Good morning. Thank you so much for being with us this morning. We are very happy with the team to welcome those of you in the room in Marlborough, the site for intismeran. Thank you so much for joining us also online. We will be making forward-looking statements today, and investing in Moderna entails risk, so please look at the forward-looking statements on the SEC website, on the company website. As you know, mRNA is nature's information molecule, carrying instructions to make protein in every living organism on the planet. Moderna was founded on the idea that if we could find a way to use mRNA, we could make new medicines for patients that not only secreted protein, but also transmembrane protein, and also go inside the cells' compartments. What is very interesting about mRNA is biology uses four letters to code every protein in life.
mRNA is really an instructions molecule. Because of that very unique feature of mRNA as an instruction molecule, as an information molecule, we thought that if we could invest in basic mRNA science, if we could invest in delivery system science, if we could invest in manufacturing and technical development, we would be able to build a set of bricks, technology bricks, like a LEGO, that then you can put together to make medicine. We could, maybe for the first time in the history of this industry, build a true platform where you can learn from one medicine to another one, when you can go faster from one medicine to another one. That was kind of how we set up the company from the beginning. Pretty quickly, we decided to use a concept of modalities.
A modality is a set of medicines that use exactly all the same technology bricks, the same chemistry in the mRNA, the same technology mRNA, the same delivery system, the same lipid, the same manufacturing processes. That feature of standardization, which is used in many other industries, but not really in pharmaceuticals, is a very powerful feature because you learn once, and then you scale. If you think about the modalities, think about the vaccine as the modality number one, if you want, on the left. Getting to the first vaccine was a long journey. Then getting the second, the third, the fourth vaccines is a much more scalable process, which is why we were able to move so quickly during COVID, because this was not our first vaccine. We had done nine vaccines in clinical studies before.
We had developed the platform, the manufacturing processes, the technology. This is how we think about the company. If you think about the unique properties of mRNA to make those protein secreted on the cell membrane intracellular, this is over time, and I am not talking months, I am talking years and decades, this is a very, very large product opportunity. Because most of the genes coding proteins in our DNA are coding for proteins that are not secreted, that are actually not addressable by the recombinant technologies. The other piece is if you have the modality approach, the standardization of medicines, chemistry, manufacturing processes, you should over time have a higher efficiency in R&D, a higher probability of technical success of medicines, because it is not like every time you put a new chemical in a human body when you go into the clinic.
For each modality, it is the same chemical that you put in the human body as the previous one. You just change the order of the letters. But from a chemical standpoint, from a pharm/tox standpoint, it is the same chemical. The other piece, of course, is with a platform, if you standardize, if you invest in IT, if you invest in robotics, you can develop drugs rapidly. Because again, unlike in pharmaceutical, where every medicine is a different chemical, you do not have to reinvent the manufacturing process for every drug. You do not have to build a plant for every drug, which is the last piece of a puzzle, which is greater capital efficiency. Again, like any platform, and we can look at the technology industry to look at what platform companies have done, to invest in a platform takes time and a lot of capital.
When you have a platform built in science, in manufacturing, you can scale the platform at a pace and at a capital efficiency that is very, very different. That's the vision we had. Where are we today? As you know, we have three established modalities, infectious disease vaccine, individual cancer treatment, and rare genetic liver diseases. We try to always use the mRNA technology not to do me-too products. We could in theory do another GLP-1 mRNA, but we don't think what this will bring in term of new value to patients and to the world. We want to use the technology to try to think about what other things we can do for patients that will over time create value for shareholders, but what we can do for patients that is different and could have an impact.
If you think about those three modalities, they're quite interesting because we think they're going to have a very durable franchise. If you look at infectious disease vaccine, there's not a lot of vaccine players. One of the reason, as you know, is you need to run very large phase III in vaccine. There are $700 m illion , $800 million , so it's a pretty big barrier to entry. There's no generics in vaccine. You have to prove back again to the regulator because of the safety element that not only the vaccine is working, but it's safe. It's pretty high barrier to entry in infectious disease. For intismeran, what's going to be really interesting, because as you know, those are individualized medicines by design, the algorithm, I will talk about it more, is ours. It's not public, it's not patented. The algorithm is ours.
We think that's going to be an interesting limitation to generics for the intismeran franchise. As you all know, rare genetic disease, it is very, very difficult to run a clinical study if you have a new drug, if there's a drug approved for those children, because you have to convince the parents and the doctors that it's the right thing to do for the children to take them out of a drug working to a drug that is experimental, that the safety profile, the efficacy of that new drug is not known. We think also in rare genetic disease, we're going to have a very durable franchise.
If you think about how we're trying to build this platform company, because it's kind of a unique way to build a biopharma platform company, we are trying to think about how we invest for growth in the near term, but how we not lose sight of what we can do for patients in five or 10 or 15 years, but what we do in the labs today. We try to think about different time horizons. Horizon 1 is really established modality, the three modalities I spoke about, infectious disease vaccines, intismeran, rare genetic disease. Horizon 2, we spoke about it quite a lot at Science Day a few months ago. It's really new modalities that we are trying to get proof of concept in the clinic that are in phase I or phase II.
One that comes to mind, because of the press release, I think last week, is mRNA-2808, our T-cell engager for multiple myeloma. That is basically the first medicine, the sentinel medicine in the T-cell engager modality of Moderna. We think that modality is really interesting compared to what you can do with recombinant, because you can multiplex that product at three T-cell engagers, and we could do more as the biology requires. Horizon 3 are modalities that are preclinical, but where the team is working really hard to finalize all the pieces to take those modalities into the clinic. One that comes to mind that we also talked about at Science Day in June is the in vivo CAR-T. It's not in the clinic yet, but it's going to be in the clinic very, very soon.
Those are basically programs that the team in the labs is working on to put the technology bricks together in a new way, sometime with new technology bricks, to build not one new medicine, but a whole family of new medicines. That's for horizon 3. Horizon 4 is basically inventing new mRNA technology blocks. What we're doing for Horizon 4 is investing a lot in what we can do and accelerate our learnings through AI. We presented at Science Day in June, LUCY, which is basically an AI-enabled full system that generates scientific hypotheses through AI, that basically instructs robots to make the mRNA, to make the lipid. Then those are tested in robots as well in vitro, then in animal model, and then you feed back the data into a system and you keep learning.
This is very proprietary data, obviously, and it's totally changing the pace at which we are learning as a company. The team is really very focused on how to use LUCY, how to improve LUCY, and this has really become a key part of our company advantage in terms of mRNA technology. Which is quite interesting when you think about where we are today, and I'll talk about it in my close, in terms of how the mRNA industry has changed just in the last few years. Of course, we also AI across the company. We've talked about it in previous investor days. We've had several sessions about it.
We think it's a very, very interesting opportunity for us to transform the company, to reinvent the company, in terms of how do we improve quality, how do we improve speed, how do we improve scalability, and how do we also get cost savings through a process. We really think that if you can improve quality across everything we do, if you can increase speed and reduce time, think just about clinical trial development, filing a BLA, manufacturing approval of products, all these timelines. If you can compress time, you can create a lot of value. As Juan will talk about later in terms of just the capacity of Marlborough, as you reduce cycle time, you not only provide the medicine faster for patients, but also you increase your capacity.
Speed is a very important element, and scalability when you have a platform is fundamental to be able to scale more medicine without having more complexity as you build the company. We have a very exciting morning planned for you. Stephen is going to come now to talk about the business strategy of our company. Then we'll have Juan talking about manufacturing. Jamey will come and close the business section with financials and financial frameworks. Then we have a Q&A with that group to answer more business questions. After a coffee break, we'll have Rita and Bill talking to you about infectious disease. Then David will talk about his favorite topic, which is intismeran and oncology.
I'll come back to close with just a couple of slides, and then we'll take those of you that are in the room, we'll take you on a tour. That's why you came to Marlborough. Thanks for making the trip. It's a bit out of Boston and away from Logan, but I think you'll get a good sense of how different this technology is from CAR-T. I've read in many, many notes, this is going to be like CAR-T. I hope after the visit, you have a good sense that it's nothing to do with CAR-T. The only commonality with CAR-T is it's individualized. That is the end of it.
Have a great morning, and with this, I pass to my partner, Stephen.
Okay, thank you, Stéphane, and good morning, everyone. Thank you for joining us here, as well as those online. I want to provide a little bit of an update on our business strategy and very quickly get us to the conversations about INT, but first remind you where we are in our multi-year journey in building the company. We've been executing a three-year strategy to drive growth and financial sustainability and health of the company over the long term. The core of that, as we laid out a year ago, is really in our infectious disease business, the things, if you will, that are below this line. In 2026, we made real progress there, and I think we feel like we've set up very well for 2027 and 2028. I'll walk through some of those milestones as we go through the next few slides.
I also want to highlight that we have opportunities to grow ahead of that plan, and the first among them was intismeran. As we talked about last year in 2027, beginning to start to contribute, we would hope, and as we will talk about through most of today, we think we are well-positioned for intismeran to add an accelerator on top of our initial growth plans. What are some of those developments that have happened other than intismeran as we set up for 2027? First, the approval of our flu vaccine, mFLUSIVA, which is now approved in the United States, it is approved in Canada, and it has been filed and under review in many other markets. We have also seen the approval of our second-generation COVID vaccine, mNEXSPIKE, as well as our combination COVID-flu vaccine, mCOMBRIAX in the EMA, mCOFLU is the local brand in Canada.
We have seen strong execution in our commercial partnerships, and I will highlight a couple in Mexico and Taiwan that are now up and running and contributing in 2026, and we hope to contribute even further in 2027. Then, of course, the main event for the day is in intismeran. Okay, just running through some of those drivers. In 2026, we saw substantial revenue growth. In fact, we had initially guided in a framework of up to 10% revenue growth in our core vaccines business, and as per our most recent analyst call, increased that up to 15%-25% growth, and Jamey will provide a lot more clarity on that as we move forward.
Our strategic partnerships in the U.K., Canada, and Australia are all up and running and contributing meaningfully, and I will remind you that those are multi-year, many, many year agreements that are based on achieving both national resilience and defense. There is an R&D component to it in terms of investment. There is onshore manufacturing, and so these are dedicated facilities supporting the vaccine needs in each of those countries, and then multi-year revenue advance purchase agreements associated with them. We believe that a majority of sales for us going forward outside of the United States will come through these sorts of strategic partnerships, as many other countries, and I will highlight a couple more in a second, become interested in onshoring mRNA technology and manufacturing capability, given how it has already demonstrated such a dramatic public health impact through the pandemic and now our broader pipeline.
