A few patents that were interesting, but they had really no lead agents. The vision was to put these companies together, utilize the patents if they were valuable in molecules, and to make a targeted therapy company. The targeted therapy company would go after, of course, antibody-based therapies, as per my history in the industry, but also other types of targeted therapy, which could include radioligands and small molecules. We're a standalone pure-play cancer company. We're not doing any other types of diseases. We're not doing every type of cancer modality. It takes different infrastructure to build things like cell therapy and gene therapy and other things. They're all excellent there, excellent concepts and excellent technologies and great molecules out of there. For a relatively small company, you have to focus. Our focus is on targeted therapies of the nature I discussed.
Great. I wanted to ask you some questions about varegacestat, which is an asset you brought in as well. That is nearing completion of phase three clinical trials. It is a gamma-secretase inhibitor that is being evaluated in desmoid tumors. My question is, how do you think about the size of the commercial opportunity in desmoid tumors? Obviously, there was a similar product approved, Ogsiveo, which is now owned by Merck . How do you think about potential differentiation or the opportunity relative to Ogsiveo in this space?
Varegacestat is, as you said, it's a phase 3 asset. We have completed enrollment to phase 3. We have guided for our data in a pivotal trial, a placebo-controlled blinded trial, to be released this quarter. That's pretty soon. We're excited for that. The reason we're interested in varegacestat, and when we saw this, we had been doing diligence on a lot of different drugs out there. We intended to build our own pipeline. Our pipeline is fantastic, and it's coming soon, but that takes a little time. We're two years and one month old. To build that internal pipeline was really, it's really, in my opinion, going to be our biggest value driver going forward. To get going quicker, and if anyone, if you know me, I'm a little impatient for patients, that's one of my favorite statements.
I wanted to get going quicker, so we looked around. We did a ton of diligence, and one of the molecules that came out of it was varegacestat. We looked at it and said, ok, this could be, based on the data that was known, this could be a fantastic drug and really help patients. What I'm interested in doing is making great medicines. I've made a lot of medicines that are available around the globe treating patients, and those medicines help patients. A lot of them have survival advantage. They've been published as such, and so I am not interested in phenomenology or hype. I'm interested in making medicines for patients, and the reason why I really liked varegacestat is the phase 2 data showed that it was much better than the alternative.
There's one drug that's on the market that you mentioned as an alternative drug. It's called nirogacestat or Ogsiveo. That drug was developed by SpringWorks. SpringWorks did a fantastic job. They brought in a drug from Pfizer that was largely being developed for neurologic disease. It has low potency, it has modest pharmacokinetics. They were able to get a 41% objective response rate and get the first time ever a drug approved for desmoid cancer. I give them a lot of credit. The company was acquired by Merck KGaA. That has helped patients. What we saw at Immunome was that we saw a phase two drug that was being developed by a tiny little company called Ayala. They were perpetually underfunded. They had different leadership at different times. They had no CMC at all.
It would have been very, very hard or impossible for them to finish development of this drug and consider a product launch. It was in a position where they had done a good job initially and showed that the phase two data was, when we looked at it, we talked to the doctors. We looked at the line listings, which is the patient's charts. We talked to the doctors, looked at patient charts, looked at everything, and said, wow, this drug is a lot better than nirogacestat. I know they are close to it, it is Vare versus Naira. It is a lot better than the one that is on the market, which is the pioneering drug, which was a great drug out there. This drug is much better from phase two data. It is once a day, not twice a day. We liked the chemistry.
We studied the chemistry. We studied everything about it. We thought this could be a much better drug. Now, to me, it reminded me a little bit of when I was running Seagen for 25 years. I looked at a company called Cascadian. Cascadian was a company that was a small company. It was perpetually underfunded. They had done no CMC. They had different leadership. It was a revolving chair of leadership over a few years. There's no way, in my opinion, that they could have developed and launched that product. It was great chemistry and a great product. I bought that company. I got tucatinib. Now it's a drug called Tukysa. It's available in over 70 countries around the world. It's the single best drug on the market for treating women with breast cancer that have brain metastasis.
