All right. Hey, everyone. Good afternoon. I'm Tejas Savant. I cover life sciences here at Morgan Stanley. Before we kick it off, just some important disclosures. Please see the Morgan Stanley Research Disclosure website at morganstanley.com/researchdisclosures. If you have any questions, please reach out to your Morgan Stanley sales rep. So, it's my pleasure today to host GRAIL, and from the company, we have Bob Ragusa, CEO. So Bob, welcome. Thanks for joining us.
Oh, thank you.
Maybe, just to start, given the recent separation from Illumina and the subsequent strategic review, can you provide a quick overview of GRAIL's mission for folks who are not as familiar with the story? And what are you focused on over the next 12 months?
Yeah. So GRAIL's mission is to detect cancer early when it can be cured. We're really focused on multi-cancer early detection. We've had a product on the market for over three years now called Galleri. And so Galleri can detect many cancers at once, as well as providing a cancer signal of origin. So, you know, from a clinical standpoint, it's a very powerful tool to be able to look broadly across cancers. And if you think about it, our standard of care screening looks, you know, primarily at the cancers that are responsible for 20% of the deaths. Galleri looks not only at those, but importantly, it looks at the other 80% of cancers that cause 80% of the deaths.
And so we think a multi-cancer early detection approach is really the key way of inflecting the cancer morbidity-mortality curve over time, and it has the best impact on public health.
Got it. Maybe on that point, right, so there's a bunch of other players going after screening. You know, most of them are taking a single cancer approach, I think except for Exact, so as you think about, you know, your decision to pursue multi-cancer screening, walk us through how you arrived at that decision. Why not sort of refocus your efforts on single cancer just to go live and then expand into multi-cancer over time?
Yeah. So, you know, from the very beginning, our... You know, GRAIL has taken an approach to really look at multi-cancer. And so, you know, if you step back, the people who have rotated to single cancers, when we look at it, we just don't see a viable process to add single cancer tests together. You know, again, if you look at through the-- where they're going is at the 20% of ca- of deaths-
Mm-hmm
... which is the standard of care screening. So, you know, colorectal has been the big one that they've rotated towards. Most of those single cancer tests focus on really high sensitivity, but also with that comes a penalty of high false positive rates and low positive predictive values. And so if you combine, you know, start adding one, two, three, four, five of those tests, you get to a point where, you know, you have false positive rates that are probably in the 50% range.
Mm-hmm.
So we're looking at, you know, many, many cancers, and so we just don't see a feasible pathway to get to a practical test in the world. So on our side, on the multi-cancer side, we recognized years ago that you could detect cancer from circulating tumor DNA. We did a large, unbiased study to figure out the best way to detect cancer from the blood. And so we looked at, you know, chromosome abnormalities, we looked at mutation, we looked at fragment length, and importantly, we looked at methylation, and found that a targeted methylation panel gave us the highest sensitivity, and importantly, with that, also gave us the ability to have a cancer signal of origin.
If you're detecting many different, potentially many different cancers, you need that cancer signal of origin in order to be a practical diagnostic to, you know, be able to guide the follow-on diagnostic effort. So, you know, with our technology, we feel that we can deliver on the multi-cancer promise. We think that we can look at that, you know, the cancers that cause the 80% in addition to the 20%. Importantly, you know, we think, you know, like a single cancer thing, the most important clinical measures are positive predictive value and yield.
Mm-hmm.
So we've been able to show in our studies that we have a positive predictive value north of 40%, and then the yield is large because you're looking across all of the... or many of the cancers. And so in our PATHFINDER study, where we showed, we showed both that we had a positive predictive value north of 40%-
Mm-hmm
... but we also showed that, combined with standard of care screening, more than doubled the number of cancers found compared to the standard of care screening alone.
Mm-hmm.
So just the sheer amount of cancer we're able to find, we think is what's going to really make a public health impact, and that's a large driver of our focus on multi-cancer versus swinging to single cancer.
Got it. I just want to double-click on that point you just made on PPVs.
Yeah.
Because I do think there's a lot of, like, confusion around it as people sort of compare and contrast across assays.
Yeah.
