Yeah, just want to make sure. Okay. I'm ready whenever you are.
All the mics are on personal mode.
Okay.
Okay, good evening, everyone, welcome to Moderna's ASCO 2023 event. We're so happy to welcome you here. Today, we have both Stephen Hoge, President of the company, as well as Kyle Holen, Head of Therapeutics, Oncology and Therapeutics, here to review some of the data that we presented at ASCO. As a reminder, this is a IR event, and we will be making forward-looking statements. Please refer to the slide number two on the webcast, relating to the risks associated with everything we're about to say today. With that, I will hand it over to Stephen.
Great. Thank you, Lavina. I got this. I'll make some brief remarks. That's gonna be a problem. Turn it over to Kyle to walk through the data. First of all, thank you for everybody who's come here to hear this. We're really looking forward to completing the picture of our first primary analysis in this mRNA-4157, previously called PCV, now called individualized neoantigen therapy, phase II trial. This trial, as you all know, we announced that the first top-line results on relapse-free survival last December. What we've been doing since then is completing the analysis on that first primary analysis of about 40 cases. It's now 44 cases that we have in this data set.
Looking at the secondary endpoint from that, which is distant metastasis-free survival, that'll be the focus of our presentation today. We've also been looking at biomarkers to help us characterize the responses we've seen. I think what we'd like to do is share a little bit of our perspective of how we're interpreting those biomarkers and why it continues to leave us very bullish on the potential for mRNA-4157 to have an impact in melanoma and other cancers very quickly. I'm gonna turn it over to Kyle now to walk through the data from both our presentation today and then I will come back. Well, we're gonna have to get that. Sorry about that.
I'll present from here, so we don't damage anyone's ears. All right, I think we're good. Am I still on?
Yeah.
Okay, great. I'm gonna walk through the slides that were presented earlier. My apologies to those of you that were at the session this afternoon. I'll try and give a little bit more context to what was discussed earlier this afternoon. For those of you that weren't there, I'll try and hit the highlights and describe what we observed in our P201 study. Just a little bit of a background on melanoma on this slide. RFS and DMFS are really important endpoints in this disease. They have been correlated with overall survival, and RFS has been a regulatory approvable endpoint for quite some time, including from KEYNOTE-054, which was approved.
It was a study that approved pembrolizumab. Pembrolizumab was approved with a hazard ratio of 0.60 in the KEYNOTE-054 study. The KEYNOTE-054 study also showed an improvement in DMFS, which was statistically higher in patients who received pembrolizumab than patients who received placebo. This was a highly statistically significant result. This led to the approval of pembrolizumab. However, I'll point out that even in the patients that had pembrolizumab, there was still a significant unmet need with 65% of the patients who were alive and distant metastases free. However, there were still 35% of the patients that had recurrence. We would hope to improve upon that recurrence rate with the use of mRNA-4157. We designed this study, the mRNA-4157 P201 study, to include patients with high-risk melanoma.
That meant patients who had stage IIIB, IIIC, IIID, or even stage IV disease. All these patients, however, had had complete surgical resections. Even in the patients with stage IV, they had no evidence of disease at the time that they initiated treatment and were randomized into the study. Patients had a ECOG performance status score of 0 to 1, and they had tissue available for next-gen sequencing. They were randomized in a 2 to 1 ratio, with 107 patients in the combination treatment and 50 patients in the pembrolizumab control arm. You can see at the bottom that the analysis, the primary analysis, was triggered at 40 RFS events and at least 12 months of follow, 12 months of follow-up.
In the statistical analysis, we had a secondary endpoint of DMFS, and it was hierarchical testing, meaning that we would be able to transfer our alpha from RFS to DMFS, should we have a positive RFS signal. We also had endpoints around safety and tolerability. I'll walk through this very briefly. I think most of you by now know how we create the mRNA-4157 individualized neoantigen therapy. At the bottom, on the right, I'm sorry, on your left, you can see that a schematic where we take tissue from patients, both tumor tissue and normal tissue. We sequence with a whole exome sequencing, and we do RNAseq. We then take this information, we put it into our algorithm. The algorithm then selects for 34 neoantigens.
We after designing the mRNA, we manufacture the RNA, and we ship it back to the patient for administration. These are the demographics for our P201 study. They were generally balanced between the two arms, with equal amounts of men and women on both arms. The age was fairly comparable between the two arms. We also had comparable ECOG performance status, stages, staging, LDH, and lymph node dissections. There have been some comments regarding our PD-L1 and tumor mutational burden, slight imbalance. We have done sensitivity analyses on these, and we don't believe that that modest imbalance led to any difference in the outcome. As a reminder, these are the data that we presented at AACR back in April.
At AACR, you can see at the 18-month RFS endpoint, we had a hazard ratio of 0.561 with a p-value of 0.0266. This was a one-sided p-value, that was what we had designed as part of our statistical analysis plan. We met our endpoint with that one-sided p-value. Therefore, we moved on to our next endpoint, which was DMFS. These are our DMFS data. Whereas we had a 44% decrease in the risk of recurrence or death with RFS, here we're seeing a 65% decrease in distant metastasis-free survival, with a hazard ratio of 0.347 and a p-value of 0.0063.
