Grail’s Josh Ofman on the Revolution of Cancer Screening
For Episode 103
Harry Glorikian: Hello. I’m Harry Glorikian, and this is The Harry Glorikian Show, where we explore how technology is changing everything we know about healthcare.
For decades now we’ve been getting used to the idea that there are certain cancers that we can and should screen for, with the hope of catching them while they’re still in their early stages. But there aren’t all that many.
For women, it’s standard to get mammograms to screen for breast cancer, and pap smears to screen for cervical cancer. Men can have their PSA level measured to test for prostate cancer. And typically both women and men over the age of 45 should get a colonoscopy every 10 years to check for colon cancer.
On top of all that, if you were ever a smoker, it’s not a bad idea to get a low-dose CT scan to check for lung cancer.
So that’s exactly five cancers that we can screen for somewhat regularly. And the benefit of catching those cancers early is so great—both in terms of survival and in terms of money saved—that most insurers are happy to pay for the screening.
But what if we multiplied those tests by a factor of 10? What if your doctor told you there’s an easy way to screen for 50 separate cancers at once, just by taking some blood?
Would you want to get that test? Would it be worth the trouble to sort through the possible false positives to find the real cancers possibly lurking in your body? And would your health insurance provider want to pay for it all?
Well, those aren’t theoretical questions anymore. Because there’s a certain company called Grail that’s had a so-called multi-cancer early detection test on the market for about a year now.
The test is called Galleri, and it can detect not only breast, colon, prostate, and lung cancer but also a lot of the less common cancers, like those that begin in the bladder, kidney, liver, or small intestine.
Grail is just one of the companies introducing the so-called “liquid biopsy” tests that work by checking blood for free-floating DNA shed by tumors. But the Galleri test is arguably the most sensitive and comprehensive one available right now.
Last month I had the opportunity to speak with the president of Grail, Dr. Josh Ofman. We talked a lot about how the Galleri test works, and how the availability of multi-cancer early detection tests could transform the way we think about cancer.
If we could catch the deadliest cancers earlier—and if we could detect more of the cancers that we don’t even screen for currently before they spread—it could help a staggering number of people live longer, healthier lives.
In fact, Dr. Josh Ofman says that if every American over the age of 50 got the Galleri test every year, about 70% of all cancers could be intercepted at an earlier stage, ultimately averting 100,000 deaths per year.
The FDA granted Josh Ofman’s Grail a breakthrough designation for the Gallery test in 2019. Right now the company is still gathering the evidence about risks and benefits that the FDA will want to see before it grants final approval. Insurers will also want to see that data before they’ll agree to pay for the test. But in the meantime, if you do want the test right now, you can pay for it out of pocket for $949.
Just as a little background on Grail, the giant gene sequencer manufacturer Illumina formed Grail as a spin-off in 2016, and actually bought it back for eight billion dollars in 2021. However, in early December the European Commission reiterated its opposition to that merger, on the grounds that it could reduce competition in the emerging market for early cancer detection tests. It said it wanted Illumina and Grail to unwind the deal. But Illumina will likely seek a stay of that divestment order.
Dr. Josh Ofman and I talked before the EC’s announcement, and we focused on the science rather than the regulatory questions. It was a great conversation. And I think that whatever happens, we’re swiftly moving toward a world where Grail and other makers of blood-based tests will give us a better chance against our old enemy—cancer.
Here’s our full conversation with Josh Ofman, President at Grail.
Harry Glorikian: Josh Ofman, welcome to the show.
Josh Ofman: Thank you very much for having me.
Harry Glorikian: Yeah, this is great. I’ve been looking forward to this discussion for a long time. But, you know, trying to find the right person at the company to talk to. And you, you know, your background is perfect to have this discussion about, you know, what we’re going to talk about, which is, you know, your test, liquid, you know, I guess framed for everybody who’s listening, as a liquid biopsy.
Harry Glorikian: Right.
Harry Glorikian: And so I’ll start with, you know, Grail has a test called Galleri and other liquid biopsy tests that look for signs of cancer in bits of DNA floating in the blood. And they are remarkably powerful. And I’m not sure that’s something anybody would have predicted, say, 15 years ago, although I would tell you that when we were at ABI, we were talking about all sorts of crazy stuff back then and at a high level.
Before we get into the science, can you tell the listeners:
Why is it that sequencing cell-free DNA can be so effective at detecting a wide range of cancers?
Josh Ofman: So it’s been known for decades now that finding signatures in DNA can be incredibly powerful tools to predict the future occurrence of disease, to understand disease as it exists today, whatever disease you have currently, and to understand the biological features of that disease.
Most of the work on DNA has focused on mutations, which are changes to the code of the DNA. But, you know, in depending on what application you’re using it for, that may or may not be a viable way to look at DNA. So over the last decade, people have begun to learn to look at DNA and to study DNA in all of its various ways, looking for mutations, looking at chromosomal changes, looking at fragments of DNA and what that means. And then actually now looking at it at the molecules that attach to DNA and turn the genes on and off, so, regulate the genes in the DNA. And that’s called epigenetics, right?
The molecules that attach to the DNA. And so it’s been, that has been evolving over the last decade. And now with, depending on the application, we know we can find DNA in circulation. And once those two things came together, we can find DNA in circulation, and we have all these tools now to measure different aspects of the DNA, we can do much better.