Why do you think comparing PPVs is the right approach for an MCED test?
Yeah, well, you know, if you think about with a MCED test. So start with a single cancer. So if you look at, like, a Cologuard test, you know, if you do that and you get a positive, you reflex. The reflex is relatively easy. You reflex a colonoscopy, and you can determine very quickly, because you know it's single organ, single reflex test. Second, in multi-cancer, we have 21 cancer signals of origin. And so if you don't have a high hit rate, which is your positive predictive value, if you have a positive, how often is it actually positive?
Mm-hmm.
If that's a relatively low number, you're doing a lot of diagnostic procedures to find, you know, cancers. Whereas with a high positive predictive value, you know, we're almost 50%, it's almost 50/50 in terms of if we say there's a positive there, you're going to find cancer. And so we think, you know, for a multi-cancer test, where you have a lot of modalities, where you might have to go look at, we think a high positive predictive value is critical.
Got it. You know, one of the other, I guess, trade-offs in a sense of multi-cancer screening versus single cancer approaches is, you know, in any single cancer, the single cancer tests generally have better performance than an MCED, right? So there is that trade-off that you're going after multiple cancers at one go. Does that become a challenge to uptake of the test, just given how physicians think and how, you know, guideline bodies might approach MCEDs?
Yeah, so I think, you know, they are very different, and so if you look at, you know, as you said, single cancer tests are focused on high sensitivity, but with that comes-
Mm-hmm
High false positive rates.
Mm-hmm.
You know, with multi-cancer, you know, again, by getting high positive predictive value, high, and high yield, we're able to, you know, generate a lot of diagnostic value within that. And so we think, you know, we think that, you know, driving down a multi-cancer pathway has a lot of value. And, you know, a lot. When you get the sensitivity, you know, one of the amazing things that's remarkable with Galleri, at 99.5% specificity, when looking at the cancers that cause two-thirds of the cancer deaths, we have a 70% stage II sensitivity. And so, you know, it's not like you're trading-
Mm.
really high sensitivity for really
Yeah
Poor sensitivity. You're trading high sensitivity for good sensitivity, but across a broad set of cancers.
Got it. Fair enough. So, I wanna just dig into the reorder rate a little bit. You know, through the first half of this year, more than 250,000 commercial Galleri tests, you know, ordered across about 11,000 healthcare providers. Could you just provide a breakdown of the volume coming through to date in terms of the channel, the healthcare networks, the self-insured employers, you know, life insurance, health payers, et cetera, as well as the reorder rate?
Yeah, I'll give you some sense. So, on the self-pay side, so self-pay for us is primarily clinical.
Mm-hmm.
And we, you know, clinicians, and then we have some patient-initiated telemedicine, and that runs quarter to quarter, about 2/3 to three quarters of the volume.
Mm-hmm.
So the majority of the volume is in that area. And then what we call enterprise, so large self-insured employers, life insurance companies-
Mm-hmm
... some small payers and health systems makes up the, you know, the 25%-33%. From a testing perspective, testing interval, we've done a lot of significant modeling, and all our modeling suggests to date that annual testing is gonna be the right, you know, the right optimal interval. When we get through our NHS Galleri study across 140,000 people in the U.K., we'll get good data on that annual testing to get, you know, more data behind our modeling on that. And then from a reorder rate, we're just starting to collect some of the reorder rate. We've been out there for three years now.
Mm-hmm.
and so we're starting to get some of that data and, you know, not prepared to share, you know, details of it, but we are seeing reorder rates increase, and we do suspect, or, you know, do expect to see differences by channel in the reorder rate as-
Mm
... we go forward. So we probably have more on that to come later.
Got it. PATHFINDER 2, you know, you recently completed enrollment in that sort of 35,000 -patient study, which will be filed along with NHS Galleri for your FDA PMA submission. Could you just remind us of the key objectives for PATHFINDER 2, the primary endpoints, and what we learn at the end of that study?