Now, in the U.S., the story is actually the mNEXSPIKE story, formerly called mRNA-1283, and how successfully we have launched that program in the U.S. market, both through the retail channel and through IDNs and government. It now makes up 94% of the shots in arms for a retail sales perspective for Moderna, and that was from last year, its first approval year. It has far exceeded our expectations in terms of a launch. We are really pleased with that timing, and I think we are most pleased with the demonstration of real-world benefit that has now started to allow us to have. Rita will stand up and share some more additional data on that, but we now have multiple publications showing the real potential of mRNA-1283 to, we think, provide the best public health outcomes against COVID compared to our prior vaccines as well as competitors.
Okay, next big driver for us was mFLUSIVA. In 2027, we did not have any expectations for sales. We are not raising those today. We did want to get the product approved and launched into the market in the United States, so that we can begin to set ourselves up for a 2027 year where we hope mFLUSIVA starts to contribute meaningfully financially for us. That happened, it was launched, and despite the fact that the contracting cycle was fully closed off, we are really pleased that we are now in over 25% of retail pharmacies. That is an accomplishment when you think about how much of the flu vaccine contracted volume is really locked in in the early part of the year, in the first quarter of most years.
We have already seen 110,000 shots in arms, with really the second half of the market, the second half of the season to go. We have been starting to publish some of the real-world effectiveness and vaccine effectiveness and economic studies, including the two referenced here, that really show the benefit of mFLUSIVA, not just from a supply perspective, but actually from a vaccine performance perspective. So pleased with where we are. In fact, in many ways, exceeding our expectations for what is not even yet really the launch year for mFLUSIVA. 2027 is the one that we are going to participate in the full contract cycle. Europe is a big driver, as everybody saw and knows. We now have four approved respiratory vaccines in Europe: Spikevax, mNEXSPIKE, mRESVIA, our RSV vaccine, as well as the flu-COVID combo in mCOMBRIAX.
It is a very large addressable market, nearly 90 million doses annually across those three vaccine opportunities. Because it takes a little bit longer to ramp up commercial activity, to get pricing and reimbursement and market access in the European market, we have been working our way through that. Key milestones are the approvals, as we said, through 2026, and actually now we are beginning the process of setting up for market access and reimbursement in 2027. So look for this to again be a driver for our infectious disease vaccines business in 2027. I will remind you, this is a market where we have negligible sales as a result of the pandemic and as a result of the fact that we have just now recently been able to get those four products approved.
We are excited to be building our respiratory business in what is still a very large respiratory vaccine market. We are moving beyond into new markets. We have talked about our strategic partnerships in U.K., Canada, Australia. I have talked about Europe. Mexico and Taiwan are two examples of where we made progress this year in entering into multi-year agreements and beginning to deliver them. In fact, just in September, we signed a five-year agreement to sell COVID vaccines to the government of Mexico with a local manufacturer. I have already started to deliver the first doses there. Their initial 4 million doses were shipped in September, and we continue to build from there through this season.
It is a meaningful long-term commitment, so it's a multi-year supply agreement with that local manufacturer, and it's just another example of the kinds of relationships we're building as we enter into new markets and build our vaccines business. Taiwan is another one. That's a direct, from our perspective, where we won a multi-year tender for COVID vaccines in December 2025, which sets us up well with stable business 2025, 2026, 2027, and beyond. We will continue to explore additional opportunities, but we are executing on these strategic partnerships that really set us up for growth and stable business going forward. Last, and by no means least, is intismeran.
Others will stand up and walk through the data, but we are obviously very excited to be partnering with Merck to bring intismeran forward and try to establish it as the new standard of care, we really think it should be, in adjuvant melanoma. The benefits, David and others will walk through, but we think it is obviously exciting to be talking about a potentially curative treatment for those with high-risk melanoma. The safety profile continues to be the thing I would just point to as a commercial opportunity, not just in the context of the benefits it's providing of adjuvant melanoma, but as you think long term about where INT might play more broadly than in the adjuvant setting.
The fact that its safety profile continues to be so impressive really bodes well for monotherapy applications if we're able to show a benefit, and treating earlier stage disease. Even stage I lung, as you all know, is a place where we have an ongoing phase III trial with Merck. The other part of today, and the thing that we'll be looking forward to sharing, is how important our launch-ready infrastructure has been as an investment area for us over the last number of years. It is not something we popped up two months ago when the press release came out on the phase III result.
In fact, you're sitting in a physical manifestation of how forward-looking we have been in that regard. It has been a substantial investment area for us over the last three to five years. In fact, this facility is just one part of many activities we've been investing in, including building out specialist capabilities from a commercial model perspective. This is a very different sale. We will partner with Merck, who has incredible field capabilities, but there is a need to understand the unique nature of the first-ever individualized cancer vaccine.
There are order portals and digital investments to make sure that the process runs smoothly. We have a Moderna INT engine that orchestrates all of this, named MINT, which provides all of the coordination of an incredibly complicated effort to deliver products around the world as a part of the launch, but even our R&D activities. We have this purpose-built facility, which Juan will walk through, and the tour will walk through in great detail to give you a sense of where we are from a scaling perspective.
All of that has been an investment for us over the last number of years, and we are excited now to turn that into a commercial return if the product is approved and launched as we hope next year in 2027. Merck will be our co-partner in the U.S. on commercial activities. They will lead outside the U.S. That sets up really well from our capability perspective as well. The entire commercial and operational ecosystem is what we are proudest to have built and we are looking forward to highlight today. There is obviously the unmet need, which is why we are all here. We still see a sizable opportunity in the U.S. market in adjuvant melanoma to improve upon standard of care, to become standard of care, we hope. 22,000 patients annually are eligible.
About one in 10 will recur or die within a year of adjuvant therapy, tragically, still high unmet need. About half of recurrences, and there are a lot of recurrences, unfortunately, will involve distant metastases, which over the long term do correlate with overall survival. But we see a large opportunity to expand from just that stage III space, even into the stage II area. About a third, almost 40% of eligible stage II patients do not receive adjuvant therapy post-surgery. An example of a place where we believe the unique safety profile and dramatic benefits that we are seeing with INT could expand the toolset and maybe even the market for treating adjuvant melanoma in the United States. All of those great opportunities were well down the path in executing our growth strategy and setting up well for 2027 and 2028, as I mentioned a moment ago.
A fair question to anticipate is, how then are we balancing all of those investment areas? We have large number of resources, but not infinite resources, and how do we think about the trade-offs? What I would like to frame up today, and Jamey will do a lot more on towards the end of the morning session, is how do we think about these different investment areas and balance across them? The short answer, not surprisingly, is we think about them very differently. We are going to manage them very differently, and in how we talk about them with all of you and our investors, we hope to provide more clarity. First, let us talk about the infectious disease vaccines. We believe that as we look over the next three to four years, we have a unique growth opportunity to continue building that business.
A lot of the things I highlighted before were in the commercial space, and we will continue making the investments, expanding into Europe, expanding to other markets, launching all of our products in all our geographies. But we will see ongoing opportunities to invest in pipeline, opportunities that include things like our Lyme disease vaccine, our EBV vaccine, which is against infectious mononucleosis, but also can prevent sequela if it is effective, we believe, in things like multiple sclerosis. There are a lot of other opportunities in the early to mid-stage pipeline. Now, how do we think about growing that pipeline? We have already got five approved products. We have got six that we are in development with, norovirus in pivotal development, and then these here. The answer is we are going to pace our growth based on the growth of the infectious disease business.
In some ways, we think it will be P&L funded, profit funded going forward. That is a self-funded growth business for us when we look forward. Intismeran is in a very different stage of its development. If you look at intismeran, it is clearly balance sheet funded now. We are advancing, we are investing across all of the infrastructure that I just described, as well as expanding clinical trial work. We have nine ongoing trials, but we are not done there. There will be more trials coming, and David and others will highlight some of that. We are looking to accelerate that investment to drive both the near-term revenue growth, the launch of the product through our commercialization efforts, as well as long-term value and profitability. That really is about expanding into new indications and moving them forward. That is principally a balance sheet-funded opportunity.
We try to take a multi-year view on the resources we have from our balance sheet, and Jamey will say more about that. The third area of investment is what we call mRED, Moderna's research and early development efforts. Our approach here is also balance sheet funded. We use money that we have on our balance sheet that we have raised through the convert and other, but we are constraining that going forward. Whereas INT, we will invest substantially to accelerate. Our approach to mRED is more based on our long-term view as an entrepreneurial company, as a biotechnology company, that we want to continue to drive innovation and investment in the cutting edge, but we want to do that in a disciplined way.
We want to have a pool of capital that year over year for multiple years, we invest carefully, and as we see proof points, we accelerate beyond that. What are some of the proof points that we are looking for that would cause us to accelerate? Our cancer antigen therapies, so our off-the-shelf cancer vaccines, is one where we have some very early data. We are looking to share more as we move forward, but we will be looking as investment opportunities in mRED. Our T-cell engagers, we have shared some in the R&D day in June, and there is obviously upcoming abstract and presentations that will share even more data, and we will talk a little bit about that further today. But that is another place that we believe the platform has a real opportunity to expand, and we will potentially invest.
There are obviously future modalities, many of them, but we have highlighted things, for instance, at our R&D day on in vivo cell therapy with our 6007 program. These are three very different types of investment. When Jamey shares a bit more transparency on the financial data in a bit, you will see that our infectious disease vaccines business has got about a $2.3 billion investment envelope. Now, as we move our revenue north of that, we will see cash flow positivity from that, and any future investments will be some share of that cash flow, will go back into pipeline investments. Intismeran and mRED represent the balance of the rest, approximately $1 billion of our cash investment in our business.
And there, we're viewing that much more as a balance sheet directed investment, meaning we will be very disciplined, we will look forward over multiple years, we will have data that will cause us to invest in either new indications in intismeran or new technologies in mRED, but we'll do that from a relatively fixed mindset of our balance sheet, investing in that long-term future. We will continue to try and clarify how we think about these things differently in our communications going forward, but I hope you'll see that we're continuing to maintain that financial sustainability discipline around our mature businesses while investing in those dramatic growth opportunities from a balance sheet perspective, and we'll look to keep that going.
Okay, so with that, I think I'm going to invite my colleague, Juan Andres, back to Moderna, but also back up here on stage to walk through how we've been investing in our manufacturing infrastructure.