The term liquid biopsy, for example, turns out that word comes from in people already diagnosed with cancer. Right. And we look in their blood instead of looking in their tumor, to find the molecular signatures of their cancer. We’ve now extended that idea. So liquid biopsy may or may not be the right term because we’re using it at Grail for early cancer detection, asymptomatic cancer detection.
And but the technical challenge from going from “You already have cancer” to “You have hugely strong signals of cancer in your body that are pretty easy for us to read to finding very subtle signals and cues in the blood of somebody who is asymptomatic and has no idea they have cancer,” that’s a very different technical challenge.
Harry Glorikian: Right. So just to step back and sort of like do some foundational stuff, I’d love to spend a little bit of time on sort of the biology and computational science behind the actual Galleri test. I mean, if we could even go back a little bit to, you know, when and how did scientists figure out that tumors shed DNA and can be detected in the blood?
I mean, I believe, you know, can you tell the story of how researchers sort of accidentally discovered cancer signals in cell-free DNA in the blood of pregnant mothers? And I remember this happening, you know, when it happened, we were talking about it behind the scenes of, oh, shit, Like, do we actually, we found something. Do we actually tell the mom because it’s not what we were originally looking for?
Josh Ofman: Right. So it’s a great question. So it gets back to the origin story of Grail. And I’ll tell you that in a minute. But even before that, I think, I think it was in, you know, somewhere between year 2000 and the year 2014 that the tools became more widely available to begin to to look at, you know, once the Human Genome Project was completed, obviously that set the whole field, you know, afire in that direction.
But somewhere in the mid 2000s, you know, people started looking at DNA in circulation, but not really with any application in mind. So Illumina is the world’s largest gene sequencing company, DNA sequencing company. And within Illumina, in about 2014, they began a big study in healthy pregnant women.
And the idea there was instead of doing amniocentesis, where you introduce a large bore needle into the abdomen to withdraw amniotic fluid, to look for the chromosomes of the fetus—because that carries risk to the fetus—Illumina investigators thought we can probably look in the mother’s blood for those same chromosomal DNA from the fetus because you’re exchanging blood between the mother and the fetus through the placenta.
Josh Ofman: And in this study of 125,000 women, Dr. Rick Klausner, who was the ex head of the NCI and the chief medical officer at Illumina, was brought 10 cases of women’s DNA that the lab director, who was a woman who later ended up working at Grail, brought those samples to Dr. Klausner and said, “You know what, these look really abnormal.” And sure enough, all 10 of those women had an occult cancer that they had no idea they had. And Dr. Klausner took one look at that DNA and said, “You only see DNA like this in cancer.”
So that’s when the light bulbs went off within Illumina that they may have discovered serendipitously this way of detecting cancer by looking at circulating DNA and seeing these very common patterns of DNA. And they spun out Grail as a private company. We raised a lot of money and we did a lot of research to try to develop the assay, validate the assay, and has embarked on probably the largest human genomics program that at least that I’m aware of.
Harry Glorikian: So now you guys in 2020, published in the Annals of Oncology, the circulating Cell Free Genome Atlas Study and the Grail scientists collected more than 15,000 people and sequenced the cell free DNA in blood, paying attention to more than I think it was 100,000 informative methylation regions. I mean, can you help people understand, well what a methylation region is and why it’s important?
Josh Ofman: So we knew from lots of published, there are many databases of cancer and lots of research that has been done, so we know, we knew broadly which regions of the genome were most informative for cancer and are most involved. And then the methylation patterns. So you can sequence the DNA to get the code of the DNA, but you can also do a different form of sequencing, we call it bisulfite sequencing, which reveals the pattern of the methyl groups attached to the DNA.
And Grail, to its great credit, didn’t just presume that it knew the answer about how to do this. They did an unbiased experiment and they said, okay, if we’re going to look at all of these cancer people and non cancer people for signatures of cancer in their DNA in circulation, let’s ask an open, unbiased question: What’s the best way to look at the DNA? Should we be looking at mutations? Should we be looking at chromosomal abnormalities?
Should we be looking at fragment lengths? Or should we be looking at these methylation patterns and recognizing the patterns? So they did a, they developed a bunch of machine learning classifiers and they compared all these approaches head to head.
And what they found was, without question, and this has now been widely published and is well known, that looking at this methylation pattern was by far and away the best way to find cancer signals, because there’s a shared cancer signal that many cancers share.
Because the regulatory genes, the tumor suppressor genes and the tumor promoter genes, are modified in cancer. Tumor suppressor genes are turned off, tumor promoter genes are turned on, across all kinds of cancers. So you see these very common patterns of hypermethylation and hypomethylation around these genes.
And if you look in the informative regions of the genome, so Grail’s assay looks at 100,000 genomic regions. We look at 1 million of these little methylation sites, and then we show this pattern to a machine learning classifier which has been trained on thousands and thousands and thousands of these cancers and non-cancers and can discriminate a cancer signal from a non-cancer signal.
And if it sees a cancer signal, then it goes through a second step and it goes through another machine learning classifier to predict where in the body that signal comes from. And that’s the other reason why methylation is so powerful, because it holds two signatures. One that’s a cancer signal. The other signature or fingerprint is from what cell type does this come? From what part of the body—is it pancreas? Is it liver? Is it ovary? Is it stomach?