Sure. So PATHFINDER 2 is focused on performance and safety. And so on the safety side, the test either generates a positive or negative result, and so if it generates a positive result, then we'll look at the number of, the number and types of invasive procedures, and then if it generates a negative result, we'll look at the... what's the adherence to standard of care screening for people who received a negative? That's really on the safety side. On the performance side, we'll look at positive predictive value, negative predictive value, and the sensitivity and specificity of the test. And then, you know, we expect in 2025 , we'll have the readout for that. We'll see the readout on the first, 25,000 people-
Mm
on the safety and performance elements.
Got it. And that's in the second half of 2025, the interim readout?
Yeah.
Okay, got it. On the NHS side, you know, you've completed the final study visits for the 140,000 patients in the NHS Galleri trial. Similar to the question on PATHFINDER, can you just provide an overview of the study design and the key data that we should be watching for in that study? Will you also present any interim data from that study ahead of the final readout in the first half of 2026?
Sure. So the NHS Galleri study is a randomized, controlled, interventional study across a 140,000 people in England. In the study design, it's longitudinal, so there's a baseline draw, followed by one year later, another blood draw, and followed by another year later, a third blood draw. So three blood draws spanning two years with a year follow-up after the last blood draw. As I said, it's a randomized control trial, so in the control arm, we're banking, you know, those samples for further evaluation later on. We'll look at each of the time points later. In the intervention arm, in the Galleri arm, we're, you know, again, looking at if you get a negative in that area, then we'll just have you come back for your next year's blood draw.
If you get a positive, you get referred to the National Health Service rapid diagnostic pathway for evaluation and workup. From a performance metric standpoint, so the key measure there is a clinical utility measure, which is a reduction in stage III and IV cancers in the intervention arm, the Galleri arm, versus the control arm. There's also an element where we're looking at reduction in stage IV cancers, again-
Mm-hmm
... comparing the two arms... and then from a performance standpoint, we're looking at performance and safety. On the performance side, we're looking at positive predictive value, CSO accuracy, and specificity.
Got it.
And then, you know, from a readout standpoint, so, you know, for the main objective of the trial, you really need to go through the entire trial, not just the prevalent round or first round. So, we won't see any of the full readout until the full readout at the end in 2026.
Got it. You know, one of the questions we've gotten recently is just given some of the critiques in the British Medical Journal article and so on, there's just a lot of noise around NHS and their relationship with GRAIL. Has Galleri now become a bit of a political hot potato in the U.K., where irrespective of, you know, how the results from the trial readout, the broader rollout is just, you know, unlikely and complicated?
I think, you know, the NHS has had a long history of being very data-driven. They have incredible rigor. That's. You know, I described the study. It's a large, you know, very large study, high rigor on the endpoints, and so I think that's really what guides them. You know, there's always a lot of noise around it, but I think the rigor of the study and the science is what guides their decision making. Then what's also useful is because they've had that demonstrated rigor, the rest of the world looks to their studies as well. So when we have the end result of that, that data will be useful as we go and talk with other countries around the globe, just because of the reputation of the rigor.
Got it. You, you're also planning to release some data at ESMO next week, I think. So could you just give us a preview of one, what we should expect there?
Sure. There'll be a few things there. So one is we'll show some additional data in our clinical pathway workups. We'll have some health economic modeling that we'll show. And then in the precision oncology space, one of our biopharma partners will present some data in the precision oncology world.
Got it. I want to get to stage shift, right? So one of the ways that screening approaches have shown clinical utility is stage shift, which is, you know, something you're hoping to show in the NHS trial as well. First, where is the field today in terms of accepting stage shift in lieu of long-term survival benefit, which obviously takes longer to demonstrate and then entails costly trials?
Yeah, so I think there's, you know, more and more buy-in. You know, so if you look at mortality versus stage shift, I think there's more and more buy-in, that stage shift is a good proxy for it. Certainly what the NHS is relying on in this, and I think people just recognize the realities of the time duration of mortality studies versus the rate of technological change. So if you wait for a mortality study to finish, the technology has changed over two or three times since then.
Mm-hmm.
And so people are looking for, you know, rigorous, endpoints, but ones that are actually also more timely, and I think stage shift is a reasonable way of doing it.