This is a one-sided p-value, but still, even with a two-sided p-value, considerably, statistically significant here, there's really no question about the statistical significance at this p-value. Here you can also see the difference in DMFS between the combination and the pembrolizumab arm. You'll also note that the pembrolizumab arm performs similarly, in fact, probably slightly better than some of the other studies that have been performed in the melanoma space. We've also looked at the recurrence patterns, particularly the distant metastasis-free recurrence patterns, and we've highlighted the different organs that were impacted by recurrence events. Generally, the patterns were similar from the 4157 containing arm and the pembrolizumab control arm.
Some of these, of course, are significant events which are clearly not curable, including the recurrence in the brain, where you see a 6% recurrence from the pembrolizumab arm and approximately 1% in the brain. In the lungs, you see a much higher percentage of patients recurring in the lungs. However, these numbers are pretty small, so you have to use some caution when interpretation, but generally, the trends show favorability with the mRNA-4157 treatment arm. We also have some swimmer plots here on the actual events, and I'll just remind you that in this swimmer plot, it's a 2 to 1 randomization, so we had double the number of patients in the mRNA-4157 arm than we had in the pembrolizumab arm.
As I walk through this, I'll show you that the treatment is signified by the gray bar of pembrolizumab, as well as the combination therapy is the red bar. Each one of those red dots is a local recurrence, whereas the black squares are distant recurrence, and then death is signified by a blue square. Here you can see there were quite a few consistent and early recurrence events in the distant recurrences, both in the 4157 arm and some early events in the pembrolizumab arm. We also have done DMFS by ctDNA status, and I will show you some more in-depth results from our poster on ctDNA. What I'd like to highlight are a few things here on ctDNA.
First, in the solid lines, those are the patients that had ctDNA positive results, at the time of the patients enrolling in the study. At the top, you see the dashed lines. Those are patients that were ctDNA negative. The ctDNA negative patients all performed much better than the ctDNA positive patients, and you can imagine that this would be true because ctDNA positivity just means that there's likely residual disease at the time of surgery. We just couldn't see it with any type of imaging or by the naked eye. It's a very highly significant prognostic factor.
Unfortunately, for the 4157 arm, we had a significant imbalance of patients that were ctDNA positive in the 4157 arm, with 13 patients being ctDNA positive in the combination arm and only two ctDNA positive patients in the pembrolizumab arm. You can also look at the Kaplan-Meier curves. The patients on pembrolizumab who had a ctDNA positive disease recurred very, very quickly. Patients did slightly better with the combination arm, although these numbers are quite small. When you look at the ctDNA negative populations, so you're taking out the imbalance of the 13 to 2 patients, you can see the Kaplan-Meier curves separate pretty quickly. The Kaplan-Meier curves separate before 20 weeks, they continue to separate as you follow these patients out long term.
Here we saw a hazard ratio of 0.048 with the ctDNA negative patients. Now I'd like to talk to you a little bit about safety and tolerability. This is the same slide that we presented at AACR. Essentially, the types of events that we observed in the combination arm that were related to mRNA-4157 were what we would have expected with any type of vaccination process, like a COVID vaccine, where we saw patients with fatigue, injection site pain, some chills, and some fevers. Rarely was this severe. Most of these events were mild and very limited in the first week or two after treatment.
If you look at the pembrolizumab adverse events, very, very consistent with what you'd expect from pembrolizumab, and you don't see a significant imbalance between those who are on the pembro arm and those who are on the combination arm, suggesting that we did not increase the toxicities of pembrolizumab with the addition of mRNA-4157. Some of the safety and tolerability that were immune-related adverse events that you'd expect from checkpoint inhibition therapy. Similarly, we did not see an increase in the immune-related adverse events with the addition of mRNA-4157. Okay, now I'd like to do a little bit of a deeper dive on the ctDNA results. The ctDNA positive or negative, the assay was done using an amplicon-based next-gen sequencing RaDaR assay by NeoGenomics.
We used this assay on two of the core biopsies and whole blood samples to identify some of the variants that were most suitable for MRD. Unfortunately, there were some patients that we could not identify enough of the variants to determine whether or not they were ctDNA negative or ctDNA positive, but the majority of patients, we were able to assess whether or not they had a ctDNA result. These are the c-curves I showed you before, where we had a significant benefit in RFS from the patients who were or actually, I showed you DMFS data. This is the RFS data. With RFS, again, we see a pretty significant change in the curves. This is even earlier than what we saw previously.
Also impressive here with the RFS data is that we have a hazard ratio of 0.225. The numbers again here are pretty small. Because the numbers are so small, we haven't calculated a hazard ratio. We're really excited about the results in the ctDNA negative population. This is a depiction of the prognostic value of some of the markers in this population. Here we're comparing ctDNA negative versus ctDNA positive. The hazard ratio is remarkable at 0.149 when you compare the ctDNA negative and ctDNA positive populations, meaning that this is a significant prognostic marker for recurrent disease.
If you look at other markers like TMB high, TIS status, and PD-L1 status, they still show some benefit in helping prognosticate patients, but not at the same degree as ctDNA status. We are continuing to follow up patients, and the one thing I just wanted to mention very quickly because I know that there are some questions about the censoring. In a Kaplan-Meier curve, anytime a patient does not have an event, that those patients are censored, it does not necessarily mean they're lost to follow-up. We actually have no loss to follow-up patients in our study. They're censored because they just haven't had an event, each one of those tick marks means how long they followed up. Those are the censored events.