Harry Glorikian: So. I’m glad you you talked about the machine learning because part of the show is like where the where these two things intersect and how it’s really helping us drive things forward. I mean. Why do you need machine learning to detect and identify the methylation patterns? I mean, I’m almost willing to say like, you almost couldn’t do what you’re doing without this technique. But you know, I’ll let you comment on that.
Josh Ofman: Well, it’s a great question, but we we’re having this conversation today about Galleri, Grail’s multi cancer early detection test, because of the scientific developments and convergence in human genomics and in artificial intelligence and machine learning.
So the computational biology elements. Grail was founded, you know, with a bunch of genomics experts, geneticists, computational biologists, machine learning experts, public health physicians, clinical researchers. And we brought all these disciplines together to figure out the best way to detect these signals.
And once we recognized that we were going to be using features of DNA, right, when you look at different features and you weigh those features using different regression equations, then you want to be, then you begin to realize this is a classification exercise. That we’re trying to classify a signal as representing a cancer signal or a non cancer signal.
That’s exactly where machine learning can be really powerful because you can put a lot of featurized information into these algorithms and it can get better over time. So the more we train our algorithm with more data, with more cases, the better it’s going to get. Let me give you an example.
For example, we find this shared signal, we are able to find cancers that we’ve never trained our algorithm on. Because that signal is shared across many, many different cancers. But the algorithms also vary because methylation markers are very sensitive markers of cell type. It can also predict, even if it’s a cancer, it’s never been trained on what tissue it came from. So we’re already finding cancers that we’ve never trained.
And we did experiments where we purposely didn’t train it on lung cancer and it found all the lung cancer samples, for example. So that’s where training machine learning algorithms—if done right, you need models that are not over fit, you need you need to have a lot of very careful research protocols to do this correctly—But when done well, machine learning algorithms can be incredibly powerful classification tools.
Harry Glorikian: So now you guys, you know, got granted FDA breakthrough designation for this test in 2019. And doctors can order that test for patients who are, say, elevated for risk of cancer or have maybe a family history. Do you see like as the real target is is that the real target for Galleri, because I envision this or maybe you envision this as, as you said earlier, an early preventative test, best administered, you know, before there’s any suspicion of cancer.
Because my wife says to me, if we’re going to spend any money, we should spend it on something like this so that we can be ahead of the curve.
Josh Ofman: Well, that’s exactly. Well, let’s take a step back for a minute. So what are we, why are we even here? Right. I mean, Grail exists because we are having an epidemic, a COVID size epidemic in cancer every year where cancer is about to become the number one cause of death in men and women worldwide.
We’re losing 600,000 of our loved ones every year, 1700 to 2000 a day. And why is that? It’s because we’re finding most cancers too late, right, when they’ve already spread. Treatment options are not very effective or and sometimes not even available. So the big idea here is that if you find cancer while it’s localized, nine out of ten people are going to live five years or longer. Unfortunately, that doesn’t happen very often.
When you find cancer when it’s already spread, two out of ten people will live five years or longer. So huge differences in survival. Now we have some screening tests. We screen for five individual cancers, right? You know, if you’re a man, you might be able to get a colon cancer screen, a prostate cancer screen, and if you’re a smoker, a lung cancer screen, that’s three for men.
And women similarly, they get, you know, cervical cancer screening, breast cancer and colon. And then if they’re a smoker, a fourth, lung. So we have three or four cancers that we’re looking for. But all the deaths are occurring from cancers that we are not looking for at all. In fact, 70 to 80% of the deaths from cancer are in other cancers.
So when I went to get my colonoscopy, I felt pretty good about myself—I happen to be a gastroenterologist—that I’m taking care of my health. What I forgot is that in that moment, in that year, I was ten times more likely to be diagnosed with some other cancer that I’m not even looking for.
Harry Glorikian: Right.
Josh Ofman: So we have this huge opportunity now to change the paradigm about how we think about cancer detection. Right now, the paradigm is I’m looking for individual cancers and the new paradigm, by adding Galleri to the standard of care screening, we’re not replacing them.
We are a complement. But the new paradigm is to also look at individuals. I want to look at you and say, What cancer might you have? Not, do you have colon cancer? That’s a big change. And by doing that, we think we can dramatically improve the cancer detection rate in the population.
Harry Glorikian: Yeah, I mean, listen, my mom died of pancreatic cancer, so by the time we found it, right, it was, you know, way down the line. And it would have been nice to find it much earlier and maybe be able to do more about it. But. You know, to decide whether a test like Galleri should be adopted, say, at a population level, screening, I’m sure that regulators want to know a lot about sensitivity, false positives.
So if we can talk about that a little bit. Your the paper that you guys published in 2020 mentioned, you know, Grail scientists found that the gallery has a sensitivity of 67% for a subgroup of common cancers at stage one to stage three. And it was a whole number of them, right? Anus, bladder, colon, etc.
The sensitivity rate was lower for early stage cancer. So help people understand how do you interpret these sensitivity rates? You know, does 67% sensitivity rate translate to 33% false negative rate? And, you know, I’m sure that it’s improved since since the paper in 2020. So those numbers may be, you know, continually being, you know, upped.
Josh Ofman: I mean, the performance, it’s important to put the performance in perspective about where we are today. And so here’s what most people don’t know, is that for an individual, we know what the false positive rate is for mammography. We know what it is for Cologuard. We know what it is for cervical cancer screening or PSA.
