue very strong growth. MRD, in a way, is going to come on top of that where we're sort of holding back the volumes at the moment. We really need to get the reimbursement and increase the ASP. So we think -- again, yes, I think the majority of the revenue over the short term is going to be Therapy Selection, but then really MRD can start to really drive that revenue, hopefully, much higher than the 20%. And on the Screening spend, yes, again, I mentioned research and development has been the main spend over the last few years that can now start to come down. We'll still be working on multi-cancer and lung. But I think revenue -- R&D spend will come down. And then as we pointed out, we'll be increasing the commercial investment. We'll be building out the field force. And yes, we'll be getting it on -- first of all, the first gate is to get FDA approval on Medicare reimbursement. When we know we're close to that, we want to start ramping up. And as we start to get into state level guidelines, again, that's going to be the driver for us to build our sales force again. And again, when we get to in guidelines and when we're at scale of 1 million tests, then we're just going to get the build of the spend over time.

Great. And then maybe just on screening, maybe for AmirAli, just could you share some color about the FDA interactions. You said you're very pleased. Just any incremental color there and thoughts on the label? And then on the V2 version, I think you showed the combined stage I, stage II sensitivity. Would you be comfortable breaking those out? And any thoughts about the 2025 time line you discussed in terms of have you discussed that with FDA, the supplemental PMA process?

So in terms of interaction with agency, we are making steady progress, as I mentioned earlier. Really the agency has been very collaborative collegial in terms of resource spend, availability conversations. It's been great, and we appreciate all the efforts happening, but still we are in the review process. But based on everything that we see, we continue to expect FDA approval in the time line that we've been always talking about in 2024 and launching it in 2024. In terms of V2, so -- once we want to get approval as a PMA device, since this is just an algorithm update, we think, as I mentioned, we can just do supplemental PMA. Let's say the quick route in terms of the details of what needs to go to that supplemental PMA, some interaction with agency and coordination with the agency would be required. In terms of the data that I showed earlier, so on the samples like on this staging site still is in progress. It's like, "Hey, it's stage I, stage IIA. And I think the way we look at it is like even for ECLIPSE like 55% stage I, 100% stage II, when you run probably 10,000 samples, stage I, 10,000 stage II, maybe some of the numbers is just within the variation, right? So you need to combine some of this in order for it to have more statistically meaningful performance assessment. So -- and this is very strong. When you see 76% goes up to 88% when you combine stage I, II, which is effectively the localized disease, it's pretty interesting. As I mentioned, it's not the regulatory-grade data though. We have to coordinate with agency and figuring out in terms of derisking. We are very pleased with what we've seen.

Guys. So Mark Massaro, BTIG. Thanks for a great presentation. So looking at your ASP assumptions, they do look quite achievable, even conservative to me. So I wanted to ask some questions on ASPs. So the first is G360 CDx, you're at 5,000 and the LDT is at 3,500. So based on the number that you just provided, is there any reason why you can't go materially higher than the target you just laid out? And then for Shield CRC, 500 plus, your list price is substantially higher than 500 plus, and you're pursuing ADLT. So I'm trying to bridge the difference between 500 plus and perhaps 900. How do you think about that? Are there any changes to your pricing strategy on CRC?

Yes, I can take the Guardant360. Yes, I think if you look at our ASP at the moment it's 2,600, 2700. We've seen that move up over the last 6, 9 months as we sort of the mix between LDT and CDx, has moved more towards the CDx, which you mentioned is higher reimbursed. So that could be a positive trend for us. Again, we've seen positive trends from commercial payers. We need to contract with those payers. We need to see those payments coming through. But yes, again, I think that can drive that. International expansion, which we talked about in Japan, the reimbursement rate, there is in this 2,600 to 2,700 level. So again, that can help support as we grow. So can the ASP on Guardant360 get higher than 3,000, I think, yes, materially-higher, it depends. I mean, I think there's always payments that we're not going to receive for certain payers. There is the mix outside of Japan and the U.S. that might have an impact there. But yes, I mean, we would hope that 3,000 is the minimum we can achieve by 2028 and it could be higher. I don't know, AmirAli, if you want to talk about.

Sure. First so in terms of Shield ASP, like the assumption that $500, almost all of it is just the landed ASP just from Medicare and Medicare Advantage claims. So any kind of private coverage policies over time would be additional on top of that. But again, we need to not get away from ourselves too far and just go added 1 by -- step by step. So in that $500, just kind of -- majority is just Medicare and Medicare Advantage at the ADLT pricing, which would be in place sometime in 2025. .