Thank you, Stephen. Good morning, everyone, or good afternoon, good evening if you're listening to us from other parts of the world. For those of you that are here, if you would come here in the future, probably we won't be able to host you here because this will be production area where we will be making medicine for patients. But before I go into more details for intismeran and talk a little bit more about the facility here and what is what we're doing, allow me for a couple of minutes to double-click on the network that we have for infectious disease. Obviously, our main site, which is a campus right now, is at Norwood, which is approximately an hour from here, depending on traffic, but it is close. That allows us to do a lot of learning and a lot of support from each one of the areas.
It is not by chance that this is close. Stephen touched a little bit on the presence that we have in Canada, the U.K., and Australia, where we have long-term agreements to support domestic supply. What I can tell you is these three sites have been built identically. When I say identical, they are identical. Same location, same sizes of equipment, the same feel, and that allows us for the platform for replication, for validation, for avoidance of surprises that are very, very important when you do these type of things. They are focused on operational excellence, they are focused on flexibility, and that is very, very important in infectious disease, as you know very, very well. You're here in Marlborough. As I said, this site has been built specifically for the purpose of intismeran.
The reason we need this, it is a personalized product. It is one batch equals one patient. The majority of the products that are out there in the market, they are scaled up. Basically, as you have demand, your batch sizes are bigger in order to supply more patients. In this case, we do not do it, and we call it, we scale out. This is one of the reasons we build this plant. You are here, and this is the scale-out area that we are going to be having. The production area that is over there is already built, and it is already making product. We build this facility with the design on end-to-end operations. You are going to see it a little bit later, but our focus is going to be on the speed, the scalability, and flexibility.
As I mentioned before, we can expand the capacity within the site. It is being built also for efficiency, and we have been making product at this scale for years. The amount of learning that we have been able to gather allows us to put automation, robotics in the design of the skids that is going to help us going forward. That will allow lower production cost, and obviously, as we generate more efficiency, as we make more batches. The site is ready. It began to produce in August 2025. We have produced hundreds of batches already, and we are on track and ready if we get approved during 2027 to go into commercial launch. This will be the commercial site.
We are GMP ready, Good Manufacturing Practices ready, and it has the latest generation of skids. I will expand a little bit here in a couple of minutes, and we can do phased addition of capacity as we need it. You will see it too. What is the supply chain? How do we go? Stephen mentioned a little bit the patient onboarding. We do the sample collection, and we do the sequencing, and then as soon as we have the algorithm and the sequence for the mRNA, the activity starts on this site. This is where we produce the batch. All the physical activity to produce the batch is here, and it is integrated.
We do not ship outside to be doing, for instance, the prefilled syringes. They are made here. We finish the packaging. It is integrated, and when we have the final product, it will be ready for the patient directly. We will deliver to the healthcare facility, and then we will have the patient dosing. What we are targeting is approximately six weeks, what we call needle-to-needle, and we are still trying to go and become more and more efficient as we go along. There are three levers that we are using to scale up or to scale effectively or efficiently.
One is the compact equipment. You will see a couple of pictures on that. The automation, as I mentioned before, and then we are going to be very disciplined in the way we expand capacity. It is going to be simple. We have this space, and as we expand, it will be in the same location, so we can do that very fast. Let me start with the first one. Obviously, and this is intuitive for everybody, think about every batch is one patient. The smaller the footprint where you can produce that batch for that patient, the better and the more efficient you will be.
We started with what we call the first generation. We started in 2019 to make batches there. The supply obviously was for the clinic, and those skids are the previous generation. This is, again, technology. Stéphane was alluding to it at the beginning. This is the technology platform. You do not make previous generation devices once you have the new ones in place, so we are decommissioning the previous equipment. That is our baseline. We are in Generation 2. This is what you are going to be seeing later. This is here in Marlborough. We are going to continue supplying to the clinic, plus commercial.
They are semi-automated skids. They are in a smaller footprint, and that is 50% reduction from the baseline in terms of the cost trajectory for this piece of the production area. We are already working on Generation 3. That will be here as well. You always work for the next generation. The next generation, we want it to be more compact, faster, more automation, and build on the experience that we keep gathering. I will go on that one a little bit later, and that will be another 50% reduction in terms of what we do in terms of efficiency. Now, why I wanted to bring automation, productivity, and how it is important. Let us start with automation. Again, we did not start now. We started years ago.
One of the things is I spent most of my career in production areas where paper was the base of what you were doing in terms of batch record, in terms of procedures, in terms of things that operators needed to fill out. In some cases, batch records that were this thick. From the beginning at Norwood, this is years ago, we banned paper at the production areas. It took us a while, but everything is automated. Now, when you digitize everything, you can access the data in a way that allows you to connect dots. It allows you to see the inefficiencies in the system. It allows you to process things faster. It allows you to be predictive, and it allows you to start now AI and use it for a number of different things. It all started there, and we continue building on this.
I mentioned a couple of times about the modular production. What you see there at the top is just a representation of what we call the production unit number one. This is, we can make lots of batches there already, and we can start making two to seven production units. One of the reasons we do not have is obviously we want to allocate capital in a smart way, but the other way is we continue learning. As we continue learning and bring new generations, we will be able to improve the process. That is the idea, or this is the way we are going to be expanding. Let me stop. We have already made 5,000 batches, approximately. 5,000 batches for 5,000 patients. This is for clinical trials. We will launch.
I was just looking and going into my memory banks. I did a couple of questions in the web associated with 5,000 batches. If you think about a blockbuster in the market right now that has to go and make 5,000 batches, on average, it would take between eight years and 15 years to produce 5,000 batches. We have done it. The amount of learning, if you put together the automation, our ability to do the robotics, our ability to do the AI, plus the experience that we are gathering, this is going to help us improve this as we go along very, very fast.
Three key takeaways. We have an established network that supports infectious disease and the vaccine supply. We have specialized capabilities like the ones that you are going to be seeing here today, and this is built for purpose here. We are going to have a discipline and scalability, not only for intismeran, but also for all the other modalities that we have. That technology is industrialized. We keep building on it, we keep learning on it, and we keep improving it. Thank you very much.
I will pass it to Jamey for the next session.
Thanks, Juan. Good morning, everyone. It is great to see everybody. Thanks for joining us here in person or via our webcast. I want to get into our financial strategy moving forward and elaborate a little bit upon what Stephen talked about in terms of how we are thinking about capital allocation. Before doing so, I want to revisit what we said at last year's Analyst Day. I am going to walk through each one of these, but we talked about growth, we talked about margin expansion, how we are evolving our capital allocation, cost and cash management, and I am going to walk you through each one. We said we were poised to deliver up to 10% revenue growth in 2026, and we had numerous growth drivers thereafter. As we reported last week, we now believe that we will be up 15%-25%.
As I mentioned last week, the good news is it is very broad-based growth. It is across the globe for really a few reasons. One is we are seeing more stabilized vaccination rates. In the U.S., Stephen walked through it on his chart, but mNEXSPIKE now has penetrated 94% of our vaccines that we sell. That has really taken off in the year 2026. The strategic partnerships in the U.K., Canada, and Australia have really been delivering this year. We are excited that we have seen growth this year, and we continue to see growth moving forward. We talked about expanding gross margins. Last year, we did 55% from a gross margin perspective, and we said that we would deliver 10 percentage points over three years.
When we came into the year, we guided 61%, and with our recent guidance, if you take the midpoint of our revenue range, which is roughly $2.3 billion, and $800 million of cost of goods sold, that's about 65% gross margin. We basically did in one year the full 10 percentage points that we said we would do over three years. We said we would evolve our capital allocation more into oncology, and by 2025, we were at 22% of our total R&D was in oncology. This year, we expect it to be 37%. We continue to expand into oncology. We will continue to do so. I'll talk about our capital allocation moving forward, but a good improvement year-over-year. We said we would reduce our cash costs by 2027 to $3.5 billion-$3.9 billion, and that we would target break-even in 2028.
When we came into the year, we guided $4.2 billion, and then we just recently updated it to $3.8 billion. Essentially, we have already met what we said we would do in 2027 in the year 2026. Then we said we're confident in our future financial framework with enhanced liquidity. We ended last year with $9 billion in liquidity, and we anticipate that we'll be a little over $9 billion with ending liquidity this year, and I'll take it piece by piece. We announced this morning that we amended our Ares facility. I'll come back to that later and explain that. All of you know we launched a convertible offering, and we executed that at 0% interest rate with capped calls that protect dilution all the way up to almost a $400 stock price.
That gets us at an effective about 2% interest rate. But I want to spend some time on this $5.6 billion of what I'd call our core cash. When we came into the year, we guided $5.5 billion-$6 billion. Right now, you can see at the midpoint of our range, we're at $5.6 billion. But at the time, we did not know we were going to settle an IP litigation for nearly $1 billion . We are still hitting our original range even after paying almost $1 billion to settle that litigation. It's really due to the terrific performance across the teams. Revenue growth is up $300 million-$500 million. Cash costs are down $400 million. Our capital expenditures were hitting the low end, so we said $200 million-$300 million. We're hitting $200 million.
Then the working capital improvements that all the teams across the globe are delivering. We anticipate ending with a little over $9 billion in liquidity, which I think sets us up well moving forward. I just, for a moment, wanted to reflect on what we did this past year, thank the teams across the globe. They have continued to surpass my expectations, which I think positions us well moving forward. I think 2026 was an inflection point for us, not only for intismeran, which is why we're here and we'll talk about it, but also we have five approved products. I think our pipeline is more well-known, but also financially. I think in 2025, we stabilized our financials, and I think the trajectory of our financials in 2026 have certainly changed.
Obviously, we will have double-digit revenue growth, we have a more manageable investment profile, and we have $9 billion in liquidity. I think that is a true inflection point from a financial standpoint as well, not just from our pipeline perspective. Things have to change as well. As we look forward, we have new financial objectives, and I will walk through each one in a few pages. We want to build upon that renewed growth. I will talk through that. We want to improve the profitability in our infectious disease vaccine business. We will continue to be disciplined with our capital allocation, but we want to and need to invest in oncology and our emerging pipeline more. We will maintain a strong balance sheet. Let me walk through each one. Stephen already covered this chart, but I am going to start still with 2026, actually.
mNEXSPIKE, obviously with 94% of our revenue in the U.S., we have already captured the large majority of that. We can continue to bring mNEXSPIKE across the globe, and we will continue to do that. Our strategic partnerships. While it is a growth driver in 2026, we want to add new products to those countries, bring new products to those countries, vaccinate in different ways. We think that that can continue to grow moving forward. Stephen has already outlined, but we have four growth drivers in 2027 that I think position us well to grow come 2027. We are going to see where 2026 lands before we guide next year, so you can expect our guidance not until the February 4Q earnings call. I think we have good momentum here, not only in 2026, but we are positioned well moving forward as well to grow.