But what nobody ever talks about is for for you, Harry, what’s your false positive rate for screening for three cancers? Adding the false positive rates up. So a woman who gets cervical cancer screening, lets say stool based colon cancer screening, mammography and low dose CT because she happens to be a smoker, her false positive rate—that means we know she doesn’t have cancer yet—these tests are going to tell her she does, it’s over 40%.
So that’s where we are today. So let’s anchor there for a minute. Now let’s look at Galleri’s false positives. Galleri, with a single blood draw, can look for all these cancers, 50 or more of them all at one time with a false positive rate of 0.5%. Okay? Now, those numbers are perplexing to you because you’ve never heard them before because nobody is doing the math. What people are doing is they’re telling you, oh, mammograms have a 11% false positive rate.
Low dose CT has a 13% false positive rate. But you need to add them up because they’re all being added up in you. That’s the the power of a multi cancer early detection test. We can have a single false positive rate on that cancer signal.
Josh Ofman: Now, the way we’re measuring cancer is by looking at DNA and circulation, and not all cancers shed DNA into the blood. So when you talk about the average sensitivity across all these cancers, we’re including cancers that we know we’re never going to detect because they don’t shed much DNA into the blood.
So the average sensitivity is a difficult number to understand. You want to look at each cancer type’s sensitivity because invasive, rapidly growing cancers, solid tumors shed a lot of DNA into the blood and we’re able to measure them. So if you look at our sensitivity for pancreas or ovarian or liver, you know, gastric, colon, invasive cancers, we have very high sensitivity. We find them very well. But we do that at a very low false positive rate.
So you need to compare, whenever you compare sensitivity, you need to make sure you’re doing it at the same specificity. And and no other cancer screening test can come close to the specificity that we have with Galleri. So we knew for a multi cancer test we had to bring it to the market with very few false positives, right?
And we knew over time we would be able to improve our sensitivity for individual cancers. The nice part, because you’re you’re bringing up the harms of cancer screening, one of them is false positives. And I’ve just told you how how we manage that harm by keeping the false positive rate very, very low.
The other harm of screening is what we call overdiagnosis is, Oh, well, maybe you’re just finding all these cancers that don’t matter, that people are going to die with, rather than die from. And the good news for Grail was that those slow growing cancers, like encapsulated prostate cancers or slow growing indolent thyroid cancers that people are worried about, even slow growing hormone positive breast, those cancers are slow growing.
They do not shed a lot of DNA into the blood. And therefore, we very rarely detect them. So it’s unlikely we’re going to contribute to this problem of overdiagnosis that people are worried about. So that’s how we manage the harms. And then in terms of the performance on sensitivity, you have to remember that most of the current sensitivity for most of these cancers is zero because we’re not screening for any of them, right?
So even if we find 30% of them or 40% of them, it’s an enormous improvement from where we are today. So we’ve just got to anchor ourselves in what is the performance that we’re getting today? And compare that to what the performance is could be if you add a Galleri to today’s standard of care. And there’s no comparison. It’s a much better, more efficient world.
And maybe there’s a number that can illustrate that. Current standard of care screening, for example, finds about 15% of the cancers in an elevated risk population of adults over the age of 50. That’s not enough. That’s good. Those these single cancer screening tests save lives that are wonderful.
But finding 15% of the cancers that’s not going to bend the cancer mortality curve. If you add a Galleri to that and this has all been published with models, if you added Galleri to that we could find 50% of the cancers in that population. And if you asked a better question, which is how many of the deadliest cancers could you find? It gets up to three quarters. So that’s just an enormous population impact of cancer detection at presumably earlier stages.
Harry Glorikian: Oh, yeah. I mean, I remember as we were developing or talking about other diagnostics for screening and every time somebody would bring up, Oh, we got to do a screening test, it always like gave me like just trying to get over that hurdle is, is, you know, a daunting hurdle.
Josh Ofman: Because Harry, we’re never going to we will not single-cancer-screen our way out of this problem.
Harry Glorikian: No, absolutely not.
Josh Ofman: Adding three or four or five more single cancer screening tests means your individual false positive rate will be well over 70%. It will never be cost effective. So the nice thing about Galleri is it’s highly cost effective as a screening test.
You don’t have to add ten or 15 or 20 individual tests together, which is very inefficient because of the high false positive rates that you have to add up. So even today’s current standard of care screening to find one cancer, you find about 41 false positives. It’s very inefficient. If you add a Galleri you can get that down to about 1 to 15.
Harry Glorikian: So. How sensitive does a blood based cancer screening test need to be before the FDA will clear it for that early screening, and/or Medicare will pay for it, in your opinion?
Josh Ofman: We don’t know the answer to that specific question. The question let me reframe it, which is the regulator, the FDA, will assess the benefit-risk profile of the test. And the benefits will be all the early cancer detection, all the asymptomatic cancer detection, because there are two benefits, right? One is finding cancer in an asymptomatic state at any stage is better than finding it when they’re symptomatic. Right. They’re going to have more time.
They’re going to have a better diagnosis, likely be at an earlier stage, and they have more time for planning their life and planning their treatment and more treatment options. And quality of life obviously can be better. The second benefit is if you actually get it at an earlier stage, right, because then you you know that earlier stage has more curative potential. Curative intent. Often can be treated and cured surgically in their early stages.