We are continuing to follow patients and adding more events as they occur. Our next, protocol-specified analysis will happen after 51 events. When we have 51 events, we will redo the RFS, DMFS, and see if maybe even OS is mature at that time, and then we'll release updated results at the time of the 51 events. That will help us with the durability of the treatment effect, with the long-term follow-up. As you already know, we are initiating a phase III confirmatory study, which we hope to have open in the third quarter of this year. We'll have many, many other studies that we're planning to initiate in additional tumor types, including another study opening up again this year in non-small cell lung cancer.
4157 with pembrolizumab had a clinically significant improvement, and I would argue a clinically meaningful, clinically significant and meaningful improvement in RFS and DMFS compared to standard of care pembro, with 44% reduction in the RFS and 65% reduction in distant metastases with two years of follow-up. It's the first randomized trial to demonstrate an improvement over pembrolizumab and the first vaccine to show an improvement in a randomized setting. The combination was well tolerated without an increase in immune-related adverse events.
The combination received a breakthrough designation, as you're aware, from the FDA and a PRIME designation from the EMA just this last April. I just want to thank all the people that participated in this study, the personnel, the collaborators, the scientists, all the clinical research staff, and of course, the patients and their family, and all the people at Merck as well as our Moderna colleagues. I think that was the last slide. I think, do we have time for questions?
Yeah, we're trying to move quickly to Q&A, 'cause we know you probably have seen some of this before. Just as a closing couple of comments, and then Lavina will start that. What we're looking at now, as I tried to say up front, is the initial the primary analysis. What we've seen is statistical significance to the RFS primary endpoint, and now dramatically more significant benefit in the DMFS endpoint. You know, what was a 44% reduction is now a 65% reduction in the rate of those events. As we look to the biomarker data, we start to actually have a pretty clear understanding, we think, as to why, which is relates to ctDNA positivity.
People who've had a ostensibly curative resection, but before they start their treatment, there's still evidence in their blood of circulating tumor DNA, and therefore a higher risk of progression. Even when we stratify for that subpopulation, what we see is, we think in the RFS curves and the DMFS curves, very strong evidence of a benefit in both kit populations. Actually, a trend that starts to look pretty consistent between them, which is that the DMFS benefit, hazard ratio is 0.347. That is a dramatic number. And the DMFS and the RFS, ctDNA benefit is 0.227. Again, a dramatic number. Those curves are separating early, and they're not coming back.
That is part of why we are really looking forward to the next analysis, the 51 event analysis, which will move us past the two-year median follow-up, perhaps towards three years. Really, we believe, start to demonstrate the maturing benefit of this individualized neoantigen therapy in preventing relapses, be they distant or local. With that, I'm happy to take any questions about any of the data we've covered today or anything else. I'll let Lavina come and see us. I'm also gonna stand here, so I don't get.
Yeah, yeah, we're gonna probably...
Okay, great. We're gonna bring microphones around. If I can just ask for the benefit of folks listening in on the webcast, please identify yourself before asking the question.
I think I have a good one to start off. This is Ted Tenthoff from Piper Sandler. I've always kind of wondered this: Are there always 34 antigens? Are they all unique antigens every time you develop or create the personal cancer vaccine? Are there ever any multiple antigens within a given vaccine, depending on the patient's tumor? Is there an ability or value now that this data is maturing, to really analyze the responses based on these individual antigens? Do you have that level of fidelity, or does it even matter? I think I have a second follow-up, just with respect to showing the difference between ctDNA positivity and negativity. Obviously, the benefits in both, but it seems to make sense to stratify maybe in the phase III. Curious if that's something that you're thinking about. Thank you.
I'll let Kyle take the second one, I'll start with the first. For the 34 neoantigens that are in each of those 107 people's product, they're almost exclusively private. The one exception to that is there are certain driver mutations that if they showed up, let's say a KRAS mutation, they would get prioritized because there are some recurrent driver mutations. There may be a few instances of those showing up in the vaccines. We haven't published that, but it'd be very, very small numbers. Truly, these are personalized private mutations for the neoantigens. That gets to your second part of your first question, which is, yes.
We are also now looking across those to understand, is there anything we can do to feed that data back into our algorithm? 'Cause we're now starting to see real benefits, not just in terms of immunogenicity, but potentially in terms of relapse-free survival or distant metastasis-free survival. In that case, again, we have the data, we have the ability to do that. It's still a relatively small sample size at 107 people. What we'll be, of course, looking for, are there opportunities to see recurrent epitopes in certain populations of disease that would allow us to move towards more of an off-the-shelf approach in some instances.
All that said, this is, we believe, to our knowledge, the first statistically significant trial showing neoantigen therapy. We do think that what is differentiated with it as opposed to other vaccine approaches is that it is neoantigen and private, as opposed to sort of overexpressed. As was mentioned today at ASCO, in the discussion slides, we do think that's a differentiating feature we don't want to lose as we move forward for now. Do you want to comment on the other?