Got it. So, I guess just, a corollary to that, you know, with just a couple of years of follow-up, do you think the NHS data would be sufficiently mature to see a statistically significant difference between the control arm and the intervention arm? And if you don't achieve that statistic, you know, difference with two to three years of follow-up, are there other endpoints that you could point to that also demonstrate Galleri benefit?
Yeah. So you know, one of the things we think we do have to wait for the full study results. We don't expect to see it in any interim looks at the data, which we're not gonna do because the study is blinded, so we wouldn't be able to do it anyways.
Mm-hmm.
But, we do expect to be able to see it at the end of the study. In either event, whether we see it or not, there is just an enormous wealth of data. We're gonna have 140,000 people, you know, have over three rounds of Galleri. And so, you know, again, when we think about the most important clinical and, you know, clinical measures of positive predictive value and yield, between the NHS Galleri study, between PATHFINDER 2, which will be 35,000 people, we'll have, you know, data, great data on the performance across 175,000 people. So we think that will be a really rich data set.
Got it. Going back to that earlier point you were making, Bob, about, you know, early-stage sensitivity, right? That's been a point of pushback in the KOL community around sort of the MCED approach, you know, the limited ability to detect early-stage cancers. I think even your sort of prostate data that you showed at AACR, I think the number was in the single-digit range, right? And then you compare that to some of these, you know, FDA-approved, blood-based, sort of CRC screening tests. Those are sort of in that 55%-65% range for Stage I disease. So is Galleri's early-stage cancer sensitivity sufficient enough to justify the benefits versus the cost or risks?
Yeah. So there's a couple different things. One, you know, if you use prostate as an example, one of the things that paper is showing is that what you don't want to detect is indolent cancers. And so one of the things that is really good with Galleri and, you know, circulating tumor-based tests is that it... the amount, you know, is related to the aggressiveness, was all the things we're finding. We have a paper published on-
Mm-hmm, mm-hmm
... you know, showing that being as relevant as stage. And so what you don't want to do is detect, you know, cancers that you're gonna die, you know, die with-
Mm-hmm
... rather than from.
Mm-hmm. Mm-hmm.
And so that was, you know, part of that paper. You know, if you look at the goals of single cancer tests, as you said, they're, you know, they're geared towards high sensitivity, but with that, you get high false positive rates.
Mm, mm
... and low positive predictive values. And we contrast that with MCEDs. You know, MCED, it's really important since you're looking for a broad array of cancers in, you know, again, against all the cancers. You want to make sure that, again, your specificity is very high. You know, we have a false positive rate of less than 1%, which is really critical when you think about the public health implications of it. And again, you know, we talked about before, but the positive predictive value, if, you know, when you get-- when you do get a positive in it, you know, when you have a high percentage of those actually be people presenting with cancer. You know, we look at, so we look at it as the positive value and the yield.
Again, you know, when we add our single test, you know, our one test to standard of care screening and PATHFINDER, we more than double the number of cancers found.
Mm-hmm.
So I think that's, you know, from a public health standpoint, that's really the big element.
Got it. You know, going back to the PMA filing, you know, per your discussions with the FDA, what is the benchmark that they're gonna use or the key performance criteria that they will be looking for in PATHFINDER 2 and the NHS Galleri readout to grant approval?
Yeah. So we anticipate being the first MCED to go through the whole PMA process and do the final filing. We're in process of a modular submission. And, you know, because we're the first, you know, the FDA doesn't have any precedent, and they have no external guidance that they're showing-
Mm-hmm
showing right now on MCED requirements. So we've really, you know, with our breakthrough designation, we've been in discussions with the FDA over the past several years, and, you know, we are planning on, you know, submitting the final module with the clinical validation data coming from PATHFINDER 2 and the NHS Galleri. So it'll be, you know, performance, safety, and clinical utility data across 175,000 people.
Got it. Turning to the CMS statute, you know, the Medicare MCED Screening Coverage Act, that's working its way through Congress. If passed, grants the ability for CMS to cover Galleri once you have FDA approval. Can you just provide an update on where that bill is in the review cycle and what the next steps are? How does the whole, you know, election cycle dynamic sort of change that, sort of timeline?