So it's a great drug that I'm very proud of what we did there. But it was an uncovered jewel at the time. Cascadian was trading at $2 or $3 a share. Nobody on Wall Street wanted to touch it. But the chemistry was great. And the underlying data was great. So now, fast forward to Immunome. We were out there looking to build our pipeline, but also fast forward the company. And so we looked at a lot, just like as they did at CGEN. And almost everything we said no to. Because there's a lot of stuff out there when you start digging into the data and the chemistry and the biology and everything. It's just not up to a level that we would be interested in doing something. But this was different.
And this reminded me a lot of the Cascadian whole thing and looking at Tucatinib, not Tukysa. So we pulled this in. I think that, to go back to your question, I think that the market opportunity is substantial. You probably know that SpringWorks charges, I think, $350,000 for a year of therapy for a patient. It's a pretty rare disease, desmoid. In the U.S., it's about 1,650 patients per year. But there's about 30,000 in prevalence. So this is a wickedly difficult disease type of cancer. But it's not life-threatening like a pancreatic cancer would be. It's disfiguring. I mean, it is life-changing. It's awful. You wouldn't want to have your enemies have this disease. It's painful and awful a nd all sorts of bad things happen with it. And it happens to a lot of young people and more women than men.
And it's something that we, as a cancer therapy community, could continue to try to do better for. And so when we saw the data from phase 2, it looked like it was 20 points better than the nirogacestat. It looked like the median tumor volume reduction was 20, 25 points better. It was once a day and not twice a day. Now, that sounds a little trivial. And for me, to be honest with you, when I looked at it initially, I did not put that as a premium. But in speaking with doctors, doctors say the compliance of twice a day is not great. And it's not just convenience. We want a better drug. And if your drug is similar in efficacy to nirogacestat , we would use it because it's once a day. And it's once a day because it has different pharmacokinetics.
All drugs bind protein to an extent in the circulation. If somebody says your drug doesn't bind protein, they're wrong. They all bind to some t hey get pulled out of circulation a nd theirs binds a lot more than ours. And I don't want to give all the data. We'll present the data at some point b ut there's a couple of differences in the chemistry, but one is just pharmacokinetic application. And you want something that's not pulled out of circulation and gets below trough value and is not active. And so I like our chemistry better. The potency, it's 250x more potent. So you need very little. It's a really good medicine, if you will, for patients. So the phase three is the enrollment completed in February of 2024. So that means in August of 2024, we completed 18 months since the last patient was in.
And I pull that out of the sky, if you will, 18 months, because it's an important thing to look at. It's not written in stone in the FDA. But it's something I've used in my playbook in the past. When I was developing Tukysa, we had a phase three event-driven study like this one and blinded event-driven. And we were woefully short of the number of events in that case and went to FDA and said to FDA, we'd like to unblind this study. And we had a discussion with them. And we were 18 months after the last patient was on the trial. And FDA thought that that was an important thing because we had plenty of time to give every patient drug a nd they could stay on drug, a nd so that's something that stuck with me. And it's not written in a book at the FDA.
But it just stuck with me as something with cancer could be important, s o that's why we looked and made sure we were past there. Now, I'm not going to hear say whether we have hit our event number to automatically unblind or whether we did not hit our events. And we went and spoke to the FDA. But what you could be assured of is that we are on top of it. And we are well positioned, ready to go, and ready to unblind this quarter. So that's going to happen and we know what we're doing with that. What I can tell you is that on the CMC front, we are ready to get the product submitted and launched. We were very fortunate at Immunome to bring in Phil Tsai. He worked with me for 18 years at CGEN heading up manufacturing.