So they’ll look at all the benefits, you know, and then they’ll look at all the potential harms and they’ll do an assessment. I don’t think their approval will be, as you said, it’ll be if you don’t hit this level of sensitivity. It’s not because again, the sensitivity is wildly different depending on is this tumor a shedder of DNA.
Is that tumor not a shedder of DNA. Averaging across all these tumors? Some people think that makes sense, others don’t. So it’s it’ll be a much broader review. For Medicare, it’ll be about really demonstrating in the Medicare population, again, the benefits of a multi cancer early detection test, the cost effectiveness of a multi cancer early detection test relative to to any harms.
Harry Glorikian: So you’re sort of going right into the next the next question, because I can tell you all my doctor friends, like when I bring up something new or you know, I’ve been reading the papers, they all ask the same question. And it was a, there was an actual quote and stat from Sana Raoof, who’s a physician at, you know, MSKCC, Memorial Sloan Kettering Cancer Center. And he said, you know, “We’re not waiting for these tests to get better. We’re just waiting for trials to show when you put them in the hands of a physician, outcomes get better.”
So if we could talk about that a little bit is in addition to the study that, you know, around accuracy, are you guys also studying long term outcomes? How close are you to being able to prove that the test moves the needle? And I don’t know if you could take a guess. Maybe you guys have modeled this, but how many lives would be saved each year if, you know, Galleri were used at a population level?
Josh Ofman: Well, it’s a great question. So I’ve read a lot of Dr. Raoof’s work as well. And she she’s a wonderful scientist and clinician and speaks very wisely about many of these issues. And so I think, you know, what what Grail has done is embarked on what is one of the largest clinical genomics programs ever undertaken.
So we began with what we call case control studies, which you referred to the Circulating Cell Free Genome Atlas, which is we know we have 10,000 people that we know have cancer at all kinds of different stages. We have 5,000 people we know don’t have cancer. Let’s develop an assay that can discriminate the cancer signals, validate that assay with independent training sets. And we did that three times and that helped us develop our assay.
But then to your point, you want to actually put that assay into practice in the real world. And we just reported out and are submitting for publication the Pathfinder study, which was an interventional study of 6,600 individuals in the United States across seven different health care centers, Mayo Clinic, Cleveland Clinic, and go down the list. But these were asymptomatic 50 year olds who wanted multi cancer early detection screening. Doctors were left to work up the cancer signal, as they would in usual clinical practice. And we followed everybody for a year.
Josh Ofman: And this turned out to be a very heavily screened population, right? Healthy volunteer bias is very common, mostly white, highly educated people. We’re trying to address that in our next round of studies. But that’s the population. Turns out at the end of one year, adding Galleri to standard of care screening more than doubled the number of cancers we found in the population. Which was stunning to us because we knew this was a heavily screened population and a very healthy population. So we were worried we might not find much cancer.
And amazingly, 70% of the cancers we found have no recommended screening tests, and half of the solid tumors were in stage one and two. So remarkable findings. Interestingly, the time to diagnostic resolution, which is the the time to work it up and for those who had cancer, was like two months.
And this was during the middle of COVID. And for those who had false positives, those got resolved somewhere between three and six months, which is very common. If you look at the literature about how long does it take somebody with symptoms to get diagnosed with cancer or resolve, it’s about six months.
So very consistent with the published literature and the satisfaction rates from the patients were very high, highly satisfied with the test, whether they had a true positive or a false positive. Anxiety levels were very reasonable. They were like what we’ve seen in every other screening test. And then there were no adverse events, not one from the diagnostic evaluations.
So that’s the interventional study. But the big study is a randomized clinical trial we’re doing in the UK’s National Health Service, 140,000 healthy adults over the age of 50 with no suspicion of cancer, are randomized to standard of care screening versus Galleri plus standard of care screening. And they’re going to get three rounds of testing. So in this study, we’re going to be able to find out, again, test performance like in Pathfinder.
How easy was it for doctors to find the cancer diagnostic workup, the costs associated with managing all these cases, the total cancer detection rate. But we’re going to be able to compare in the intervention arm with Galleri. Did we find earlier stage cancer? The goal in the UK is to reduce the proportion of cancers that are diagnosed in their late stages. Right?
And so we’ll be able to say, did Galleri do that? Were we able to stage shift cancer where we absolutely reduced the absolute number of cancers diagnosed in stage four and then in stage four and stage three?
Harry Glorikian: And when are we expecting that to be done?
Josh Ofman: Those data will probably read out, the first year has been completed, everybody is in their second year of enrollment now. Interestingly, this study was so popular, we enrolled 140,000 people in ten and a half months, which is unheard of. You know, a couple of thousand people study in the United States could take two years to enroll. Right.
So it was remarkable to watch. They sent vans all up and down the countryside. It was really incredible. But the first, they’re in their second year of enrollment. So we will get the 12, the first year’s data read out sometime by the middle of next year, I believe. And then the full study will read out in about two and one half years.
Harry Glorikian: We’ll be we’ll be waiting for that. I think I know what the answer is going to be, but let’s not let’s not taint the results.
Josh Ofman: But and in that population, in that population, it’s a much more ethnically diverse population, racially diverse and socioeconomically deprived. So we will expect I’m expecting our performance to even be better than what we saw in the United States with a very healthy, heavily screened population.