Sure. Obviously, ctDNA is the most important prognostic factor in this population. We were assessing ctDNA for every patient in the phase III study. What I cannot confirm yet is whether or not that will be a stratification factor, because we're still under negotiations with the agency about the final design. Hopefully, we'll be able to share that information with you soon.
You know, if I could maybe just one other thing on that.
Sure.
Which is, and as you get to the microphone. At a larger study, some of those eccentric randomization things would just get controlled out.
Yeah.
I think we would all recognize that it's better not to be trying to stratify up front. Let's take patients based on stage, and just allow a slightly higher powered study... not to see any issue there. It is really encouraging, though, to see a benefit in both populations. It just speaks to the strength of the result. Again, DMFS, it overwhelms that because of the importance of distant metastasis, we feel confident.
All right. Tyler Van Buren from TD Cowen. Thanks for taking the questions. The first one is related to your comments on censoring. You noted that they're still being followed, obviously, but that's where they are currently. On the DMFS curves, a lot of ticks right around where pembro starts to drop off. Can you just elaborate on that and the probability that, you know, a bunch of DMFS events occur and kind of close that gap? You know, you show that slide where there's kind of no late DMFS events in the combination, so maybe that's part of your answer, but I'd be curious to hear you elaborate on that. The second question I wanted to ask is: have you shown this data to the FDA yet?
Regardless, have they given any color on what would be needed for an accelerated filing?
Okay, why don't I start with the censoring? Yeah, each one of these ticks is how far someone has been followed, and so there is a drop-off here. That means people had an event. These people have not yet had an event, but they've passed that area where there's a big drop-off, and we're continuing to follow patients. There's quite a few patients that are in follow-up. You can see, however, that as you go out further, the number of patients at risk are very, very small. At the very end of these curves, it's very unstable because we just don't have enough people that are out 140, 160 weeks for us to have stability in this curve. Are these the patients that you're talking about in the pembro arm that are post?
Talking about all the red ticks, right?
All these
Where they start to drop off, yeah.
Yeah. We have, probably about equal numbers of patients here that we have in the follow-up, but I will say that there was a short period of time when we were unable to make mRNA-4157 due to the fact that our manufacturing facility was making about 1 billion COVID vaccines. There was a short period of time where patients were getting pembro and not getting DMFS. I think as long as we continue to follow these out, I don't think that there'll be any changes in the outline of the curve, because the curve is pretty flat all the way out, and once you start seeing flattening of that curve, it's unlikely that you're gonna see a significant change.
Maybe the best way to address that is if you look at the exposure numbers on the bottom, you can see that there's a pretty much a 2 to 1 balance as you move left to right. Right? There's no. While the censoring can look a little bit thick in certain places, the truth of the matter is that if you look at the overall balance between them, it looks pretty much balanced, certainly through that day 80 or that week 80.
The other thing is that when you see those groupings, people come in for scans and screening, and that's actually really what's happened, is people haven't just gotten to that point yet or are in a window in which they're supposed to, but maybe haven't come into, which is what would cause somebody to be, quote, unquote, "censored." They just haven't made their appointment yet. They can't be contributing to the arm, which is why that kind of looks like it's every three months as a periodicity.
Oh, you're talking about the grouping of scans.
Yeah.
Yeah, everyone's getting a scan here, and then they're all getting their scans here.
They have a window in which they need to come in. We're not seeing any imbalance in that censoring as we look at that data that would cause us to have suspicions about these results. Certainly, what we're looking forward to is if you fast-forward that curve a year, which is about where we think, we don't know when we're gonna see these 51 events and we rerun these curves, a lot of that will have progressed to the right, just naturally over time.
Your question about the regulatory path.
Oh.
Yeah.
Have they seen the data, and regardless of that, or have you submitted it to them, and regardless of that, with prior conversations, have they said what is required for an accelerated filing?
Yeah. I'll let Kyle comment a little bit in a sec, but generally, we won't comment on the specific conversations we're having with regulators, for obvious reasons, that we're just trying to keep those confidential with them. However, we have not had a chance to discuss the most recent DMFS data, you know, obviously, we're incredibly encouraged by the way, and we will, at the appropriate time, have that conversation. I think, you know, what I would just say is, independent of those conversations with regulators, we've tried to say over the last few months, from our perspective, what would we want to see for us to believe that it was time to seriously consider an accelerated approval? The RFS data by itself alone, as I said before, wasn't quite there, right?
It just didn't feel like for us, it was quite there. As we start looking to DMFS and some of the biomarker data and the enrichment of these responses and hazard ratios like 0.347 and secondary endpoint with all the alpha coming through and the P-value there, some of the residual uncertainty seems to be going away on that potential benefit. I think we want to see that mature for so all the reasons we were just talking about. This is still the first, right? This is the primary analysis, but we'd like to see those slightly more events.
Then the last thing that we said, for our benefit and ultimately for the public's benefit, and we think regulators are increasingly expecting this, is before we move towards accelerated approval, we think we have an obligation to start a confirmatory study and be enrolling in it, to demonstrate real conviction on not just relying on that accelerated approval. We've seen some of the attention around that even in this country more recently. Those are the things. If you ask me my personal opinion, we're getting to the point where the thing left to do is actually to enroll that phase III study, get up and running.