And Phil knows how to manufacture ADCs and small molecules and everything. And he's in charge of it. So we are on top of CMC. And like I said, Iella did nothing with CMC, literally zero. And so we had to hustle. If you asked me a year ago, what are you most nervous about with varegacestat , I would have said not clinical data. I would have said CMC and getting that all ready. But I am no longer anxious about it. We are on top of it because we have a great team. We're on top of regulatory. We have a head of regulatory from CGEN, our head of commercial from CGEN, our chief medical officer from CGEN. Now, we do have a lot of other non-CGENs.
But we have a lot of key people that were just the best of the best from CGEN that are reassembling the band. And these are people that are not looking for anything more than to make drugs for patients. They're committed, they're passionate. And when you look at the market opportunity, you need only 3,000 patients to have a billion-dollar drug. And when you look at the U.S., like what I said, 1,650 patients per year, 30,000 in prevalence, about 5,000 of those prevalence will come into treatment each year, roughly. And you look at Europe or the EU, I should say, with about the same 1,630,000 prevalence. You look at Asia. There's treatable Asia. There's more. There are plenty of patients out there to have 3,000 patients out there, plenty. You just need a really good drug. You need a really good medical affairs team to get out there and talk to doctors and a really good sales and marketing team. But underlying it, you need a great drug that's easy to use that patients want to stay on.
Right. Maybe, thanks, Clayte, maybe a couple of follow-up questions. So obviously, as you mentioned, as a second market entry, fast follower, if you will, there is the hope for differentiation. You mentioned the QD dosing, which is obviously a big advantage over twice daily. When we see the data, the ringside data, and I'm assuming we'll compare that to the DFI data, how similar or different are the two studies in terms of patient enrollment criteria and other factors?
So I would say that the patient enrollment, the type of patients, is going to be nearly identical. So I don't think we'll be able to say there's different patients in DFI, which was the trial that SpringWorks ran for nirogacestat and our ringside study that we ran for varegacestat . So I think patient population is going to be nearly identical. So that's a good thing. For looking at events, we are using radiologic scanning. And that is you do scans, i t goes to a blinded independent reader called Bicker a nd two readers read it. It's the gold standard. It's what I've used in the past. It's what I used on Tucatinib , a blinded independent group with two readers that have to correlate. It's what I know as the FDA gold standard based on other drugs I've developed. So that's what we're using.
SpringWorks used the radiologic method I just said. But they also used doctor assessment. Now, they only use doctor assessment in a minority of patients. And for our study, FDA only wanted to use the radiologic, their gold standard. They said we could capture the doctor assessment. And certainly, we'll present that to the FDA. So they'll have that. But to have only doctor assessment, if I was designing this on my own and no one said anything about another drug, it would be the gold standard in radiologic anyway. So it's non-arguable when you have data that way. So I think as far as the trial goes, we've run a very good trial. I'm proud of the trial. I know all of the operations of the trial and how it was conducted and how we did clinical operations, which is not necessarily the chief medical officer reports in.
But we have a great clinical op team that goes around to all the clinical centers and captures the data. So we're doing this in a very professional way that I'm happy with. I think that the things to look at when we have top-line data, doctors always ask, and this is not, I mean, you all know this, doctors say, what's the objective response rate? It's like the first thing doctors ask. What percentage of patients do you have objective? That means FDA-qualified responses by objective responses. So that ORR is a critical thing they're going to ask first. You can't hide it. It's going to be right out there. Their ORR is 41% in their phase three trial presented to FDA that's in their label. I can't change that. That's the bogey, if you will. We have to be a lot better than 41%.
So we look for our ORR with our top-line data. Another important thing that you can't hide from is the median tumor reduction in patients. Theirs was 59% in their trial. I mean, it's good. We have to be a lot better than 59%. If we come out and we're 43% and 62%, I'm incredibly disappointed. That is not why I'm doing this. I don't like wasting my time with that. We need to be a lot better for patients. So those are two really important ones. Clearly, there's some regulatory endpoints that are important, like PFS. And also, you want to see your statistics. You want to see your hazard ratios and p-values. And you obviously want to know about pain in patients. This is a very painful disease. But not all of them are official FDA endpoints. But we have a lot of different endpoints coming.