Yeah. So, you know, we're really thankful that a broad coalition of stakeholders brought forth the bill. It has bipartisan, bicameral support. It's one of the few things that really has bipartisan support these days. And, you know, literally everybody, almost every adult has someone, you know, close to them that's been impacted by cancer. That's no different when you get to Congress. And so I think a lot of them, you know, also have a personal sense that-
Mm-hmm
This is an important thing to do, and so, you know, with the recent, you know, lack of progress or lack of productivity of Congress in terms of getting legislation through, it's difficult to predict the exact timing, but the recent markup of the bill in the House Ways and Means Committee got through the markup and then had a unanimous vote, so it's really relatively unusual to have a unanimous vote on-
Mm-hmm
- on pretty much anything. So that's a really encouraging sign, and then we're just... You know, we're hopeful that, you know, the bill will pass before we get FDA approval because that's really the gate that we-
Mm-hmm
We would need it for.
Got it. In case it doesn't, right, given all the sort of logjam that we see in D.C. these days, what happens in that scenario? You know, obviously, you've got the USPSTF pathway following FDA approval. How quickly following FDA approval could, you know, the USPSTF review Galleri? And just as a point of clarification, assuming receipt of, you know, grade A or B from USPSTF, will CMS then automatically issue an NCD?
Yes. So it's a great question, so the USPSTF pathway is relatively unclear from a timing perspective, so it's difficult to comment on the exact timing for that, but upon FDA approval, we would engage with them to, you know, bring Galleri forward and try to get either grade A or grade B determination. With a grade A or grade B, then CMS would have the authority to pay for MCED, you know, for Galleri in that case. It would not, though, convey a national coverage decision. That would be a separate decision that CMS would have to go through.
Got it. The Galleri 2.0 version, could you just provide a progress update on where that launch stands? What drives your confidence that a narrower panel will be non-inferior to the current version?
Yeah, so a few things. So as we look to the next version of Galleri, we've designed from the beginning, this is a population scale screen. And so we recognize that to really hit population scale, we need more scalability as well as lower COGS, and that's, so that's what the next version is really geared on. We've really used a flywheel effect.
Mm-hmm
... of the data that we've generated. So we've generated over 400,000 samples. You know, about a little over half is on the commercial side and about half on the research side. And we use that information to generate this more optimized panel for the next version. You know, so we believe, you know, we've run a large number of samples at this point through the new version, so we still have to show non-inferiority, but we'll be able to. We believe we'll be able to show non-inferiority. And then from a cost perspective, we expect to see a step down in the variable COGS, to look at the variable and fixed COGS. The variable COGS will use less sequencing space, so we expect variable COGS improvement there.
To get the fixed cost leverage, you know, because it's a system probably built for scale, we're gonna have to wait until we get to scalability. So with reimbursement and broader scale, we'll switch to see the COGS, you know, move favorably in that, at that time.
Got it. And Bob, can you just mention how much of COGS improvement you'd hope to see with 2.0 versus the $500 for the current version, and at what scale?
Yeah, so we really haven't gotten into the details. You know, we think it'll be significant. You know, just to give you some sense, to get the scalability, we've nearly fully automated the entire assay.
Mm-hmm.
And so, with that large amount of automation, we do expect, again, with scale, to get to, you know, to get to a good COGS point.
... What about, you know, the bridging studies needed to support PMA approval for the 2.0 version? How big does that trial need to be, and would you likely need an outcomes type of endpoint?
Yeah, so we don't think so. The, you know, so we're running Galleri right now, and the clinical validation for that was CCGA and PATHFINDER. We're also now running PATHFINDER 2 and the NHS Galleri study, but in parallel, we're developing this new version, new version of the test. You know, so we're in discussions with the FDA based on our breakthrough designation, to understand the exact bridging studies. So we're really finalizing what are the key elements of that bridging study.
Mm-hmm. Turning to just the follow-up workup needed in case an MCED has a positive signal. You know, one of the key concerns that KOLs often bring up is the ability for a primary care physician to follow up on a positive result in an appropriate manner, right? In a healthcare system where we are pretty reliant on specialists to confirm you know, cancer diagnosis. How difficult has it been to follow up on the positive cases so far for Galleri? And conversely, how long are physicians following up a positive signal in order to confidently deem them as true positives versus false positives?