Because at that point, everybody will know that the confirmatory results are around the corner, and then, I think it might be appropriate for us, for our own purposes, to consider pushing that way. Now, I don't know if you want to add anything to that.
Just... I'll just say that what regulators like to see is consistent trends across all the endpoints that you're analyzing. We now have trends in RFS, we have the trend in DMFS, we have a trend according to ctDNA. We've presented TMB data that also shows a trend towards improvement in both TMB low and TMB high. I think when you see trends across every single data cut showing very positive hazard ratios, then it leads more belief, both from us and generally from regulators' standpoint, that these are data that are compelling. Now, the nice thing about Breakthrough designation and PRIME designation is we have an open door policy now with the agencies, and we can talk to them about new data as it comes in. It allows us to have lots of discussions with them about the regulatory path.
We are excited to share this new data.
Before we go, back to the questions in the room, can I just ask a clarifying question that came through on, the webcast, which is on the censoring, can you confirm that those patients were not lost to follow-up?
Yeah, we have no patients that are lost to follow-up.
Thank you.
Mani Foroohar, SVB Securities. A couple of questions. One, clarifying the statement around a brief period where manufacturing was directed, as one would expect, overwhelmingly towards COVID vaccine production. Have all these patients gotten the nine doses that are designed and that are mentioned in the study design? Are there still additional doses coming, and for anyone who kind of missed it during that manufacturing disruption?
During the manufacturing disruptions, patients were manually allocated to pembrolizumab, so they did not get COVID, and then once we were manufacturing again, then we were randomizing again. There was no disruption in anyone's forty-one fifty-seven treatment that was already randomized to forty-one fifty-seven. It was just a manual allocation during that time.
I can say, 'cause Kyle wasn't here and lived through that. Folks have received their treatment, you know, we announced the complete enrollment of the study over one year ago, two years ago. It's nine doses, as you know. All of that has proceeded through, and I think that's more of a historical artifact of just a couple months of disruption a few years ago in terms of enrollment.
Is that 9-dose regimen about, well, about what we should expect in other tumor types, or should we expect a different dose number, sort of different regimen in other tumor types?
It's a great question. I wish I knew the answer because there's not a great scientific way to answer it. I think, we're in the, it's not broken, so don't fix it category of, this feels like it's generating strong immune responses and evidence of a benefit, so we'll likely proceed with this. Now, as you move earlier stages, you might consider different regimens. This was designed because it's concurrent with people coming in for their infusion of KEYTRUDA, right? Just getting a, what is essentially a booster in their arm. For that reason, we go every three weeks here. It's very convenient.
In the future, we might pursue other regimens, but for the near term, I doubt we will change that because we intend to be principally working in the near term as on top of adjuvant KEYTRUDA.
Great. A question on behalf of a colleague of mine. Do you agree with the hypothesis that the late separation of the curves could be due to a slow ramp up of T cell immunogenicity with the vaccine? If so, are you evaluating any technological approaches to speed the T cell response?
I mean, I'll handle the technical question to you as well. If you look at the RFS curves stratified by ctDNA status, which is, as we just talked about, the single biggest prognostic factor for progression in this study, is whether or not you still had tumor DNA circulating post-surgery, pre-treatment. If you look at the dotted lines at the top here, those dotted lines are for the ctDNA negative populations. As you can see, that's 77 and 33, that's the overwhelming majority of the study, right? It's 110 out of 150 odd folks at baseline. Those curves are separating, as Kyle pointed out, about, you know, give or take, week 10. Patients are being randomized. We're getting the drug on board, usually that third cycle, 6 weeks, 42 days.
We actually start to see evidence that curve separation is happening pretty quickly. Now, we do believe, based on our vaccines work, COVID, CMV, RSV, that prime boost and maybe even as we saw with CMV, a second boost, you're gonna get stronger and stronger T cell responses. It's perfectly logical. In fact, I would endorse the idea that you probably wanna be boosting those T cell responses for a while, a couple of months, minimum. Although we do see a little bit of separation after 10 weeks here, I think we've got to be careful. It's very small numbers and very small deflections. What really is obvious when you look at these curves is that deflection, that separation just continues and matures over time. I would think that that's related to deepening T cell responses across the neoantigens.
The short answer is, I think we see earlier separation than we had previously reported, but we do think that multiple boosts are gonna be necessary to get T cells where they need to go.
Great. Thanks so much. Luca Issi, RBC Capital Markets. I wanna circle back on Mani's question, maybe ask different, slightly different things. My understanding, the patients are receiving up to nine doses?
Correct.
I wonder if you know what percentage of patients actually receive all nine doses versus a fraction of the nine doses, and whether you see any correlation between the number of doses and clinical benefit? That's the first question. The second question, circling back on the imbalances of baseline, obviously, you have more patients that are PD-L1 positive, as well as more patients that have higher tumor mutation burden. Can you just expand a little bit more on what gives you confidence that this signal is actually not driven by that imbalances baseline? Thanks so much.
The vast majority of patients had nine doses. I don't happen to know the exact percentage of patients that had all nine doses, but I can get back to you with that, if that's okay. The second part of the question was.
The imbalance.