I think it's going to be very straightforward when we come out with our data. Is this better? Is it the same? Is it worse? I can't imagine that our drug and with our great phase two data, everything is worse. I mean, to me, I am doing this because I think we'll see our data. But I think either our data will be better, a lot better, or way a lot better. And that's why I'm doing this, to try to make better medicine for patients. So we hope that our data is much, much better. But we'll have to see when the data come out and it's unblinded.
That's super helpful. A question on tolerability. So we've heard from docs that dose reductions are happening fairly frequently with Ogsiveo. Over 40% of patients' dose reduce. Just given the high potency of your drug, do you see opportunity to drive higher dose intensity and perhaps better tolerability with varegacestat ?
So there are different drugs. They use a total of 300 mg per day. We use 1.2 mg per day. So it's 250x less. Now, our drug is more potent. But it stays in circulation better, has better pharmacokinetics. So there's a lot of differences to go out there and look. And one can predict, oh, a drug that's more potent will be more toxic. Alternatively, you could say, well, if you're using a drug 250x more just to get it there because of the bad pharmacokinetics, that'll be more toxic. So you can postulate whatever you want. What I can tell you factually is that their phase 3 data set and our phase 2 data set, it's hard for me to really look at them and say there's a huge difference. I think that our phase 2 data set is a smaller N than their phase 3.
So it's not a good comparison. To me, a good comparison is a phase 3 versus a phase 3. Now, if you look at the phase 2 that we had, which is the only data we have until we unblind, we are a little bit slightly more toxic in some areas and slightly less toxic in other areas. So if you take 10 different areas, but if you line them up, I wouldn't look at this that if I lined it up, say, you should use one or the other. I would say they're very similar based on phase 2 to phase three. But that's not a fair comparison. So when we come out with our phase three data, it'll be important to look at that. We had throughout the entire trial, we had something called a Data Safety Monitoring Board.
And the DSMB, I've used DSMBs in every phase 3 trial I've done. I mean, it's really important to have a group, largely academics, that sit there and they're professional. A lot of these people do this for a living almost. They look at safety of drugs. And they review it. And certainly, with our last patient being in February of 2024, if there was an issue that we had any issues with, we would have had to put out a press release. We would have had to talk about it. We did not. So it's not like we publicly said there's a big problem here. We enrolled everyone. The enrollment, I want to point out, the enrollment was fantastic. And what I look for as someone who's very experienced developing drugs is I like to look for something that I call same-center enrollment.
I've developed drugs in the past that haven't worked. And you go in and you enroll patients a nd you get one or two patients in a site. And then they don't enroll anymore a nd you call and you go, Dr. Jones, what's going on here? And they go, oh, everything's fine. Because they don't want to say bad things. And you go, but Dr. Jones, tell me what's going on. And they go, well, you know the drug's a little toxic. It doesn't really work. We don't really want to. But we have other drugs we're going to use in other trials. And you learn. In this case, we didn't have any Dr. Jones discussions. We had the centers enroll patients. Then they enrolled more. Then they enrolled more. And I look for that because you don't even need to hear the words of the doctors. If they enroll same-center over and over, they like what they see. And so that's a factor. Now, it doesn't mean the drug's going to work. You still have to see the data. But that's a good factor.
Great. So I'm going to just leave it at that. And yeah, well, hopefully, I'll look forward to the data very soon. And I did want to spend a couple of minutes just discussing some of your ADCs. And obviously, this is sort of your bread and butter. The most advanced product candidate targets ROR1. And it's using a proprietary payload, HC74. So perhaps could you discuss some of the differentiating features of that product candidate? And there's a very similar product by Merck also targeting ROR1. We've seen some data. We're going to get some white ash. And so I'm just curious how you think about, again, potential differentiation opportunity for that.