Just a quick second question. I feel like this is the first time I've heard you talk about expanding beyond oncology to other diseases, super interesting, whether it's Alzheimer's or whatnot. Can you share maybe some of the initial disease types that you'd like to go after? And can we expect any of these to be in the market before 2028? .

So yes, I mean I think we built this epigenomics technology and the smart liquid biopsy initially for the purpose of going after cancer, and it's proved to be successful in terms of really achieving much higher sensitivity there. But as you see from Darya's talk and the panel that epigenomics is a much more fundamental tool than just cancer. Cancer is just one of many, many different applications. And so I can tell you that the first stage we'll be exploring a lot of these applications with many of our biopharma partners and other disease types. And they have a lot of interest right now. If you see what's happening with the IRA and so on, it's really shaking up a lot of the pipelines or at least the thinking in terms of what's the next big thing in cancer. We saw with the COVID vaccines really this idea that we can go after much bigger populations now, especially in the large biopharma companies. And so having a technology and a tool, like this is very exciting where cancer has been in a league of its own in terms of really having precision tools, almost every other disease area has been very starved. We've been flying blind, whether it's neurodegenerative trials, autoimmune disease and so on. It's a lot of guess work. And so having a tool like this that can provide sort of analogous precision medicine in those other areas is hugely exciting. And so we're going to be exploring those collaborations with biopharma initially, but because this test is going to be out there, we don't think it's going to be very difficult to commercialize. But the exact road map and exact sequence of what would commercialize first will be dictated by the data and how good it is.

I think what we are doing, we are building the infrastructure to be multi-disease ready in terms of the panels, in terms of claims, in terms of databases. So we just want to make sure that treasure is the right treasurer to go beyond the cancer at the right time.

Patrick Donnelly from Citi. AmirAli, maybe just 1 more on the next-gen Shield data. Can you just talk about, are those the same samples as the PMA? I'm just trying to figure out, is it an enriched sample set? You've said a few times, it's not regulatory grades. I just want to -- if you could give a little more color as to what that means? And then again, obviously, with ECLIPSE, we saw the case control data come out and it slipped a little bit. So just trying to manage expectations here. .

Yes. So these were not like vendor samples, case control, which effectively like -- we needed to make sure malignant polyps, those kind of harder stage Is are well represented. That was the main issue, right? So these are cases for the patients that go through colonoscopy really. So like if there is any kind of polyps getting caught out that in fact after the fact you figure out there was some kind of CRC in them, the blood sample have been collected instead of the blood samples post colonoscopies depleted from those cases. So the data is representative, but like when you want to submit data set to regulatory agencies, there are a bunch of documentations you have to do, clinical study plans, stat plan, we haven't gone through that process. And we need to coordinate with the FDA, but I think the worst case scenario would be like running a bunch of new CRCs. And those new CRCs would be the CRCs that we have collected already in our ECLIPSE trial, which is in our biobank, but we didn't want to touch them and burn them and not use it for regulatory purpose. So these are some [indiscernible] other kind of studies that we've been doing in parallel to get these colonoscopy samples in a proper way, but not for regulatory purpose submissions, but the data would be represented. I doubt it would drift in a very material way. But we'll see.

Okay. That's helpful. And then, Mike, maybe a quick 1 on the guidance. I think you said R&D. I don't know if the Shield, specifically you said, down next year and then maybe stable around that level going forward, is that company-wide? And then just any way to think about the SG&A spend as you guys start to layer in that Shield build out would be helpful. .

Yes, Patrick, what I was referring to was the R&D on the Screening side of the business. So yes, that's been fueled by ECLIPSE and the CRC development over the last few years. So ECLIPSE is winding down. It will be finished by the end of this year. And so yes, in 2024, that R&D spend will were lower. And then we think we can maintain it at a lower level than it is now, over the next few years. On the oncology side of the business, Therapy Selection and MRD. Yes, I think the R&D side is going to be relatively stable expense over the next few years. Again, we pointed out the synergies that we get from smart liquid biopsy. So hopefully, some of those synergies can drop through to the operating expense line.

Guys, Dave Delahunt with Goldman. Thanks for all the extra color. Could you give us a little bit more detail about how you arrived at the 1 million screening test volume estimate for 2028?