We talk about improving infectious disease profitability, and I think there are four levers on this page, and I am going to walk through each one. Revenue growth, I just touched on. The midpoint of our range is $2.3 billion this year. From a revenue perspective, that is 20%. Gross margin, we are hitting our 65%, and I think there is more to do. We have a lot of capacity across the globe so that when we scale, we will get volume leverage from a gross margin perspective, number one. Number two, there is more automation to put in, there is more productivity to drive. From an AI and digital perspective, I am going to walk you through an example on the next page on how we are expanding margins on the gross margin line.
R&D right now, of our $2.7 billion of R&D, roughly $1.1 billion of that is in infectious disease, and we continue to drive efficiencies there. As we have always said, those large phase III trials will continue to wind down, and so our R&D is either flat or down moving forward. Commercial and medical, we have got a sales force across the globe that as we add products to it, we believe we are well-positioned. We do not need to invest more. There are other things we can do to drive productivity in commercial and medical as well.
Just to go back to what Stephen said, we believe we are nearly profitable already, and we will continue to grow the revenue line and drive efficiency in here, and we will manage when we invest in another product, be it Lyme or EBV or everything Stephen laid out as we move forward and improve the profitability of infectious disease. Real quick, just as an example in terms of combining digital technology, sensor technology, and artificial intelligence on how we can make our P&L more profitable. We put a sensor in every box in every shipment across the globe to measure, one, the temperature that it is so that there is no excursions, and also to make sure that we are going to deliver on time from a customer satisfaction perspective. Once we have that, we can then intervene.
We have this cockpit that you can see on the upper left here that says, "Where is the product? Is there any risk that there is going to be an excursion and therefore it is going to miss from a quality perspective? Is it not going to be on time for a customer?" Then we can intervene. Right now, we intervene about a couple times a week to be able to save product or get it to our customers on time. We think that is a good example of being able to eliminate waste from a productivity perspective, but more importantly, to improve the customer experience to make sure that they get our products on time. That is infectious disease, and then Stephen talked about INT and what we call mRED, which is the rest of our portfolio.
Right now, we invest about $1 billion in both of those areas. Our baseline investment following the intismeran readout is that that is going to increase. You can see our baseline investment is increasing a little bit. But we will remain disciplined here. We will follow the data and understand what is happening from a clinical readout perspective. If we continue to do really well across our entire pipeline, we will invest more. If the data does not meet our criteria, then we will invest less, and that is how we are going to plan for this. But we are planning some uptick, and I want to talk about that in terms of what is our guidance for 2027. We expect that we will be about $4 billion in investment in 2027 across the entire company.
Now this incorporates infectious disease and everything. $3.8 billion in 2026, going to $4 billion in 2027. Then we anticipate this being in the $4 billion-$4.5 billion range. That is this baseline investment that we are increasing over the coming years, and we think that we will be within that range. That is kind of our planning assumption right now. This is clearly a change in the trajectory of what we have been doing over the last three years. But just to remind us, three years ago, we were $9 billion in investment, and in 2026, we were $3.8 billion. We obviously showed the discipline to take that down substantially while still investing in things like intismeran and the entire emerging portfolio, some of which we will walk through today.
W e think it is the right thing to do to make sure that we invest behind this landmark data and everything else that we have going on in oncology. Then we will maintain a strong balance sheet, so we will always monitor this. This is at the top of the house from a company perspective. We have to be mindful of it. I already walked through where we will be at year end, but I want to take a moment on what we did with Ares this morning. We really changed three things. We extended the duration from 2030 to 2031. The undrawn liquidity that we had, we had $900 million in undrawn liquidity at the end of last year. We had to make a decision on $400 million by November of 2027, and $500 million by November of 2028.
Now, all $900 million of that has no contingency, and we have that flexibility through November of 2029, which we think is great. From an interest rate perspective, we also dropped it. The overall blended cost, when you factor in the fact that the $600 million that we originally drawn is sitting in cash, is a little over 2% interest rate. We are excited about that. It provides a lot of flexibility. It almost serves as a revolver that a company that is cash flow negative cannot get. We will always have access to $900 million for the next three years, and we will evaluate this over time.
We will look at the health of the business as we de-risk the company, as we look at revenue or IP or whatever it might be, but it is nice to have this at a pretty cheap cost of capital. I just want to end by thanking our teams for the amazing execution that they have displayed over the last few years, but certainly 2026 in particular. I think this strategy is all about investing for value creation for all of our stakeholders, but most importantly, our patients and for our investors.
I think we are poised to actually be able to invest behind that with $9 billion and a changing trajectory of our financials. At $2.3 billion of revenue this year and moving up, and a cost base of about $4 billion, we have the ability to invest behind this landmark data, as well as everything else we are seeing in our portfolio.
With that, I think I am going to open it up to Q&A and invite my colleagues back up.
Okay. We will take questions from in the room first. Please introduce yourself and tell us what your affiliation is.
Great. Thank you. Tyler Van Buren from TD Cowen. Thank you so much for having us here. Have just a couple questions, maybe for Jamey or Stéphane. Understand you are not guiding to 2027 yet, but qualitatively, do you think Moderna can achieve that 15%-25% revenue growth year-over-year in 2027 again? Could it be higher, or should we be a bit more conservative? Did this year include one-time benefits? The second question regarding manufacturing. The one production unit that is online, does it have five stations, and how long is each station locked up for the manufacturing of each product as we think about how many products can be produced in a year?
Yeah, I will take the first one. Thanks for the question. I do not think a wise planning decision is to plan 15%-25% per year in our company at this point in time, at least as it pertains to infectious disease. INT, we will see what happens, based upon the commercial approval of that, but I am just talking about infectious disease. We did not have any pull-in of anything. I know that was a question out there. This is really fundamentally broad-based demand, as I just walked through. Vaccination rates have stabled. Our execution has been terrific. It surpassed my expectations. If you look at mNEXSPIKE, we thought that that would be a trajectory over coming years. We got to 94% of our revenue in 2026. That was not our planning assumption. We thought that that would increase.
I think last year we were 56% or something like that of our total revenue. That is really, we captured a lot of that in 2026 as opposed to over the long term. I do believe that the infectious disease business will grow. We are adding flu. We are adding combination vaccine. You can see the geographic footprint that we will expand upon. Our strategic partnerships are solid. Stephen talked about the multi-year aspect of that. We will add products to those. But I do not think a 20% average growth rate is the right planning assumption. I am not guiding right now, but it will grow, but I do not think that that is a fair planning assumption for us. Unless everybody surpasses my expectations.
Let me address the manufacturing piece. This is a process unit train. You go through the different stages until you make the product. We can make several thousands in the current environment that we have right now. As I said before, it is expandable very, very quickly to a number of different lines as we go through. It is ready to be expanded. Look at above you. The infrastructure is there. All we have to do is finish that up. We understand the equipment. Several of those pieces of equipment are going to be identical. Several of them, depending on where we go and how fast we need to go, we could go to the next generation as we go and improve even further to what we've done right now.
Hey, Mark here for Salveen with Goldman Sachs. You've discussed a six-week or a turnaround time from sample collection, or like the inject vein to needle-to-needle time. Where do you think is possible? I know you said you wanted to go for less than six weeks, maybe two or three years post-launch, and could you ultimately get to maybe four weeks? What do you think the current rate-limiting step is, and how do you plan to ship the samples globally post? If you could expand on that. Thanks.
Different things. When you talk about needle-to-needle, you cannot only look at what is your best cycle time that you're going to be achieving with one specific patient. You need to look at what is going to be the queue of patients, how the demand is going to start fluctuating. When we talk about the six weeks, that is where we think we are going to be achieving to start with. That obviously is something that we are going to improve over time. Volume is going to help us. The flexibility that we are going to be bringing future innovations will help us as well. We call it turnaround time. That is our main focus.
The faster we are is going to be better not only for patients, but also our efficiency is going to get better and better. That's why I insisted on the automation. That's why I insisted on the AI. Having all of that already in place and automated is going to help us move forward. Obviously, we need a scale, we need numbers. That is going to take us there.
Hi. Morning. Jarwei here for Geoff Meacham at Citi. Two questions. Maybe one on the updated annual cost framework of $4 billion-$4.5 billion. I guess maybe if you guys could talk a little bit about how much maybe downside or upside flexibility there could be if maybe some of the renal or bladder or lung data come out better or perhaps not quite as expected. Then the second, maybe a clarification on the manufacturing. Could you maybe give us a sense of where the delta may still lie between the 64-day turnaround time we saw in the phase III clinical trial versus the six weeks that you guys are aiming for?
How much of that lies outside manufacturing under your control, and how much of that maybe is within some of the clinical trial sites or maybe in the future, the patient and hospital sites that maybe could be further streamlined? Thank you.
Want me to take the first one? Yeah, so on the $4 billion-$4.5 billion, remember, we've put in a baseline increase, and that is primarily for intismeran. We are expecting, after this data, to increase our investment, including for RCC and others. I think to your question, how could you get above $4.5 billion? I think that's probably outside of intismeran. If everything is working across cancer antigen therapies, if our entire pipeline's working. But we've already put some amount of money in for that, but if literally everything's working, perhaps you could get above $4.5 billion. But intismeran has been provided for in that guidance.
It is already driven by performance in terms of the pipeline, and it is not fixed cost. Those are decisions we will make based on data.
Well, let me start addressing the physical part of the manufacturing. Stephen will address a little bit some of the other parts of the process. Think about before we had the generation one, and we were doing clinical trials, and we were doing them in Norwood, and we achieved certain cycle times. We have moved here. We are in a new generation of equipment, and we had to plan and get this site through the learning curve. Even with that, we have achieved a substantial improvement. I like our chances. We will continue doing this, and we will continue progress.
I am not going to give you a very specific number in terms of what we can do, but we know we can do it faster on average of what we are doing, which is not the measure of one single patient, because you need to go and you need to queue some of those things.
I think David will come up later and talk through the overall clinical trials, but I will highlight The New England Journal recent publication. You can see there is a distribution of timelines for delivery. There are patients that receive their doses very early, and there are some that receive it late, and the median is the one that you are describing. When you think of that distribution, that means we have demonstrated things can be very fast, but we need to work on the things maybe beyond our control to get even more effective at getting doses there faster. The consenting process as part of clinical trials is different. Getting tissue out of labs was different when you did not have an an approval, there had not been a change of standard of care.