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Harry Glorikian: So you brought up economics in that statement. And so you and I both know that it’s often economics as as much as science that determines whether a new diagnostic test gets widely adopted. So I’d love to talk about, you know, the costs and reimbursement. I saw the list price is about $949 on the website. So how does that compare to the cost of existing cancer screening tests?
Josh Ofman: Well, the way to think about the cost here—so, right now we’re a lab developed test, an LDT, CAP, CLIA certified, New York State Department of Health certified test. And it’s available in the market. It’s been in the market for about a year. We’ve now done well over 50,000 tests.
And it’s very reassuring to see in the real world that we’re finding early cancers, you know, of the bad kind we found early pancreas, early gastric, early liver, you know, so the test is is mirroring in the real world what we’ve seen in our studies. But our test is costly right now because we’re sequencing a huge amount of the genomic material. We’re sequencing over 100,000 regions and a million of these sites, but we have a line of sight to get those costs down.
So it’s a self-pay test right now. Now, some large self-insured employers, we have dozens and dozens of companies that are paying for the test. We have some payers that are providing coverage. So we have a Medicare Advantage plan, there’s a large commercial plan in the Northeast that’s paying for the test.
And then the rest of it is self pay. People pay out of pocket. And the retail price if you just walk off the street is about $949. There are discounts on that to some large purchasers, obviously. And but we have line of sight to getting that price down because we know we need to.
Josh Ofman: If you think about other genomic tests, other liquid biopsies, which is the best comparison in someone diagnosed with cancer, those tests cost thousands of dollars. Right? They can be $3000. They can be $6000 to try to do some genomic work on your tumor or in the blood in a patient with cancer.
So relative to those, our costs are very are low. But if you compare ours to an image, to a mammogram, for example, or something like that, it’s going to be more expensive than that. Colonoscopies, those cost quite a lot of money. As you know, low dose CTs cost quite a lot of money. So from a from an absolute cost perspective, it’s in the range, but we know the costs are going to come down. We’re going to we’re going to find, the next version of our test will sequence less DNA.
We’ll be able to get all the costs down because we know that’s necessary for population screening. But from a value perspective, even at this price, $949, it is a high value medical intervention, meaning it’s very cost effective. In other words, the health that you’re buying is well worth the dollars that you’re spending in traditional economic terms. So we are as cost effective as the single cancer screening tests, yet we can find over 50 different kinds of cancer.
Harry Glorikian: So there was I mean, I keep thinking about this. I mean, I think about the economic impact, the financial impact that, you know, there are so many reasons to test early and not find something later, although I’m sure that most pharmaceutical companies will not be happy about finding something earlier as opposed to later. It’s sort of affects their financial model, you know, negatively.
Josh Ofman: But let me let me jump in on that, because I actually you know, I think we can think more broadly about that. We are, you know, most biopharmaceutical companies have technology that’s very effective against certain cancers. But they begin by using those in late stages. That’s just the regulatory approach.
But they well recognize that the real value of those medicines might be to use them in earlier stage disease as neoadjuvant or adjuvant treatments, where you can really improve outcomes. So they’re very excited actually about Grail, and we’re working with many of them in partnership because we’re also developing our assay for people with diagnosed cancer so that we can look at prognosis, minimal residual disease, early recurrence monitoring.
But even in the early detection space, they would love to find more early lung cancer, more early colon, more early gastric, more early pancreatic because they’ve got agents they would like to study in those early stages.
Harry Glorikian: Yeah. So. You know, when I think about this, right, there was a bipartisan bill before the 117th Congress in 2021 called the Medicare Multi Cancer Early Detection Screening Coverage Act. They’ve got to come up with shorter, shorter names for this stuff. But it it would have required Medicare to cover annual liquid biopsy screening for cancer. And that bill hasn’t passed. And I’ve heard that it’s unlikely to pass. But do you think it’s this kind of legislation that’s needed to get multi cancer early detection technology off the ground?
Josh Ofman: Well, let’s remember what what Medicare statute is. Medicare by statute is not allowed to pay for any preventive services like screening. The only reason Medicare pays for pap smears and PSA tests and colonoscopies is because special laws were passed to give Medicare that authority.
So when when I joined Grail about three and a half years ago, there was a group of stakeholders in Washington who were already thinking about, given the advent of these technologies, how are we going to give Medicare the authority to provide coverage for these technologies, so that our Medicare beneficiaries are most at risk for cancer because of their age? And so these are some of our most vulnerable populations in the United States.
And for them not to have access to this cutting edge technology makes no sense at all. So I think the stakeholders began thinking about how to introduce legislation. And now it’s been introduced. It’s got very strong bipartisan, bicameral support. It may get passed at the end of the year. We don’t know.
But there are a lot of really important stakeholders, including congressional members, bill sponsors, who are really advocating for it. And all that does is give Medicare the authority to pay for it should they choose to. It’ll have to be FDA-approved, obviously, but that is what’s going to have to happen. We’re going to have to get Medicare, the authority to pay for these types of tests in a screening context if you really want widespread benefits to the population.
Josh Ofman: And we’re talking about an enormous public health benefit. You asked how many lives could be saved. Our models show that if you take a population of the age over 50, forget about all the other elevated risk populations just age over 50, and you found all the people who were going to die of cancer in the next five years. And you said what would happen if you introduced Galleri, in addition to standard of care screening?