Yes, it's actually -- some of it is based on precedent of what happened to Cologuard, but more also the experience that we have at our Shield LDT at this time, in terms of number of accounts that we are the depth of ordering that we are seeing, the time is taking for our salespeople to warm up and ramp up the time that it would take for accounts to get to some almost saturation level of kind of their ordering depth, their ordering physician. We went through those kind of detailed forecasting and the ramp rate that we have in mind in terms of the size of the sales force based on the financial discipline that we want to have. And we feel comfortable that by 2028, we can get to about 1 million samples a year.

Great. And then on the 5-year plan, I really appreciate that extra color and great to see the cash flow breakeven runway. Could you tell us more about what gives you confidence in those gross margin estimates that will help you get there? .

Yes. I mean the gross margins, we're very confident I think over the last few years, we've maintained a gross margin of over 60% with Therapy Selection and MRD combined. And that's even been against the backdrop of launching Reveal with relatively low ASP, and volume is not getting reimbursed. . And if you look at the Therapy Selection and MRD gross margin this year, it's over 60%. In fact, in our overall company -- I don't want to get too complicated, but our overall company gross margin, we do have the dampening impact of the Shield LDT at the moment. So if you strip that out, MRD and Therapy Selection is about 62%, 63% gross margins. And so the way we see the growth going, the way we see the ASPs trending, and I think our ability to manage volume how we want to manage that, we're pretty confident that we can maintain that. And again, we've got a lot of operating leverage that we can really drive from, and we look at bringing down the cost per test over the next few years as well. So yes, we're very confident on that.

Sung Ji Nam, Scotiabank. Just 1 quick question for AmirAli. For the MCED test that you're developing, just kind of curious how big or what kind of scale clinical study, we could anticipate, could you leverage the Shield and the ECLIPSE studies? And also kind of if you can talk about how many cancer types you might be targeting at this point? .

We're learning some insights from ECLIPSE, but the ECLIPSE cohort is not going to be the data that we can used to put it in the guidelines for MCED indications or get FDA kind of labels, but there are definitely a bunch of insights we are getting from a ECLIPSE trial because as I mentioned, these are real-world average risk patients. We did enroll them for CRC, the reality bunch of the lung cancer, breast cancer, like we are finding all these kind of cancers in the patients since we are following up the patients for a year or 2 after colonoscopy. So that insight is helpful. In terms of trials, the size of the study for registration regulatory grade, we need to actually make more progress and see what's going to happen. But what we are seeing in the field is a lot of partnership opportunities, like we and other companies are around the tables, NCI about some of the activities. NCI want to do with like other international bodies that they want to do some population level screening studies in different countries. So we are tapping into a bunch of those partnership opportunities at this time versus ECLIPSE, which was like 100% funded and executed by Guardant. So -- but in terms of like a pivotal study that we get maybe MCED FDA label expansion, that one is TBD. We may never even do that like if there are potential to just put MCED label as a lab-developed test for the current FDA-approved device, we would explore. But we will coordinate all this with agents.

All right. Great. Alex Nowak from Craig-Hallum. 2 questions. The first one is the sales force expansion for Shield. Where are you trying to source these reps from? Are these reps that are coming out of, whether it be pharma, calling on primary care, these reps that have done this before, maybe with Cologuard, just where those unscreened patients sit. And then the second question is, in the first half of the presentation, there was a discussion around we want to create a one-stop shop, oncologists like that. There's demand for blood and also tissue. The market, the oncologist seem to like -- at least some of them like the tissue test for MRD. Why not create an MRD tissue test in addition to Reveal for blood?

Maybe I'll start on the Shield first and help me the rest. So actually, we've done the 1 wave of hiring already in terms of field force at the time that we launched Shield LDT, right? So -- and in fact, the quality of the team has been pretty good. PCP channel, they experienced with heavy PCP. All of them have new product launch experience, award winners. Vast majority of -- a good fraction of them were actually [indiscernible] prior jobs, mainly sourced from companies who had offerings to PCPs. Some of them are therapeutics, but not all of them. So -- but we feel comfortable that we can hire qualified people in short period of time and really train them and warm them up to go to the field about the MRD.

Yes. So I mean people like keyboards and phones, but eventually, that went away, too. More seriously, I would say that look, we didn't start with tissue, we started with liquid, we started with blood. We added tissue to our offering. We're moving that forward with digital pathology and AI, and we're going to continue moving that forward. . We're going to essentially connect our ecosystem and make sure that it provides as much of an informative experience for physicians as possible. And so we're going to let the data be our compass in terms of what we continue to add to our portfolio or not. Right now, we feel our portfolio is fairly complete and answers the information that physicians need and even more so than a lot of the tools out there. But as that changes, of course, we'll continue to adapt, and we'll continue to augment our portfolio so that it truly can become the most desired one-stop shop out there.