Hopefully, we will be able to shorten those timelines down and really get to the critical path is the manufacturing process where we think we are reliably delivering very quickly. There is always going to be things on the back end as well about getting the doses to patients, and there is always going to be reasons why a patient may not receive a dose, misses an appointment, whatever it would be, staffing issues, and those will kind of drive the tail of that distribution. But our goal post-commercialization launch is going to be to tighten that all up to that critical process that Juan described, where we are really confident we are going to be on path and maybe even shorter than six weeks.
Yeah, and maybe just to add another point to what Stephen and Juan described, don't think about the turnaround time as one magic thing we have to make happen that is very, very risky and might never happen. This is not how manufacturing works. It is dozens of little projects that the team is working on. Some might happen in two months, some might happen in two years, some might happen in five years. There is a lot of things we are doing to really think about all the pieces of the process and how do we keep shrinking and shrinking it. Because as Juan said, it is only good for patients. It is great for capacity because you have a very easy rule math. If you can do half the turnaround time, you get twice the capacity.
It is not one thing, and we have already done a lot of progress, and you have no idea how much time we are spending on it and how passionate we are and how many opportunities there are. But it is going to take time. It won't happen next week.
Hi, Andrew Tsai from Jefferies. Maybe a question for Jamey again. Because INT could be approved next year, we need to shore up our model. So can you just remind us one more time the P&L calculation of how this all works? You share cost, COGS, OpEx. How does this all get recognized in your income statement, and do you book INT-only revenues or INT plus PD-1? I am curious about that too.
Great question. Thanks, Andrew. I will caveat by saying we still are working with our auditors to make sure that this is all the way we believe it will go. Yes, we will ship the full product. We will manufacture it here. We will then sell that to Merck, who ultimately will distribute it. There will be a sale at the outset. When we ship our product, there is a title transfer that goes to Merck. There will be some margin on top of that. That will be point number one. Our expectation is over time, as batches are sold ultimately and administered, there will be some portion of revenue along the way also.
To answer your question in terms of what does that basically calculate to, it basically gets to something like 60% of the ultimate price that we would recognize on us, because it is half of the overall revenue or profit, plus some markup on our COGS is what we will ultimately get to, but it will be staggered over time. Hopefully that helps answer the question.
Alex Hammond, Wolfe Research. Thanks for the question. On the flu launch, the commercial progress has been really impressive. Can you kind of walk us through how those conversations have been going? What learnings can you apply to 2027? Where are you in discussions with the FDA on the COVID flu vaccine as well? Thank you.
Yeah. First on the flu, thank you for that. We started the year with, we did not even have a PDUFA date, and we were going into a review process. For obvious reasons, most customers signed up most of their demand. But we wanted to make sure they were aware that there were reasons they might want to consider additional product, and ultimately, we think those resonated. There was some space left in for them to, if you will, get a trial year underway. Mostly it comes around, we think, the superior profile of mFLUSIVA. When you look at the relative efficacy, when you think about the role of egg-based adaptations and mutations in driving mismatches and decreased vaccine effectiveness performance, that was a topic of discussion, frankly, at the VRBPAC with the FDA.
It was a subject of discussion during the review process and something we've talked a lot about that we're proud about. The majority, 95% of enhanced vaccines available in this country are actually egg-based, so there's a gap there. That has an impact on efficacy, but it also can impact supply. We happen to be in a year this year as well, which happens pretty regularly, where there's been some challenges to supply of the egg-based vaccines. That often happens, that's not a surprise to us, not something anybody roots for. But it relates to that manufacturing process not being quite as reliable as the egg-free processes like we have with mFLUSIVA. Nothing matters more to customers than the stability of that supply. When they launch their campaigns, they can't launch it with half the doses they need.
They need all the doses they expect to have for the year. So for a lot of reasons, we found customers in the United States interested in having an alternative, and one with the profile that mFLUSIVA brings. We're excited to give them that chance to try it this year, because that really sets us up for contracting discussions in 2027 that are based on not just an idea, but they've had it in their hands and they've seen what we can do. As far as the flu COVID product, we have had a lot of activity with the agency through August and September, in particular getting flu launched, as we just talked about, approved and launched with an annual strain update, first ever for an mRNA-based flu vaccine.
We had to get the COVID products through their annual strain updates in August. As you can imagine, when there's a limited number of folks, they need to work through those things that are most important. We're now turning to the question of the combination product, flu and COVID. We do believe that there's a strong case based on flu's approval and mNEXSPIKE's approval that the combination product should be considered for review. We haven't had a chance to ask that question yet because the calendar was pretty full, both for ourselves and the agency, but we're doing that in the near term.
Hi, Moderna team. My name is Courtney Breen from Bernstein. I really just wanted to probe a little bit more on the manufacturing scale kind of components. You spoke about how the next generations are going to improve that gross margin perhaps over time. You've also spoken about how if you can get faster for the individual patients, you can perhaps have more throughput on the individual platforms that you have available. Can you just help us also think about what happens as you scale the number of patients? For example, launch year one versus launch year two, let's assume the generation is still the same in terms of the manufacturing, but you've doubled or tripled your number of patients that you're able to treat.
Are we going to see kind of gross margin efficiencies there like we do with other traditional products that scale up rather than scale out? Or how should we be thinking about kind of the patient contribution and kind of the volume contribution to efficiencies?
Look, this facility can make tens of thousands of patients, and we are going to stage the expansion depending on how the new indications come, how and what are the numbers when we launch, et cetera, et cetera. We can do that very, very quickly. Of course, as productivity goes or increases, we expect to have gross margin expansions as we go along.
Maybe just to-- Can you hear me? Maybe just to add a little bit of color. There's a lot of things. First, as you see this facility, as we described, there's only one suite built. We can build six more. So you have a side of a factory that's of course fixed cost, including depreciation, the labs, and so on. Then as we talked about the turnaround time, we are working on everything to shrink that time, as you said, that will improve capacity. But also raw material costs, raw material usage. It's just a lot of things that go into the final cost of a product that we have not talked about yet, but that we're working on all of those things.
Because we are very clear that the more we can drive the cost of goods of this product We're going to be doing this product for a very long time, as we said. So the appetite we have to invest behind it, because first it's the right thing for patients to get them the drug faster, and then the value it has on the company in term of just financial performance is really important. You need to be assured that we're very looking at suppliers and reducing the cost there. Even the use of products, the testing, the machine, the cycle time, we are looking at everything.
As Juan said, we're going to learn quickly because we have so many batches made, which is very different from traditional pharma, where you learn slowly.
Thanks so much. Thanks for hosting this. Terence Flynn, Morgan Stanley. A couple for me. I guess just any comments, Stéphane, on status of FDA inspection of the facility here and confidence in clearance? Then you mentioned, we'll leave with the impression that this is not CAR-T. Just, can we assume that your cost of goods is going to be better than where the current CAR-T products are landing, which I think is around 70% or so? Thank you.
Sure. We're not commenting specifically about where we are from a regulatory standpoint with FDA. I will just point you to a few things. First, we're partnered with Merck. You should expect that Merck's quality team has spent time in this factory, and potentially has done mock audits, which would be reasonable to think about. As you know, because of our Norwood facility, which is now away, we've had almost annual FDA inspections, because we're in a seasonal business. The 483s have been either with no observation or one or two minor observation. We've had since the beginning of a company, I had the chance to work at Lilly in manufacturing for many years, so I wanted to make sure, and Juan was my buddy there, and we had a little manufacturing issue in 2002, I think.
2001, 2002 with the FDA, which he was at the coalface, I was just here to help him. There was a lot of things I learned the hard way in that experience that I wanted to make sure as we set up Moderna, we set it right from the get-go. Because you design things right, and again, remember, I'm an engineer, as you design things right, you have much less quality problems than when you try to fix the plane as you're flying the plane. Again, as you know, from the time we filed the BLA, the FDA can show up anytime they want. It's part of a process, and we look forward to welcoming them, inspecting Marlborough.
Your second question was?
Gross margin.
Yeah, cost.
You want me to take it?
Yeah, Jamey, you do on cost.
I mean, we are confident in attractive long-term margins with some amount of scale into this facility and everything. I think you will see it on the tour. When you walk through the tour, you will already see that there is already a lot of automation. If you think about what is here, we basically just need to get the overhead and some amount of volume through our facilities. Once we do so, we are highly confident that these will be pretty attractive margins.
I think to underscore that, I would just highlight, in the development program, we have been treating thousands of patients a year, 1,000, 1,500 a year. We have direct experience with the cost structure at a scale that we think is commercially relevant. I think we are working hard to make sure it is attractive, but we are confident that it can be.
It will be.
Hello, this is Adam here for Jess at J.P. Morgan. Thanks for taking our question. You mentioned you intervene batches a couple times a week based on the sensor feedback. Can you elaborate on what that means, as in, are the patients still getting the product on time? Will that increase as you scale?
This is specific to infectious disease vaccines, just so we are clear. Yeah. If we see a delay at an airport, as an example, and we want to change the route to a different carrier to make sure that it gets on time to a customer to improve the customer experience, that is an example of what we are doing. Or if it is sitting on a tarmac and all of a sudden we think that instead of 2 to 8 degrees, it gets to 9 degrees, we might be able to do something and intervene and say, "Make sure that we go back and change the temperature control." I think that is a reduction of waste. That is already We have waste in our $800 million of COGS. We have been actively trying to reduce that.
That is how we intervene, either for customer experience or to make sure that the batch is not lost.
To give you a sense of the logistics involved in a seasonal vaccine, we do 70+ million doses a year globally in seasonal vaccines. They are approved, as we were talking about in flu or COVID, weeks before or days before. They then need to be shipped out and show up so that everyone can go into their pharmacy that Saturday and get a booster if they want one. In the case of the United States, those are thousands of shipments happening within 24, 48 hours of approval. It is a massive logistical challenge to do that, as well as all the global work. We make sure that those products are there. What is remarkable is how consistently we are able to do that across COVID and now flu, RSV.
Tracking every last little one of those potential logistical challenges is one of the ways that we eliminate waste in the system. But we have not had situations, fortunately, and do not anticipate any, where the product is not there when a customer or patient shows up and wants to get vaccinated. I think the track record we have shown in the last few years across our full portfolio really demonstrates that.
Our flexibility is bigger than traditional egg-based vaccines. I mean, you need to decide in the first three months of the season or before that how many. I had the opportunity to work on egg-based vaccine on previous lives. You define what it is going to be, and if you miss it, you miss it big time. That is not our case. We can move faster, and we can go because everyone thinks about waste and going down, but think about going up and the possibility to react and be ready there for patients.