Turns out you could intercept about 70% of those cancers at an earlier stage, and if you did that, you could avert about 39% of the expected deaths over the next five years. That equates to about 100,000 deaths averted every year. Which is about the magnitude of benefit delivered by everything we’re doing in cancer today.
So if you read the American Cancer Society papers about everything we’re doing in cancer, the ROI basically of cancer, everything we’re doing, it’s about averting 100,000 deaths a year. And we’ve estimated that if Galleri were used broadly in everybody who could take it in the adults over 50, we could have about that size impact, which is really remarkable. But it gives you a sense of the possibility.
Harry Glorikian: So, I guess, two questions. One is there are other companies working on liquid biopsy. I mean, when I look at the chart, it’s like littered with little dots. You know, one question is, what makes Galleri unique, in one sense. And the other part is, is you are taking this sample. I think you’re working on other tests for other diseases. And I don’t know if you can talk at a high level about the products in the pipeline.
Josh Ofman: Sure. So in terms of test development, obviously there’s a huge number of companies who are already doing liquid biopsies and many of them, Exact Sciences, Guardant, Freenome, are also talking about moving earlier into multi cancer early detection. Now, they all have their their approaches.
Most of the traditional approaches have focused on mutations. And we’ve shown that when you when you have a methylation based approach like ours, adding mutations doesn’t improve its performance. You and I carry some of the same mutations cancer patients carry, but we don’t have cancer and mutations are very uncommon, so it’s not a good way to find cancer. So there are other companies working on multi-omics approaches, which is very tricky.
We’ve been looking at that. We found what was unique about Grail is finding this methylation signature that is shared across so many different cancers. A lot of these tests will end up being a sequence of single cancer screening tests in one blood test, but that will never pan out because you’ll have to add up the false positive rates of all of those single cancer.
So if I have two proteins that measure breast cancer, four proteins that measure ovarian, two RNA things that measure colon, I’m making this up, and put them all into a single test, they’re all going to show up as a very low specificity. Because you’re going to have to combine all their false positive rates.
So our test doesn’t do any of that. Our test looks at a very this shared signal and has a single specificity. So right now, that is a hugely differentiating feature of Galleri, compared to any other tests that I’m aware of. And we have a lot we have very strong IP around all of that as well. So that’s the advantage that Galleri has right now, that we’re looking at this shared signal. We’re not going in trying to find a handful of very specific cancers.
That’s not how our test works at all, but that’s how many of the other tests, you know, these other companies are saying we now know how to do a blood based colon cancer screening test. And they’re extrapolating to say, now I can do a blood based multi cancer test. And maybe that’s true, but that’s a very different, different technological challenge that those companies are going to have to grapple with.
And I’ve not seen I’ve not seen another validated assay yet that’s convinced me that any of these other companies have an assay that’s that can perform anywhere near Galleri.
Harry Glorikian: Yeah. And part of that is, I mean, you know, how do you get through the regulatory how do you get reimbursed? How do you I mean, the system is designed for a different approach, right? So your your approach had to be very different and very well funded to get to that goal.
You know, I had illumina’s Chief Medical Officer Phil Febbo on the show just a few weeks ago, and we spent a lot of time talking about Illumina’s latest fastest gene sequencing machine, the NovaSeq X. How does the available of that new introduction of technology affect your work at Grail?
Josh Ofman: Well, I think it will, I think there’s huge amount of potential with the new technology coming out of Illumina. Obviously, all anybody who’s using current Illumina machines and relies on Illumina’s technology is going to try to use its latest and best technology that can drive down costs.
It can improve efficiency and improve the quality of the work. It’s really remarkable what they’ve been able to develop. So, you know, I’m not ready to speak about our transition plans or anything like that, but obviously most genomics companies are going to, I believe, going to going to be making those transitions to the new machines.
Harry Glorikian: And I want to jump back to one of the questions I threw out there earlier, but. Can you talk a little bit about some of the other tests you might be developing using this technology?
Josh Ofman: Yeah. So we have this this completely innovative platform of looking at circulating DNA and evaluating it, using these methylation features and signatures. And we know that there’s a lot of information in that. For example, what we know about cancer and its prognosis really has to do with stage, right? What stage is the cancer?
But we know staging is pretty crude. It’s most often based on images and shadows and, you know, sometimes intra-operatively feeling the cancer, you know, is it spread regionally? Is it confined? So there’s also some scoring criteria for staging. So, you know, you look at the lymph nodes, all that.
So we stage cancers, but we’ve learned by studying circulating tumor DNA that the amount of DNA in circulation is as prognostic as stage. Think about that for a minute. That whether a tumor is shedding a lot of DNA into blood is a very important prognostic sign for that cancer.
We’ve shown we’ve published now that if you look at the survival curves of cancers that shed a lot of DNA versus those that don’t at every stage, the ones that shed DNA look awfully like the average cancer in the SEER cancer registry, just cancers with a big unmet medical need.
But there are cancers in stage four, cancers in stage three that are not shedding a lot of DNA. And guess what? Their survival curves look way better than anything you would ever expect. So we now know that whether tumors are shedding DNA is very related to their aggressiveness and their invasiveness. Right.
So we now are also developing a new test for people with diagnosed cancer, where we can use our methylation based sequencing approach and signal detection approach and tumor fraction determination—ow much of the of the circulating DNA is from the tumor—to do prognostic work?