It's Derik De Bruin from Bank of America. So AmirAli, I'm curious in terms of how you're looking at that 1 million sample -- the 1 million tests by 2028. Is that coming out of the people that are not screened? Is it coming out of FIT? Is it coming out of colonoscopy or Cologuard? How do we sort of think about that? And what are also your assumptions on the competitive dynamic? I mean there are other companies that are working on liquid biopsy tests and you're not going to be -- in theory, you're not going to be the only player in the market. So what are your sort of assumptions on market share and just that where are these patients coming from that you're sort of thinking at?

Yes, very good question. So when you look at that on screen patient population, 50 million testing every 3 years. Effectively, we're dealing with a 16 million TAM opportunity just in that patient population. So in our models, it's heavy towards converting those on screen patient population, although we believe this lack of preference to stick to stool-based testing, would be some additional opportunity for us. But in those exercises, we are just kind of even focused on that 50 million -- 16 million annual testing opportunity. And conversion of effectively that would be like 6% of that. So in terms of -- what was the second one -- what was the second part of the question?

Basically, it's like what's your competitive...

Competitive assumption, yes. We're counting that this 1-year time advantage would pay dividends for us in terms of raising the bar. Having said that, we are not assuming that we have 100% of blood-based CRC screening penetration in 2028. We are assuming that we would be the market leader, but there would be a piece of the market that's left for any new entrants in the marketplace. That's the way we are modeling it right now. .

Andrew Cooper from Raymond James. Maybe just first, can you give us a sense in terms of the global opportunity when we think about the 20% CAGR in the Therapy Selection and MRD, just what you're baking in for 2028 and how we should think about the pacing there outside the U.S.?

Yes. And I'd say, primarily on the outside the U.S., and it's really focused on Japan and the U.K. on the clinical side of Therapy Selection, and China is on the biopharma side. Yes, I would say it's very heavily weighted in our thoughts and modeling on the therapy selection. We'll be looking to launch Reveal outside of the U.S., and hopefully, that gets some traction. But really, we think the opportunity in the near term is Therapy Selection. And again, I think starting 2024, we'll start to see some meaningful revenue. It's hard to break out exactly in [indiscernible] what that opportunity will be, but it's definitely going to contribute to the top line. It's definitely going to help us achieve that revenue CAGR of greater than 20%. And we think these are big opportunities that we've got ahead of us.

Great. And then just 1 more. Obviously, a lot of things that you talked about that epigenomics can let you do that genomic-only players can't necessarily do an MRD. So when we think about those actually being implemented, can you give us a sense for time lines and what sort of data pacing we should expect for adding, like you mentioned, location of recurrence or metastases and things like that?

Yes. No, I mean, we're -- so that's a good question. We're working on a lot of those applications as we speak. We have sample cohorts to be able to validate them. Exactly when they're going to be released is a little bit dependent on some of the regulatory and reimbursement pathways that exists. So we have to sort of navigate those in the proper fashion. But yes, we're going to ensure that a lot of those features are palpable to physicians as soon as possible. So we think the first crop of those features, perhaps on the 360 side, maybe on the MRD side, would be visible to clinicians in 2024.

For Mike, can you talk about the balance sheet. So you've got $1.2 billion of cash and investments. You've also got the converts. Just based on the targets you laid out, seems like you might need to do another capital raise at some point. Can you just talk about how you plan to manage the capital position of the company through the jury you laid out? .

Yes. No. I mean, hopefully, we laid out how we're going to sort of manage the spend. We know we'll have more than $1 billion in cash at the end of this year. And we plan to spend less than $1 billion over that 5 years and get to breakeven. This is a convertible. Yes, that's due November or matures November 2027. So we've got time to address that. But yes, obviously, at some point in the next 5 years, we're going to need to address that and whether or not we roll that forward or it's all going to depend where we are as a company, where we've seen the traction. And yes, I mean, if we need to -- do we need to raise again, I can't sit here and say, we'll never raise again. I'm not going to sit here and say, we'll raise at a certain specific time. But I think where we are is that with the balance sheet -- the equity raise that we did in May put us in a very strong position. And we feel there's no urgency for us to do anything. We think we've got a really well thought out financial plan. And the balance sheet that we've got can help us manage the business over the next few years. And yes, I mean, the thing has been about rapid revenue growth, and I think the balance sheet that we've got is going to enable us to support that, but we're going to do it in a very disciplined way.