Yeah, so, you know, we look at the pathway. So a Galleri test returns either a negative or a positive. If it returns a positive, it also generates a cancer signal of origin, and so that's, you know, very useful in the diagnostic workup. Also, upon a positive, our medical science liaison will reach out to the ordering provider.
Mm-hmm.
And so we have a lot of experienced Galleri ordering providers to this point, so there it's usually, you know, pretty simple. If it's a relatively new Galleri ordering provider, we'll often connect them with more experienced providers that have just been through it. We also provide guidelines for the workup, so we have 21 cancer signals of origin. So we have, you know, kind of standard workups for each of those-
Mm-hmm
... cancer signal of origin. So to date, it really has not, really hasn't been an issue in terms of physicians being able to follow up. And then the timing, it really varies by physician. Some physicians look, you know, kind of do the first test and then we'll call it a false positive. Others will dig deeper. We do offer... In a case where the initial workup doesn't show a cancer, we offer a follow-on free Galleri test-
Mm-hmm
... to be able to do a reconfirmation of that, to help in the diagnostic workup.
I see. Got it. So the NCI has multiple ongoing efforts to answer questions around MCEDs, including, you know, collection of blood samples, to establish a reference standard for all the different tests, that'll come on the market eventually. They're also running a randomized, you know, study called Vanguard, just to look at performance of these assays in head-to-head fashion. Can you just elaborate on the extent of your involvement in those efforts?
Sure. So, you know, first of all, we think the NCI has done a lot of work to progress towards their MCED research goals. You know, we really value the work that they've been doing, and we have a lot of shared goals around, you know, pushing-
Mm-hmm
... the MCED field forward from a research perspective. When you look at the actual studies, you know, we've already done our CCGA study, PATHFINDER. We're well through PATHFINDER 2 and NHS Galleri, and so with that, we've amassed a large database already. That database is, you know, roughly where the NCI will look to get to be in about five years.
Mm-hmm.
So we didn't feel it made sense to participate in the Vanguard study, but going forward, we'll continue to deeply collaborate with them on-
Mm-hmm
... on our shared goals around MCED.
Mm-hmm. Got it. You know, want to spend a little bit of time on the restructuring. Could you just elaborate on the streamlined commercial sales channel? I know you had pretty robust physician support for Galleri. Have you cut back on that service as well?
No. So we, you know, we wanted to make sure as we go through that, there's no patient impact, and so we, we sized the business to make sure that the... You know, it's kind of a ratio of, you know, sales, sales to medical-
Mm-hmm
... science liaisons.
Mm-hmm.
So that piece we didn't touch, 'cause again, the patient side of this has to, and patient experience has to be good with this and the provider experience.
Got it. Walk us through the thought process in scaling back on that employer and life insurance channel.
So we look broadly, you know, really at commercial, our overall commercial footprint. And, you know, over the past several years, you know, being in the market, we've learned a lot of things, what works, what doesn't work, and so we've, you know, just really cut back in the areas that weren't as productive.
Mm-hmm.
And so a lot of those areas are productive, so we're staying engaged in those, but the areas were less productive, so for example, we would, you know, more blanket the U.S.-
Mm-hmm
... and now we're, you know, much more concentrated. So we're not trying to chase after every sale, but trying to go where it's more efficient, especially in the non-reimbursed space, to get sales.
Got it. And then on DAC and MRD, you know, you've decided to substantially scale back on your investments there, but could we see you perhaps, you know, partner with another vendor to commercialize those assays down the road? Particularly in MRD, you know, that is a growing opportunity with a large TAM, and there's broadening support from the payers as well. So why deprioritize it?
Yeah. So we think we have a lot of capability in the MRD space particularly, you know, so in prognosis and, and in MRD itself. And our DAC product, we think, you know, if you look at the SYMPLIFY study, we showed pretty amazing data to be able to really take people who had, you know, actually a suspicion of cancer.
Mm-hmm.
They were symptomatic, and really divide them into people who are very likely to have cancer and people who are very unlikely to have cancer. The work there was really, really strong. When we looked at our business, though, and you look at Galleri compared to all those other elements, you know, Galleri really stands out as the breakthrough opportunity.