... Yeah. The best way to answer that question, Kyle mentioned before, is to stratify and look for the benefit in each of those subpopulations. As we presented AACR, we actually see benefits for PD-1 and both high and low, and TMB, both high and low, and the tumor inflammation scores, both high and low. Here, ctDNA, both high and low. In fact, it's remarkably, if I would, I would observe, it is remarkably resilient, that the benefit seems unrelated to PD-1 status, unrelated to TMB status, unrelated to ctDNA status. It's, it's showing up everywhere, which suggests there's a novel mechanism action, right? All of these are known stratification factors that you know, you look for. From our perspective, and Kyle, you know-
Yep.
as we look at this data, we have not yet found the place where we don't have a high degree of confidence in the biological effect we're seeing. It probably matches the biological hypothesis of what you're doing. There's really no reason why, you know, a vaccine, a neoantigen therapy, that's trying to improve T cell, expand T cells and activate them independent of PD-1 status, why it would be dependent upon PD-1 status, as an example, or why it would be responsive to ctDNA status independent of the risk of progression.
The magnitude of that benefit is pretty consistent as well. When you start seeing consistent magnitude of that benefit across all these subpopulations, it's hard to argue that that was really a factor in the imbalance was a factor in the overall outcome.
Gena Wang from Barclays. I have a few questions. first, I think you mentioned that there are some patients did not reach nine doses. What were the reasons for this patient did not reach nine doses?
Yeah, I don't have that information.
I mean, here is an example of a reason.
Mm-hmm.
Which is patients that progress inside of the initial, 27 weeks, as an example, you know, may come off study and not receive, further doses. They may stay on study and receive them. That's an example.
We did not have significant treatment discontinuations either. I think on the safety slide.
Is it there?
you go to, discontinued due to adverse event.
Oh, on safety.
On safety, before. We don't have that on that slide, but we didn't have any treatment discontinuations because of mRNA-4157 treatment. There were some treatment discontinuations because of the pembrolizumab, but not because of the mRNA-4157 adverse events. Some patients did come off mRNA-4157 because of recurrence. I can get back to you with those exact numbers. I don't have that percentage with me.
Yeah.
Okay, great. Thank you. My second question is at DMFS, secondary endpoint. You did a stats analysis on ctDNA positive and negative.
Mm-hmm.
Were these, pre-specified, or was it post-hoc analysis?
That was a post-hoc analysis. We did not pre-specify a ctDNA subset.
Okay, the secondary endpoint, DMFS, that's pre-specified?
That was pre-specified, yes. That was the first ranked secondary endpoint. Right after RFS, then we had our DMFS ranked endpoint evaluation.
My third question, last question is the 51 events based on the current update? What is the estimate? I know it's very difficult, but, you know, what could be the possible time range for that event?
I'm gonna say, Kyle, we don't control the rate of these relapses, nor do we, you know, want to guide beyond saying, As soon as we have the 51 events, you can be darn sure we're going to turn around that analysis real quick.
It's really hard to speculate on when that would occur. Honestly, we hope it never occurs, right? That nobody has this recurrent event. Unfortunately, there's not a consistency in these events occurring, that we can safely say it's gonna happen next month or in the next four months. We're still waiting for those events to come in.
If I could give you a little bit of insight into one way I would look at that if I were in your shoes. The events are relapses, right? Not distant metastasis-free, or not distant metastases. What you can see, these are the populations, right? The ctDNA positive populations, people who had their tumor removed, but even after the tumor was removed and their lymph node was removed, they still had circulating tumor DNA. Essentially, you can see that those have all progressed. The monotherapy arm moved very quickly in the black, solid black line.
They've all come down, and everyone's had an event.
We actually did you know, we were positively surprised by what we saw with the ctDNA positives on the red line, as you can see. A large number of them did last quite a while without a relapse, which is good news. What you can also note is that the top red line, our ctDNA negative combination therapy, has essentially flattened out. We'll see how that plays over time. If you believe that that line is not contributing, and you believe that the two solid lines are no longer capable of contributing, then really what we're dependent upon is accruing events in the pembro monotherapy arm. As you can imagine, that's a smaller portion. As you can see, about half of those have happened.
It is good news, we think, that any patient is not progressing. It also might bode well for the performance of 4157, that in fact, it's taking longer and longer for us to see those events, because looking at those curves, you know, it appears that they're really gonna have to be coming out of the monotherapy ctDNA negative line.
One of the things that was particularly exciting for us is to see that if you're ctDNA negative and you were randomized to the mRNA-4157 pembro arm. You're essentially at a 90% cure because these patients are not recurring at 140 weeks, they're flatline Kaplan-Meier curve. We'll continue to follow up and see if there's any changes in that curve, but once you start seeing Kaplan-Meier curves go flat, it's unlikely you're gonna see significant more events.
That's a hard question to answer, Gena We can't.
From these likely from these these folks.
Rest assured, the moment we have it, we will very eagerly look at it because it will allow us to update the maturity of all these curves. The latency here, the delay, is maybe not bad news.
Anoumid Vaziri from Salveen and Richter's team at Goldman Sachs. In your view, how do the results from this study inform the translatability to other indications such as non-small cell lung cancer? Could you help quantify what success would look like for you at the 51 event analysis? Thank you.