AmirAli, thanks for the follow-up here. In your conversations with USPSTF, have they talked at all about sort of time lines or thresholds for new information, new data? And relatedly, do you think that you feel comfortable about coming in under the wire there with the V2 Shield because presumably inclusion in '26 doesn't necessarily mean starting the process in '26.

Yes. So in terms of formal conversation with task force, no, it's just a voluntary people and -- but we talked about some former members in terms of making sure there is this what used to be completely black box and a lot of, I think, misrepresentation of what happens during that process, it became more transparent to that is a good extent in terms of what really this process is. So that was actually a very useful exercise for us. We expect that some of the data reviews would start in 2024. That's why the window of opportunity for other players are very quickly closing in terms of having any data readout. How that translates for us and we too -- we continue to be confident we want meets the bar and like the modeling the data that I showed, like there were -- if some KOL conversation, even some quotes from a former Scientific Director of USPSTF that she talked about the ECLIPSE data after our presentation, was very promising and exciting for us. So we think V1 as is would meet the criteria, but we are not going to just sit down and just -- we are going to continue with the philosophy of continuous improvement that always we had to continue to raise the bar for other players and continue to be the best in class.

Puneet Souda, Leerink Partners. So I just want to be 100% clear on what is the benchmark for the Shield V2 data that you showed today just getting a couple of questions on that. So I just want to clarify, is that closer to the ECLIPSE data set as -- but that was a pivotal trial? Or is it more closer to the Shield launch, which I believe was 91%, 91% sensitivity, specificity last year. So can you just help us calibrate on that clearly.

Sure. The performance of lung cancer put aside. Both are different indications. Patient population is different. Like it's not a comp for CRC data, right? So the data that we presented that we are kind of excited with in terms of clinical validation for this V2 in this specific cohort that we ran, it's 45 CRCs coming from screening procedures, blood draw before screening, U.S. patient population. And this 45 blended with a bunch of screen negative and advanced adenomas that's happening in the screening world got processed, right? And then we have 2 algorithms, V1 and V2, since assay and data are all the same. So very simple. On that they run the V1 algorithm, which was our PMA device, then run upgraded algorithm, which is V2, same data, V1 detected 84%, V2 detected 91% both of them with specificity of 91%. So I think the value is in this differential performance that there are some missed CRCs with V1 that now V2 can't find, and all of them are early stage CRCs, as we expected. So I hope it clarified.

Yes, so you expect a very limited, if any, degradation there.

Yes. That's -- the degradation conversation. Yes. I think that, hey, the fact that V2 is better than we V1, if you figure out V2 is worse than V1 or similar to V1, like I would say, "Oh my God, like I don't understand biology anymore." So there are many evidence that we have that V2 is better. In terms of like any new study that we do like how much better in this study, we saw 84% to 91%.

Just 1 last one, if I could add. Advanced adenoma wasn't discussed as much. And I just want to get your latest view in terms of the performance that you expect there? Is there a possibility of improving advanced adenoma of pre-cancer detection? And what do you think is going to be the view of PCPs in the sort of multimodal world? .

Yes. So we saw similar performance for advanced in between V1 and V2. Within that category of advanced adenoma, there are different grades. There are some of them, which are much closer to CRC and stuff, but like we can become very scientific about it. But blended the performance was similar in this study that we've done. In general, in terms of like the market requirement, we continue to believe that the most important parameter is CRC detection especially for blood modality that you can count on patients would repeatedly do. In a modality that actually maybe sometimes it becomes 1 and done, 1 and like a bunch of miss and do it again, like detection of these pre-cancer becomes more important. And I think that becomes a reality versus like for us, with the evolution of CRC, how long it takes for different stages even to progress the time -- to all time from adenoma to CRC or sometimes in decades, like CRC is going to kill patients, not adenomas, we continue to believe that. Does Adenoma have no value? No, I cannot claim that. So -- but what's the most important thing is definitely CRC and making sure patients get the test done every 3 years. That's why I'm confident. So I think we are -- they're sending a signal that maybe we should wrap up. Thank you very much for your participation -- active participation, energy. It was great. Hopefully, it was useful for you guys and ladies. And we will be in touch. Have a great day and we have lunch outside. Thanks.