So with our ROR1 ADC, we're trying to do two things. One is we're trying to show that it's a drug. And you're doing the trial. The other thing is we're trying to prove that our technology is what we say it is based on preclinical work. So other ADCs past this will just look at whether it's a drug. But this one has the double evaluation. And it reminds me of Etcetras at CGEN. So when I started CGEN long ago, I was intrigued with empowered antibodies. They were not called ADCs. I named them ADCs. And they were called 10 other things. Genentech called them immunotoxins. Immunogen called them TAPs, tumor-activated prodrugs. And it had 10 names. And I started publishing on them and saying, these are antibody-drug conjugates, ADCs. And it got caught on. I should have trademarked it.
I got a nickel for every time someone says ADC. But that's not what happened. And so we went out there. And I did not discover ADCs by any stretch. They were out there. But I like to think that I pioneered the modern ADC, the ones that have stability and better engineering and better conjugation and better internalization and all the different factors you need in modern ADCs. And I made a number of them that are on the market. And now there's over 100 companies doing ADCs, which I'm very proud of because it's really helping patients is what I'm about. I'm impatient for patients. And I said that so much at CGEN. They put it on a T-shirt. And everyone came into work one day wearing a T-shirt that said impatient for patients. And it took me probably two hours to notice.
And I should have noticed quicker. And so look, I'm very excited with what we're doing. So when we looked at ADCs with Immunome, I don't want to take the same exact ADC technology that's out there and add it to the same 10 targets that 55% of ADCs are using. To me, that was not something to do. So what I wanted to do was similar to what I did 25 years ago. I wanted to, let's say I made ADC 2.0. ADC 1.0 was my low target. It wasn't really working well. ADC 2.0, I started the whole realm of it. I'd like to start ADC 3.0 and do something better. So we looked at all of the things that are wrong with ADCs. And I know it because I've built some of these ADCs.
And the two most heavily used technologies, if you will, are the CGEN technology with antimitotics and the topoisomerase 1 inhibitor from DXD from Daiichi. Those are the two most heavy in most of them. There are other technologies. But those are used most. Both of them have certain issues. Very notably, they both have resistance to common resistance pathways. They're sensitive to resistance pathways like p-glycoprotein. Our molecule, HC74, is not sensitive to it. They both have modest permeability. So we have a molecule that has much better permeability. And the specific reason why you want that is once the molecule is brought into the cell, you want it to have permeability so it can have bystander activity. And that's critically important. And we looked at all sorts of other activity and clearance. You want it to clear rapidly.
If it's not finding the drug, once it's released, you want it to clear rapidly so it doesn't cause collateral damage. And there's too many here. We just presented at the triple cancer meeting on our HC74 molecule. The poster that we had was packed. I have a chart that's confidential of about 20 different ADC technologies. And this would we have built preclinically in every shape, way, or form is better than anything out there, in my opinion. This is an internal chart. And so now coming out and taking this new technology and applying it to antibodies is critically important. So what we decided to do was every antibody we would use would be selected for high internalization because that is important. And so you can screen panels of antibodies. And you could look at them like that.
And so the ROR1 is the first one out the gate. The next six, I know their names. We're not talking about them because of international competition. Yet we will talk about them. We're doing all the IP work to protect them. And we have three coming out in 2026, one early, middle, and late in the year as INDs. Same with 2027, early, middle, and late. And so the ROR1 data, we've now reported that in phase one, at different doses, in dose escalation, we have seen objective responses at multiple different doses. And why that's important is you want to have a good therapeutic window. And your therapeutic window, you don't want a drug, when you test it, not to only work at the top dose because then you have a more narrow therapeutic window. We have seen responses at many doses. I am thrilled with the clinical trial. So I love our preclinical data, which we presented now completely. And I also now have given a little bit of insight in our quarterly press release to that I'm really liking the clinical data in our first molecule.
Great. This is probably a good point to stop. We're a little bit over time, Clay. But I really appreciate all the insights today. Thank you.