Thanks. Dina here from UBS on behalf of Mike Yee. Two questions for us. One about the INT filing. I know Stéphane had mentioned that you guys are working to get that filed as soon as possible, hopefully by year end. Seems like a tight timeline. Just wondering in terms of if that gets pushed into Q1 2027, wouldn't the launch necessarily be more of a 2028 launch? Just thinking about it from a modeling perspective versus 2027, or how fast can you launch upon approval? The second question is on Europe and the OUS respiratory business. Besides just COVID and flu, there is also the combo.
Maybe just thinking what is the split that you expect next year, especially as your competitor is going to be out of the market and you'll be able to negotiate and have more negotiation power there. What is the split between COVID, flu, and the combo that you would generally expect that we should have in our model, just given three different pricing points for each of those? Thank you.
Great. Maybe I'll take the first one on the INT process. We are confident that we're going to get the submission done this year. The variables on commercialization are as much out of our hands as in our hands. The FDA review process is a first-of-a-kind medicine. Is it priority or not? Yes, it was breakthrough, but there's a lot of things that we don't know about how that gets set up. Ultimately, the process of commercialization involves reimbursement and all the other negotiations that have to happen on the back end. As we and our partner Merck have said, we're confident we're going to get it done this year. That's the part we control. We're pretty optimistic about commercialization next year, given where we are in terms of those timelines. Ultimately, it's not just in our hands.
As far as the European opportunity for next year, I think we're obviously most strongly positioned and known as a COVID company. As that market opens up, there's lots of opportunities for direct commercialization in more traditional markets, as well as participating in tenders, where there's been buying year-over-year, 20+ million doses a year. As we set those up, I think COVID is going to be a place that we're contributing substantially. The second one is the flu-COVID combo, mCOMBRIAX, approved this year, doing the annual strain updates, the soft launch this year, and reimbursement work for next year. If we're successful in getting that product, from a market access perspective, approved by national insurance programs across Europe, I would expect that to actually become perhaps our lead product in many of the largest markets.
I think the third then, flu and RSV, for different reasons, we would expect to be smaller contributors. Flu will take more time. Many of the tenders in Europe are multi-year tenders, so there is less volume that becomes available every year. And honestly, we are much more focused on the flu-COVID combo product for our primary efforts. It is most differentiated. And then RSV remains the smallest volume overall in those markets. We have started to win with those tenders. As the RSV market gets built in Europe, we want to be a major player, but it is obviously the smallest of the four. So, I think some sort of mix of COVID and combo are probably the lead drivers of revenue for us in Europe in 2027.
Hi. This is Adi on for Cory from Evercore. Is there any role Moderna and Merck can play in helping hospitals who will be administrating INT? A lot of discussion at ESMO revolved around how tissue collection and discontinuation, because patients might skip a dose, revolved. And I think Dr. Long also mentioned that at her site at least, there was improvement in tissue collection. So, just wondering on what role. Thank you.
Yeah. I will start, and others will fill in if they want. There is an entire effort, that is what you are referring to, that specialty commercial effort. But there is a very large effort led by colleagues at Moderna as well as Merck to help educate and prepare the market for this behavior. We do not want it just to happen. We want it to happen fast and smooth and easy. That is practice-changing in some ways in terms of pathology labs. But I would just underscore what Dr. Long said. It has been our experience across the thousands of participants enrolled in studies, the first time you do something, it might be a little bit complicated. The 10th time, it is going pretty smooth.
And that is the kinds of education that we want to bring to bear. We are partnered with third parties, some of this will get presented later, that are actually going to be present, reaching out to those labs very, very actively, that already do that today in the diagnostic or sequencing space. And help us get that tissue out of those labs and into our diagnostic system, our sequencing system, so that we can do design work.
The good and the bad of the clinical trial program that we have run is that, as we highlighted previously, we are going to end up with about 4,000 or 5,000 people across histologies in over 40 countries that we will have had to have treated. We know what these challenges are. We work on them every day, and we are pretty confident about where we are in the United States, that maybe the first one and the first time in an institution might be a little bit of work, but we are going to get ourselves to that 10th one when it starts to run more smoothly. We are confident we can do that.
Hi. Harry Smallman from Rothschild & Co Redburn. Quick question on the manufacturing. When you are fully operational here, how much do you think you are able to produce compared to the addressable market? Is there capacity beyond melanoma?
We are not going to guide, I think, on the numbers that we expect. Think about going from one process unit line to seven. We will continue improving. I think Stéphane explained it very well. This is not only how efficient you come in the physical process. There are other things that will come to fruition. There is this part of new generations that we are going to be having. It is how much automation we are capable of doing. Again, I think the important thing is we will be able to supply tens of thousands of patients out of this place.
Yeah. I will just add one thing, which is, given all the variable we have in the models, there is a big range of what we think this capacity can get out of the system when it is fully at its best performance down the road. We will have to just make a business decision down the road, which will be a very happy problem, because it means many indications have been approved, to say, "Do we need a second plant?" We built this one in less than three years, so we would have to do that. It is just too early for us to say. There is a huge range, because again, as I say, it is not one thing, it is 20 different variables.
Depending on where we get into the improvement, we will see what will be the true capacity of this factory in three or four years. We will decide with enough lead time. As we get indications, we will review that regularly. We will have twice-a-year discussion with the board to think about, okay, do we need to pull the trigger and start a new facility? Again, you can do it in a de-risking way, like we did this one. We just built both the shell, because it saved us a year. No permitting, no nothing. The shell was built, and we just built the inside. There is a lot of things you can do to just manage risk, make sure you continue supply, and that you manage also cost.
Because the reason we built the facility like this, we could have finished the whole thing, but the first dose would have been really expensive. That was not a wise thing to do, so we built it in suites like this. We are just looking at the whole capacity, and if we over-deliver our best scenario on turnaround time and cost and everything, great, we can use that capacity longer. If we do not, and we are mid-case scenario, not the best-case scenario, we will trigger earlier on another factory. But that should not be a worry about whether we get into supply.
The learning is big. Let me give you an example. What we thought a couple of years ago our bottleneck in the process was, is different. We have fixed that one, and then we have gone to another one. What we see being the current bottleneck, we already have the equipment in place in storage so that we can go very, very quickly should we need to do that very, very fast. Those are just examples on how you can anticipate based on the reality, based on your improvement, how you are industrializing this more and more and more.
Okay, we have time for one last question.
Thank you. Daina Graybosch[audio distortion] from Leerink Partners. I want to understand the transition from Gen 2 to Gen 3, and maybe two questions there. Is this a custom miniaturization and automation that you are building versus working with other manufacturers and applying equipment and consumables that already exist? What are risks and opportunities with that? The second question is regulatory. I think we all got used to CAR- T. When you change to, let us say, automated, sometimes it requires an additional clinical trial. I wonder, can you give us some guidance as you change from Gen 2 to Gen 3, what is the sort of regulatory requirement for that? Thank you.
Okay, so let me start with the second one first. We do not use live cells like CAR- T does. Our product is different, and therefore, the need for those regulatory hurdles are different. When we go from Generation 2 to Generation 3, this is a technology question. This is something that we all are used in cars, in iPhones, and things like this. We are going to go from the current generation to the new generation, and we are studying in a very clear way what are the automations that we need to have, what are the flows. We need to de-risk that, so we are not going to go until we are ready. We want to have sizable improvements from Generation 2 to Generation 3.
I showed in the slide what is what we are planning to go to the next generation, and that is improvement in cycle time, it is improvement on people efficiency, it is improvement on turnaround time. Those are the improvements that we are having, and we are going through the generation. We are working with partners, but we are doing mostly the design inside, because we are the ones who know the process very, very well. We are working with some partners as well.
Yeah. Just very to add to Juan, there is also a know-how reason and IP reason, which is why we developed since almost the beginning of the company our own process engineering capabilities that are very, very deep. There is a lot of learning from what we are doing in Norwood, because it is still making mRNA, that we will apply also here, and that will miniaturize everything. There is a lot of the key parts, key components of those systems that have been designed by our teams. The assembly could be done by other companies, but all the critical know-how is all in Juan’s team.
I spent the majority of my life scaling up products. Let me insist on the 5,000 batches that we have made. I cannot remember any big, big product that actually made 5,000 batches. Think about the learning that we already have based on the strategy that we put in place and thinking that it is a platform.
Yeah. I am going to maybe one last comment too is, we are unique in a lot of ways. But one is, think of the questions we have been answering this morning about seasonal respiratory vaccines, managing tens of thousands of shipments around the world within a day of a seasonal update, and where we have to update all of the composition of those products and therefore the manufacturing process with them every year for regulators around the world. That is a unique sense of experience and capabilities when you think about change control in manufacturing to then bring to bear on, now I am going to do it for one patient one time, but I want to make sure that I do it 5,000 times, it will deliver the way we say it will.
We have a lot of experience discussing with regulators what it means to change our products from instance to instance. In one case, it is from last year's to this year's flu vaccine. In other cases, it is from this patient to that patient. For sure, things that are within the well-characterized and well-understood space with us and regulators, we will be able to do without clinical work. There may be things in the future, think of our two different COVID vaccines, that represent steps forward, we hope, in performance, and those might require clinical data. But many of the things we need to deliver cost efficiency are really in the former category, in the one that is well within the change control paradigm that frankly we execute every year as a part of our respiratory vaccines business.
Yeah. I will go back to one important basic thing. This is a cell-free manufacturing process. At the end of the day, there's an mRNA and a lipid in a vial, and you characterize it in terms of sequencing it for product identity and all the same specification that we do for the COVID batches and so on. There's no selling a product for shipping to a hospital. Zero.
Great. Thank you, everyone, for all your good questions. With that, we will take a 15-minute coffee break.
[Break]
All right. Good morning. My name is Rita Das, and I am the Head of Infectious and Rare Diseases here at Moderna. Today, I would like to share some exciting clinical evidence we have been generating across our respiratory vaccine portfolio, with a particular focus on real-world effectiveness and the impact of our vaccines on clinically meaningful outcomes. Clinical trials establish the efficacy and safety of our vaccines, but our evidence generation does not stop there. Real-world evidence allows us to understand how our vaccines perform in routine clinical practice, particularly against the outcomes that matter most, like hospitalizations and severe disease. It also helps us evaluate the durability of protection over time and assess the effectiveness in high-risk populations, including older adults and those with underlying medical conditions. Importantly, these data can help inform vaccination recommendations and build confidence among healthcare providers and public health decision-makers.