To look at minimal residual disease and to look at early recurrence monitoring. So we have another product that’s going to come out in the post diagnostic setting. We have a third product we’re working on for people with symptoms suggestive of cancer. Which is more of a diagnostic test rather than a screening test because they already have symptoms. Doctors are already worried that they may have cancer. So we can tune the test differently. Right.
They have a higher likelihood of having cancer. It doesn’t need to be as specific. We can we can retune a test that will serve doctors for that population. And and beyond that, right now, our focus is clearly in the cancer space. But we know in the in the future that our methylation based platform could have applicability in cardiovascular disease, neurodegeneration, autoimmunity.
There are lots of other disease areas, hepatocellular diseases, where our technology could be useful. But right now our focus is really in the cancer space.
Harry Glorikian: Yeah, this is great. I mean, you know, it’s funny because I think I’m I have to admit, I’m probably somewhat biased just because of my background from ABI and everything else, about where I think this is going to go and what we can do. I guess I have one other question that, that when is finding it too early?
Like you and I both know that you know something’s going wrong regularly, and my immune system and everything else sort of manages accordingly. Is, you know, are you guys looking at that, thinking about that like when when you intervene versus when you watch, you know, versus.
Josh Ofman: The only the the only cancers that I’m aware of today that when you find find them in early stages, watchful waiting is used, is in prostate and thyroid. Most solid tumors in the early stages, you know they’re aggressive and you want to you want to get them out. You want to cut them out.
And surgically, it’s only these encapsulated prostate, slow growing fibroids that you might watch and wait. Those are the only ones I’m aware of in solid tumors. But this idea that, well, maybe you’re finding early stage cancer and your immune system is going to shut it down anyways. I think it’s an interesting hypothesis.
I’m not sure clinically that’s ever been shown, and I think if that’s happening, it’s probably happening in the very earliest stages of malignant transformation, very early. So, you know, in the, you know, some screening tests like cervical cancer screening, breast cancer screening, colonoscopy, you can find precancerous lesions. Right.
And hopefully it’s in that transition from precancerous to cancerous, where the immune system is really coming in and shutting it down. That’s very early. That’s usually well before these tumors are shedding a lot of DNA. So that’s less of a problem for our kind of technology. But time will tell. We’ll need to understand that if that’s really happening.
But to to my eye, I haven’t seen any clinical data yet that says that when you find a stage one or two cancer, you shouldn’t treat it because the immune system is about to come and shut it down. I’ve never seen any data like that. Not one stitch.
Harry Glorikian: Yeah, well, you know, we’re just developing these technologies now, so I’m sort of it’s funny, right? The longer I stay in this space, the more I get excited about what’s coming next based on how technology is moving forward. So it’s a it’s a truly exciting time. I mean, you know, my wife was saying last night, well, maybe we should order that test.
So, you know, I think at some point, you know, we may just jump on that. I may ask my doctor to order it and jump on that bandwagon just to get a, you know, stay ahead of the curve. I think you guys get it. And you guys, it’s offered at Illumina and Grail annually if I remember correctly.
Josh Ofman: Yeah, my wife and I have had it twice now and thankfully all negative. I’ve seen colleagues, friends, others find early cancer, unsuspected cancer. We find a lot of hematologic malignancies. As you might suspect, there’s a very strong signal in blood. So, you know, we’re finding a lot of cancer out there in the community. Now, already I just heard yesterday about another pancreatic cancer that was found in an asymptomatic adult.
You know, we have found early pancreatic. So, you know, I recommend the test for adults over the age of 50 or if they’re younger than 50, if they’ve had a smoking history, they’re a survivor of cancer, if they have a genetic hereditary cancer risk, or they have a very strong first degree family history, obese diabetics, those are populations also at elevated risk of cancer. And they and they’re very similar to the risk of a 50 year old.
So those are people who ought to consider the test, talk to their doctor, make sure their doctor feels they’re at elevated risk of cancer before taking Galleri. And then we recommend it annually because based on our epidemiologic modeling, if we want to maximize the cancer detection rate in the population, you know, a lot of these cancers are very aggressive and they move fast. And so you need to do it on an annual basis.
We may even learn over time that we need to do it more frequently than that, because a lot of these aggressive, invasive tumors move through stages very quickly. And we’re learning that now by looking at the cell free DNA, which has never been done before, we’re looking at the natural history of cancer differently. And so we’re kind of rewriting the textbooks, you know, as we learn about these new assays. And so there’s still a lot to learn about how frequently we should do this.
Harry Glorikian: Yeah, no, I wrote a piece, a small piece like seven years ago saying one day we’re just going to be able to take a blood test and. at some point, you know, joke about, yeah, this thing we used to call cancer and because we got ahead of it and we’re able to solve the problem.
So I can, trust me, I can hardly wait because it would make take away one thing that I, I see people have anxiety about, because of family history or things like that regularly. It was great having you on the show. I you know, as this thing progresses, it would be great to have, you know, Grail back on the show to to talk about some of the progress and really honestly is getting the word out in educating people that these things are available, which always annoys me because so few people actually are aware of the technological advancement and what’s available for them to stay healthy and, you know, keep their family healthy.
Josh Ofman: That’s exactly right. Well, it was a pleasure to be on the show, so thank you for having us.
Harry Glorikian: Thank you.
Josh Ofman: Okay. Have a good day.
Harry Glorikian: That’s it for this week’s episode.
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