Sure. I guess I'll handle the other tumor types. INT is not a therapy that is created for a specific cancer. Unlike other cancer treatments, where you are creating a treatment antibody, or a small molecule based on that histology and what makes that cancer grow uniquely different than other cancers, we're creating INT 4157 in a way that is tumor agnostic. Meaning, just looking at the variant calls between the tumor and the normal tissue. Because of that, we believe that there's really no reason why INT will not work across all these different cancers. In fact, it makes our job a little bit harder, because basically, there's the world is at our fingertips with all these different cancers.
We'd like to start in places where we think there's the immediate adjacencies to what we've observed with melanoma. What that means is, cancers that we think are more immune responsive and cancers that have been shown to have efficacy with checkpoint inhibitors. That's our first step, but we have ambitions beyond just the pembrolizumab combinations, going to earlier settings, late settings, and across a whole variety of different cancers. We don't believe that there's really a limitation to INT, and another reason why we believe that is because if you look at TMB status from our AACR presentation, we had efficacy in TMB high and TMB low, which suggests that even in patients that aren't typically responding to pembrolizumab, they'll still respond to INT.
We're excited about the possibility, and we really don't have a limitation right now on what type of cancers we think we can go after. Would you like to add anything to?
No, I, you've covered it well, particularly that we wanna move outside of the combos. The obvious place to start is in the adjuvant combos, where there's headroom, as there is, we've shown here, to improve. On the question of success at 51 events. Look, I think we've talked about the fact that we believe the curves are gonna continue to mature, as you just look at them in a favorable direction. Certainly, you know, the separation is whether it's early or late, it's sort of sometime in the middle of that first year. What really starts to happen over time is those curves, you know, start to really differentiate, whether you're looking at DMFS or RFS. That means that if that holds true, the hazard ratio will improve over time.
Now, to some limit, in this case, you know, we're seeing the hazard ratio in DMFS is already at 0.347. The p-value is 0.006. I mean, that's a dramatic 65% reduction. Perhaps, perhaps some of those things won't keep going. In the case of RFS, we talked about it as a hazard ratio of 0.56, that's 44% reduction. When you start looking at things like the stratified by ctDNA status, you could start to believe that actually that might drift down towards a number like we're seeing here in the stratified analysis, 0.3, 0.2.
What we'll really be looking to understand is more than just those 51 events and where they happen, and hopefully, they don't happen, but if they do, we expect them to happen in the same, you know, in the same way they have been. The question is, as we mature another year on those curves, and you start to have more and more of the exposure risk be on the right-hand side of these graphs, the hazard ratios should start to approximate what the right-hand side of the graphs look like and go down. Success, from our perspective, would be continuing to see really strong, statistically significant hazard ratios, both DMFS and RFS.
A big success would be continuing maturation of those curves and actually an improvement in those hazard ratios, particularly the RFS one, as we start to understand where we think it's trending.
I'll just add, as a medical oncologist in the field for 30 years, I will challenge you to find many studies with a better hazard ratio than 0.225. I mean, this is.
Yeah, or in the DMFS primary, you know.
It's-
The per protocol analysis, has a ratio of 0.347.
It's, it's something that is just not common in the field and really exciting. I'm thrilled with these data. I'm not sure it gets that much better, but I'm, you know, we'll see what happens with the 51 event analysis.
Hey, it's Michael Yee from Jefferies. A couple, follow-ups. On the patients who progressed in your arm, was the takeaway that all of those patients were basically the ctDNA positive patients, but what else do you know about those patients, including immunogenicity data? I thought there might be an analysis or some information on that. That's question one. Question two is, what are the gating steps to starting the phase III melanoma and lung study? Question three is, what is your view on metastatic, given that you continue to say a lot of positive things about where pembro works? I feel like there's a mixed commentary and body language around metastatic. I thought there's actually a head and neck phase I ongoing. Will we ever get any information on that? Thanks.
I may take the first, you want to take the second and third?
Sure.
Does that work?
Yeah, that works.
Okay. First on the question, I can just point to the data we've released on the curves, but if you look at the DMFS by ctDNA status, so I'm going to look first at distant metastasis, today's data. What you can see there is there's only 1 event out of 77 that was in the ctDNA negative population. I'm looking at the table on the bottom. Clearly, in the combo arm, only 1 event is, I think, the most direct answer to your question. As you go look at the RFS data, and again, there in the RFS case, it's a little bit different, but you see that there are more events in the RFS case.
I'm trying to find really quickly, 8 out of 77 in the RFS case in the bottom of the table. In both cases, clearly more on the ctDNA positive. In the, you know, I think in the distant metastasis, which is from the primary analysis, as we've been talking about. Oh, sorry, I went past it. That ratio is 1 versus 8. Now, sorry.
Oh, yeah.
Second question. Remind me of the second question?
Again, what you know about it is it ctDNA is your view of it.
Oh, immunogenicity.
Immunogenicity data.
Do you want to take it or me?
Sure. We have immunogenicity data that we've generated from the phase I study. We have analyzed some samples from the phase II, but unfortunately, we didn't have a apheresis for the phase II study, so we don't have much data to share, unfortunately, from the phase II data. We will be presenting immunogenicity data from the phase I data, and that's under analysis right now.
We are expanding, in our phase II, some translational endpoints and continuing to enroll some patients to build out some more of that. Immunogenicity wouldn't necessarily inform this data, we think, on the ctDNA positive versus negative side.
phase III melanoma.