Our goal is to demonstrate not just vaccine efficacy in clinical trials, but meaningful impact in clinical practice. Today, I will share real-world evidence from our COVID-19 vaccine portfolio, including new comparative data for both mNEXSPIKE as well as Spikevax. Then I will turn to RSV, where we are learning more about the effectiveness against severe RSV disease and the durability of protection across respiratory seasons. Finally, I will discuss our planned large-scale effectiveness studies for influenza and our influenza COVID combination vaccines. Let us begin with COVID-19. We now have a growing body of real-world evidence demonstrating the clinical performance of Moderna's vaccines. I will start with a particularly compelling new comparative evidence data for mNEXSPIKE, our next-generation COVID-19 vaccine, and then show how those findings are supported across multiple independent U.S. healthcare databases.
We will also look at comparative effectiveness data for Spikevax, our original COVID-19 vaccine, against a protein-based vaccine. First, the new data for mNEXSPIKE, or mRNA-1283, our next-generation COVID-19 vaccine. This study was published just yesterday in the JAMA family of journals, providing timely peer-reviewed evidence for comparative effectiveness against Pfizer-BioNTech's COMIRNATY. mNEXSPIKE has a differentiated design, as you will recall. Rather than encoding the full spike protein, it focuses on the two immunodominant regions, the receptor-binding domain and the N-terminal domain, using just 1/5 of the mRNA dose of Spikevax. 2025/2026 was the first season for routine use of mNEXSPIKE, giving us an important opportunity to evaluate how this differentiated design translates into performance in clinical practice.
Importantly, this study directly compares the two vaccines, mNEXSPIKE and COMIRNATY, in older adults where preventing severe COVID-19 is most important. This was a retrospective matched cohort design using Veterans Administration health data designed to emulate a head-to-head randomized trial. We evaluated adults 65 and older who received either mNEXSPIKE or COMIRNATY during the 2025/2026 season with up to 150 days of follow-up. The outcomes included medically attended COVID-19, hospitalization, emergency department visits, and antiviral treatment. We also evaluated something unique here, hospitalizations for major cardiovascular events, or MACE, as an exploratory outcome. This study allows us to examine not just COVID-19 outcomes, but potentially important broader clinical impact for vaccination as well.
The analysis included 55,000 mNEXSPIKE recipients and 240,000 COMIRNATY recipients. This was a high-risk population. The average age was approximately 77 years, and more than 95% of people had underlying medical conditions, and approximately 85% of people had received COVID-19 vaccines in the prior season. We are evaluating comparative effectiveness in a population with substantial comorbidity as well as preexisting immunity, precisely where we want to be preventing COVID-19 in the real world.
Here are key results. This is a forest plot, so as you look at it, there is a vertical line, which is zero, and every point to the right of the vertical line favors mNEXSPIKE, and every point to the left of the vertical line would favor COMIRNATY. What immediately stands out is that every outcome on this slide favors mNEXSPIKE, with the confidence intervals excluding no difference. We observed 35.9% comparative vaccine effectiveness against medically attended COVID-19, and an even greater 47% against hospitalization with COVID-19. We also saw consistent findings across emergency department and urgent care visits, outpatient encounters, and antiviral treatment. But I would like to draw your attention to the exploratory cardiovascular findings at the bottom of the slide. We know COVID-19 infection is associated with an increased risk for cardiovascular complications, including heart attack and heart failure.
In this analysis, we observed a 39.3% lower adjusted risk for hospitalizations for these MACE events among mNEXSPIKE recipients compared to COMIRNATY recipients. This is particularly interesting because it raises the possibility that differences in protection against COVID-19 could have implications beyond respiratory outcomes. Since MACE was an exploratory non-COVID-specific endpoint in an observational study, this cannot establish causality. But the key finding remains that the consistent comparative effectiveness favoring mNEXSPIKE across clinically meaningful outcomes, including hospitalization, alongside this intriguing cardiovascular signal, warrants further investigation. As with any observational study, residual confounding remains possible despite matching and statistical adjustment. Differences in healthcare utilization or testing may affect outcome ascertainment, and the Veterans population was predominantly older and male. These are important considerations when interpreting these findings, but we are very encouraged by the consistency of the results across outcomes, particularly hospitalizations, and by these exploratory cardiovascular findings.
This is also why our broader evidence generation strategy includes multiple independent databases and study populations. To summarize, this newly published study provides encouraging comparative effectiveness evidence for mNEXSPIKE in older adults. We observed consistently favorable outcomes compared with COMIRNATY, with the greatest comparative effectiveness against COVID-19 hospitalizations. The exploratory MACE findings raise an important prospect for benefits for COVID-19 vaccination beyond the COVID-19 outcomes. These findings provide compelling comparative evidence for mNEXSPIKE, and importantly, consistent protection against hospitalization that I will show you across some additional data sources next as well. Beyond our Veterans Administration comparative effectiveness study, we also evaluated effectiveness of updated COVID-19 vaccines during the 2025/2026 season across several other large U.S. healthcare databases. These studies allow us to assess the additional protection provided by updated vaccination in routine clinical practice, including populations with substantial prior immunity.
We evaluated mNEXSPIKE across three independent U.S. healthcare databases, each contributing something different. Veradigm provided an early effectiveness signal in the season. Optum allows us to look at those findings and assess durability, and Medicare provides a substantial greater scale, an opportunity to examine those broader clinical outcomes like all-cause mortality or MACE. As you'll see, the data is remarkable in its consistency and protection against hospitalizations, regardless of the data source. Our first analysis uses the Veradigm electronic health records. This is health records linked to claims data, and this was a retrospective matched cohort study evaluating the updated COVID-19 vaccines in adults 65 and older. The outcomes included hospitalization with COVID-19 and medically attended COVID-19, comparing vaccinated to unvaccinated individuals. Again, an important characteristic of this population is the high level of preexisting immunity. Approximately 85% had received COVID-19 vaccination in the prior season.
We're measuring extra protection in an already heavily vaccinated population. This is what makes these findings particularly relevant to the current vaccination landscape. Here are our results. mNEXSPIKE demonstrated a 59.3% effectiveness against hospitalizations in adults 65 and older, increasing to 66.9% in adults 75 and older. We also observed meaningful effectiveness against medically attended COVID-19. You'll notice that the point estimates are numerically higher for mNEXSPIKE on the top than COMIRNATY in the bottom, particularly for hospitalization. However, these were two separate analyses against unexposed populations and not a head-to-head comparison like the VA study. We can't draw the concrete conclusions about relative vaccine effectiveness here. The key finding is, though, that meaningful protection against hospitalizations in older adults is present despite substantial preexisting immunity.
Next, we move to the Optum's database. This is another retrospective match cohort study using the Optum Clinformatics database, now in adults 18+ . We evaluated mNEXSPIKE effectiveness against hospitalizations and medically attended COVID-19. An important feature of this study is the ability to examine effectiveness by age and by time since vaccination, with the follow-up extending the full six months, the duration of the respiratory season. This analysis included approximately 385,000 mNEXSPIKE recipients and an equal number of matched unvaccinated individuals. The mean age was approximately 74 years. Nearly 80% had high-risk conditions, and 83% had received COVID vaccines in the prior season. Again, we're evaluating additional protection on top of a population with substantial preexisting immunity. In this longer follow-up, also allows us to assess the durability of protection over the whole respiratory season.
Here are the results. We see, again, approximately 60% additional effectiveness against hospitalization across age groups, including in adults 65 and 75 and older. We also observed approximately 30% effectiveness against medically attended COVID-19, consistent with the expectations of this lower severity endpoint. What I want to emphasize in this data is the durability. As shown in the lower left panel, protection against hospitalization remained evident through six months, with 63.2% effectiveness in that tail end, the 151- 180 days. The key finding is that sustained protection against hospitalization throughout the respiratory virus season provides further evidence of the clinical value of mNEXSPIKE. Our third analysis uses the Medicare fee-for-service data. This provides another independent assessment of effectiveness, but at a substantially bigger scale, and allows us to examine those broader clinical endpoints that we were talking about. The Medicare analysis evaluated mNEXSPIKE in adults 65 years and older.
In addition to hospitalizations and medically attended COVID-19, we examined exploratory outcomes, including all-cause hospitalization, cardiorespiratory hospitalizations, and major adverse cardiovascular events, the MACE endpoint that we were talking about with the VA study in the beginning. These broader outcomes are particularly interesting given the relationship between respiratory infections and cardiovascular complications that we see in flu as well. The Medicare analysis included a very large population, 1.3 million mNEXSPIKE recipients. Here are the Medicare results. Consistent with Veradigm and Optum, mNEXSPIKE demonstrated a 62.8% effectiveness against hospitalizations with COVID-19 and a 46.8% effectiveness against medically attended COVID-19. What is particularly interesting is that when you look at these broader clinical outcomes, you observe a 26% lower adjusted rate for all-cause hospitalizations, 26.4% for all cardiorespiratory hospitalizations, and 27.1% for this MACE endpoint.
These exploratory findings are interesting given that we know that there is a relationship between these respiratory infections and general health of the population, particularly among older adults. Again, these observations do not establish causality in this kind of study, but the key message is that we are seeing the same strong protection for COVID-19 hospitalization in Medicare alongside these additional exploratory signals across these broader clinically relevant outcomes. We have reviewed the results from three independent U.S. databases, and let us bring those findings together, focusing on hospitalizations, which remains one of the most important impacts. Here is all of these three studies that I showed you side by side, and what is striking is the consistency of the data from the three independent databases. Despite differences in populations, healthcare settings, and data capture, mNEXSPIKE demonstrated 60% greater effectiveness against COVID-19 hospitalizations in each analysis.
These were all absolute effectiveness studies comparing vaccinated individuals to those who had not received the updated vaccines. These were not designed to be head-to-head comparisons. But taken together with our newly published veteran study, we now have both comparative effectiveness evidence, along with this absolute vaccine effectiveness, that COVID-19 protection against, that mNEXSPIKE protection against hospitalization is incredibly consistent. To summarize, there are three key findings from our real-world effectiveness studies. First, mNEXSPIKE consistently demonstrated approximately 60% greater effectiveness against COVID-19 hospitalizations across these three independent databases, including in older adults. We also observed encouraging findings across broader clinical outcomes, particularly MACE hospitalizations, in both our veterans comparative effectiveness study as well as in our Medicare analysis. These findings are especially interesting given the known relationship between COVID-19 and these cardiovascular outcomes.