Mm-hmm.
And so we wanted to make sure that we had the runway, you know, the financial runway to get us through to some of the key inflection points for Galleri. And based on that, we had to deprioritize, you know, both MRD and DAC.
Got it. Biopharma partnerships, that does remain a priority for investment for you. Can you elaborate on what sort of revenue-generating work you envision doing here?
Yeah. So, you know, if you look last year, we generated roughly $17 million of revenue in the biopharma space.
Mm-hmm.
We're doing work... We've been public with our work with AstraZeneca, so a lot of work with them. We have other biopharma partners, also in the pipeline. And so when we're looking at the prioritization work, you know, those partnerships generate, you know, revenue and gross margin for us.
Mm-hmm.
You know, you know, so we have a level of profitability there, so it made sense to continue on with that work.
Got it. You know, you've talked of having a really rich internal data lake based on your CCGA efforts. Can you elaborate on whether this is multimodal data that is paired with EMRs and outcomes as well?
It depends on the study, but some of the studies have very strong, you know, matched-
Mm-hmm
... matched databases. So you know, we think that's one of the key advantages at GRAIL, is we've generated over the years just a tremendous database of both Galleri results, but also with the matched medical histories, and so we'll continue with that.
Got it. You know, when we met Josh earlier in the summer, you know, he said, you know, the purpose of the data lake is to help with internal test development and improvement. But, you know, there are examples of companies like Tempus, for example, that have looked to license that data, have done so successfully to drive pharma drug discovery. This could potentially also solve your near-term, you know, top-line problem as you bridge to that, you know, PMA outcome and then commercialization. Walk us through the strategic thinking behind that.
Yeah, so we've tried to find, you know, or tried to see how much value we can, you know, can really generate with the data. To date, you know, as Josh mentioned earlier, you know, we've found using our... the data internally has been the highest value generator, and in fact, the next version of the assay is really comes directly-
Mm-hmm
... comes directly from that data work. But over time, we will look and see if there are any opportunities to, you know, utilize the data and be able to monetize data in a responsible way.
Got it. So you're not sort of ruling out the possibility of working with pharma companies in that capacity. Is that fair?
That's fair.
Got it. As you think through, you know, that cash runway, you know, on the restructuring, you talked of extending it out to 2028 at this point. Can you just walk us through the underlying assumptions there?
Yeah, so we always do a long-range plan. We then, you know, update our long-range plan, looking at a number of things, you know, the things we talked about deprioritizing. You know, if you look at a commercial, for example, in the early days, when we're non-reimbursed, that's really an investment.
Mm-hmm.
We recognize and I think we've talked publicly about the fact that, you know, we view that as an investment we can modulate.
Mm-hmm.
And so we did the work to understand how much we could invest, how much sales we could still generate. And the reality is we can still grow well-
Mm-hmm
... you know, with the modulated down commercial sales force, but we just won't be able to grow as fast as we had, you know, kind of originally aspired to. So we looked at that, and then we looked at, you know, things like MRD/DAC, and with the deprioritization of those and taking the funding out for those, we were able to take our runway from, you know, from the 2026 timeframe into 2028, and we thought that was critical to get through, again, some of these key inflection points.
Fair enough. Last question, Bob. What do you think is the most underappreciated aspect of the GRAIL story today?
It's probably just multi-cancer early detection. I mean, just the general concept. I think it's new, it's novel. You know, the medical community, you know, the people who have really, you know, dug in and understood it, I think we have a lot of, you know, we call them cancer enthusiasts. I mean, people who have really been able to dig in and find, you know, finding cancer in their patients. You know, the patients are obviously, you know, have generated many amazing stories in that. But I think, you know, if you think more broadly, it's a new concept and, you know, new concepts take a period of time to really digest-
Mm-hmm
... understand, to go through all the ramifications that we've been talking about today. And, I think the more, you know, knowledge is our friend in this, and so the more people understand what MCED can do, I think the better off we all are.
Got it. That's all we have the time for.
All right.
Thank you so much for joining me.
Thanks.
Appreciate it.
Yeah.