We hope to have third quarter this year, melanoma, and fourth quarter, non-small cell lung cancer.
Subject to things beyond our control, consultation with regulators, our partner, so that's not, you know, guidance, but, you know, we are, as we've talked about with our previously, and I think Merck has talked the same, our goal is to start those two histologies into studies this year.
Part of that's related to the third question, which is I think much metastatic.
Yes.
I think what we need to do is find the right setting for us to test in the metastatic population. We wouldn't want to try and have our first study be in the non-small cell lung cancer population, where they progress so quickly that they couldn't wait six weeks before you had your first dose of vaccine. We need to find an area where we think either we can control them initially with some treatment prior to getting forty-one fifty-seven, or they have a slow enough growing tumor where we think we might be able to have them wait until we can give them their forty-one fifty-seven. That's really the biggest limitation in my mind about a metastatic setting, is you just don't have as much time to create forty-one fifty-seven for them.
I think it should work, and we just need to find the right tumor type in the right setting.
I think it's well said. I think our hesitation is not about the biology, it's about the operational questions. In the adjuvant settings, you know, we do think we got a tiger by the tail here. We think this is exciting data. Our partner, Merck, does as well, does believe that we need to go here quickly. I think what we're trying to do is stand up as much of the trials, as many of the trials across as many histologies as we can in the adjuvant setting, because we already have the operational system to do that as fast as we can. That's probably, if you see body language, is just we believe this is working and deserves to move forward quickly across a wide range of histologies.
Let's get that going and get focused on that first.
Okay, we have time for one last question.
Evan Wang from Guggenheim. I just have a few questions, I guess. Clarifying the differences in ctDNA positive versus negative. I know it's a pretty small subset, but wondering how you're interpreting those results and potential expansion again to more advanced settings. Counteracting that, maybe some of the speed of responses you're seeing now versus when you presented at AACR, does that actually provide encouragement there? Third, in terms of some of the immunogenicity data, I know you said it may be a small subset of that, but how should we be thinking about timing and, you know, what exactly that data set will look like? Thanks.
I'm glad you're writing these down. I'm gonna try and do the first one.
Okay.
There were 125 participants have ctDNA baseline status out of 157. It's, you know, I think it's over 80% of the population. The others, it was just, you couldn't at baseline, maybe get the assay validated for them. NeoGenomics, our partner in that assay, didn't produce it. We'll keep pushing to do that, but it is actually quite a large subset. I mean, the study itself is 157, but it's a, you know, well over 80% of the study. Did you have... Was that the wrong question?
Just to interpret some of the CTA, ctDNA positive patients.
Oh, I'm sorry.
What we're seeing there.
The rapid progression. Yeah. The 13 versus the 2? Let's point to those numbers. It's 13 and 2. However, obviously, the benefit that we're seeing in the separation in the 13, the red line, those that were on combo, is pretty encouraging and does look different. We wanna be careful about overinterpreting that. We need more numbers to go much further than that. However, I think this is the second part of your second question. When you see that kind of separation relatively early, you could start to see quite dramatic effects at, you know, let's say, that's 60 weeks, that's 1 year, if those red and black lines, the solid red and solid black lines, hold up. We are looking at those things as potential study populations for the future.
In the near term, it is not our focus. In the near term, we're focused on melanoma by stage, and trying to get that enrolled as fast as we can, but we'll continue to think about biomarkers and how they might be used to stratify risk or identify signals more quickly in the future.
Can I just add a little bit? This is one of the reasons why we're excited about the potential in metastatic setting, because these patients with ctDNA-positive disease, they're essentially metastatic patients. You just can't find it. If it works here, we think it's likely gonna work in the metastatic setting, too, and this is what gives us that early signal that a metastatic scenario might be feasible. I think the next question you had was the comparison between AACR and the data that we presented here at ASCO. It's the same data cut from November, just to remind everyone. We didn't have a new data cut that we did just for ASCO because we are following our statistical analysis plan that triggered that data cut after we had 40 events.
We ended up having 44 events included, but we triggered the analysis at 40 events, and by the time we had cleaned all the data, we ended up having 44 events. This analysis, DMFS, is from that same data cut from RFS. What we're excited about, however, with this data cut, as I mentioned before, we had a 44% decrease in RFS, and yet we saw a 65% decrease in DMFS. The trend and the improvement over that RFS was exciting to us for this ASCO presentation. The last, I think you asked about immunogenicity. We're in preparation to be able to release that immunogenicity data.
I can't give you a timeline because it's a little bit out of, out of our control based on the journal and the editors and getting back-and-forth comments and trying to get that published. We hope to have that published in the not-too-distant future, but I can't give you a timeline on when we're publishing the immunogenicity data, unless, Stephen, you've heard anything that I haven't heard about.
No, we're looking to publish it as soon as we can. Lots of comments back and forth and reviews.
We might be able to give you a heads-up if we find out that it's gonna be coming out. Right now, we really don't know when that data is gonna be published, unfortunately.
It's out for review.
Excellent. Thank you so much to both Kyle and Stephen for walking us through that data, and for everyone who had questions. Have a great evening, everybody.
Thank you!
Thanks, all.