Second, we demonstrated sustained protection against hospitalization for the totality of the respiratory season through 180 days. Third, the consistency of these findings across different populations, databases, and outcomes strengthens our confidence in the real-world clinical performance of mNEXSPIKE. Together with our encouraging comparative effectiveness data, we now have a robust and growing body of evidence supporting the clinical value of mNEXSPIKE. Having reviewed our comparative effectiveness data from mNEXSPIKE against another mRNA vaccine, I would like to turn to a different comparison. The original COVID-19 vaccine, Spikevax, or mRNA-1273, against the protein-based vaccine, Nuvaxovid. This study, published in Advances in Therapy, addresses two interesting questions. First, how do vaccines with different platforms perform in routine clinical practice? Second, whether differences in strain selection may influence protection against COVID-19 outcomes. This was the 2024-2025 season, not this prior year, but the year prior to that.
It provided a particularly interesting opportunity to examine both of these questions. Spikevax targeted KP.2, while Nuvaxovid targeted JN.1. Both were consistent with FDA recommendations, but KP.2 was the more recently emerged variant and potentially provided a greater antigenic match. We are evaluating two differences simultaneously, vaccine platform as well as strain selection. While the study cannot isolate the contribution of either of these factors, it provides valuable real-world evidence of how these vaccines performed during the same respiratory season. This was a retrospective matched cohort study using the Optum database with approximately 104,000 adults. The study was specifically designed to be an active comparator analysis evaluating the outcomes between the recipients of Spikevax and Nuvaxovid over 180 days. We had about 70,000 Spikevax recipients and 35,000 Nuvaxovid recipients. 70% were 60 and older, and three-quarters had underlying high-risk conditions.
Here are the results. These are forest plots. As you look at the forest plots, estimates to the right of the vertical line favor Spikevax, and if anything was to be the left of the vertical line, it would favor Nuvaxovid. Once again, we see a consistent pattern favoring Moderna's COVID-19 vaccine. For hospitalization with COVID-19, Spikevax demonstrated a 40.7% comparative effectiveness in adults 18 and older, with a very similar estimate in adults 65 and older. Importantly, the confidence intervals for these estimates excluded zero. We also observed favorable results against medically attended COVID-19. These results are interesting because both the better strain match and the vaccine platform may contribute to the enhanced protection against the severe COVID-19 outcomes measured. Of course, this is an observational study, and residual confounding remains possible. There are also limitations related to claims-based outcomes ascertainment.
Despite these limitations, we are encouraged by the consistency and the magnitude of the findings, particularly the 40% comparative effectiveness against hospitalization. To summarize, Spikevax was associated with lower rates of medically attended COVID-19 and hospitalizations compared to Nuvaxovid in the 2024/2025 season, and these findings were consistent in older adults at greatest risk for severe outcomes. Importantly, this is one of the first large real-world studies comparing mRNA and protein-based COVID-19 vaccines with different strain targets in the same season. Together with our mNEXSPIKE data, these results provide further encouraging evidence of the clinical performance of Moderna's COVID-19 vaccine portfolio. Now I would like to turn to RSV, where real-world effectiveness is helping us answer two important questions: how effectively these vaccines can prevent severe RSV disease, and how durable is that protection?
RSV remains an important cause of hospitalization in older adults, and with adult RSV vaccines now in routine use, we are beginning to answer these questions using not clinical trials, but large healthcare databases. Clinical trials demonstrated the high efficacy of RSV vaccines against lower respiratory tract disease, but they were not powered to estimate the protection against hospitalization. Real-world evidence is what we would need to address this gap. We have already seen substantial evidence of effectiveness against hospitalizations for the protein-based RSV vaccines, and now we are generating the evidence for mRNA-1345, or mRESVIA. I will begin with real-world effectiveness data for mRESVIA specifically in the Veterans Health Administration. This study provides an important opportunity to evaluate protection against hospitalization in a population, again, with substantial underlying medical risk. We will look at two complementary areas of evidence.
First, real-world effectiveness of mRESVIA against hospitalizations and medically attended RSV illness. Second, what multiple U.S. studies are telling us about the durability of RSV vaccine protection across two respiratory seasons. This first study is mRESVIA-specific. It was a retrospective test-negative case-control study in veterans age 50 years and older. The primary endpoint was RSV-associated hospitalization, with secondary endpoints including emergency department, urgent care, and outpatient encounters. The study included a veteran population with substantial underlying medical conditions. Measured baseline characteristics were well-balanced after matching, supporting the comparability between the RSV-positive cases and the test-negative controls. Here are the results. mRESVIA demonstrated an 85% estimated effectiveness against RSV-associated hospitalization, with a 57% effectiveness against emergency department or urgent care encounters, and 65% against medically attended RSV illness overall. These are very encouraging findings, particularly in a population with substantial underlying medical risk.
The hospitalization estimate does have a wide confidence interval because very few vaccinated individuals actually were hospitalized with RSV. This study provides the confirmation in routine clinical practice of the effective protection that mRESVIA provides against RSV outcomes. As with any real-world study, there are limitations, particularly the small number of vaccinated hospitalized cases, which affects the precision of that effectiveness estimate. We are very encouraged by these findings. An estimated 85% effectiveness against RSV hospitalization is a strong result, particularly in this high-risk veteran population. We move to the real-world evidence across the field. Having established that, okay. We have data from four large U.S. studies: IVY, VISION, the Veterans Health Administration study, and the Kaiser Permanente Southern California studies.
These all are a composite of multiple RSV vaccines, and they all differ in design and population, but together, they provide important insights into the durability of RSV vaccine protection over time. They help us frame the question of whether RSV vaccination may eventually need to be repeated or revaccinated, or whether people need to be revaccinated, particularly among the high-risk groups. This slide shows us the effectiveness estimates across all of these studies. What is striking is the consistency of the findings in three of the four studies, showing substantial protection during the first season, followed by lower effectiveness in the second season. The effectiveness declined from 69% to 48% in IVY, 78% to 42% in VISION, and 81%-49% in the Veterans study. The Kaiser Permanente study was somewhat different, showing a more sustained protection.
While the findings are not totally uniform, three of the four studies show a consistent pattern suggesting waning protection for RSV vaccination over time. This raises an important question for the field to tackle, whether revaccination could help maintain protection, particularly in older adults at greatest risk for severe RSV disease. This question becomes even more important in immunocompromised individuals who are at greater risk for severe RSV disease. Several studies suggest effectiveness may be lower or decline even more substantially in these populations. For example, in the Veterans analysis, effectiveness among immunocompromised individuals was 69% in the first six months compared with 40% in the longer follow-up. Although the estimates vary across studies, the findings reinforce the importance of understanding whether revaccination could help maintain protection in the highest-risk populations.
S tepping back, RSV vaccines provide substantial protection against hospitalizations, but emerging evidence suggests that that protection may decline over time. This is leading to an important discussion in the field about the potential need for revaccination, particularly among older adults and those at highest risk. At Moderna, we have already completed studies evaluating both homologous and heterologous revaccination with mRESVIA, and we have demonstrated robust boosting of neutralizing antibody responses. These findings are particularly encouraging given the challenges observed in generating robust boosting with repeated doses of protein-based RSV vaccines.
And while we continue to learn about the relationship between antibody levels and clinical protection, higher neutralizing antibody titers are generally expected to be associated with greater protection. We believe these immunogenicity findings position mRESVIA well as the field considers future revaccination strategies, and we look forward to understanding the additional data that may be needed to inform these decisions.
Now I would like to turn to our planned studies in influenza and combination vaccines. Influenza first. We are taking a similarly rigorous approach to generating evidence for clinical protect effectiveness for mRNA-1010. Our objective is to evaluate how our influenza vaccine performs against an established high-dose influenza vaccine in older adults using outcomes that matter clinically, including medically attended influenza and influenza hospitalizations. For mRNA-1010, or mFLUSIVA, we are planning a cluster randomized effectiveness study in the U.S., adults 65 and older, targeting approximately 400,000 participants per season with one-to-one cluster randomization.
We have already demonstrated clinical efficacy for mRNA-1010 in this group, and this study builds on that evidence by addressing an important clinical question: How does mRNA-1010 perform against high-dose influenza vaccine in clinical practice? The primary endpoints will be PCR-confirmed influenza and influenza hospitalizations, and we will look at influenza A and B separately as well. We are already well advanced into planning the study with the preparatory activities underway this season, with a planned start for next season.
All right. Finally, I would like to turn to our COVID-flu combination vaccine, an area that we are really excited about. Our combination vaccine, mRNA-1083, has been approved, as discussed, in Canada and in the European Union, although it is not yet approved in the United States. We believe that the combination vaccine will offer an important opportunity to simplify seasonal vaccination while maintaining protection against multiple respiratory pathogens, and we are investing in a particularly large and rigorous clinical effectiveness study to demonstrate the value of this approach. This is our DAN-COMBO study, which we were very excited to launch a couple weeks ago. DAN-COMBO is a very large, pragmatic, individually randomized phase IV trial evaluating our influenza and COVID-19 combination vaccine against co-administered licensed influenza and COVID-19 vaccines.
The study is being conducted in Denmark and Spain over two respiratory virus seasons, leveraging population-based healthcare registries to capture individual outcomes. I want to emphasize the ambition of this study. We are using an individual one-to-one randomization in this very large population to directly evaluate comparative effectiveness against clinically meaningful outcomes. The primary endpoints include medically attended influenza and COVID-19 hospitalization associated with either infection. We will also evaluate virus-specific outcomes and the broader measures of healthcare utilization, such as all-cause mortality or all-cause hospitalization. The key feature is the combination of scale, randomization, and the inclusion of these clinically meaningful endpoints. All right. I would like to close with a few observations.
First, across our COVID-19 vaccine portfolio, we are seeing a remarkably consistent protection, a remarkably consistent body of evidence supporting protection from hospitalization, including encouraging comparative effectiveness for both mNEXSPIKE and Spikevax. Second, in RSV, we are seeing substantial protection against severe disease, while also learning more about the durability and the potential need for revaccination. Third, as we advance our influenza combination vaccine programs, we are investing in large-scale randomized studies designed to demonstrate effectiveness for these clinically meaningful outcomes. Across our portfolio, our objective is to generate rigorous evidence that demonstrates the clinical value of our vaccines and supports informed vaccination decisions.
Thank you, and I will now turn this over to Bill Schief to talk about strain selection and AI.
Hi, everybody. Let us see if I can see. I am Bill Schief, Vice President for Protein Design and Infectious Disease, and my team spans expertise in bioinformatics and evolutionary biology, where we actually make strain selections, protein design, where we design the amino acid sequences encoded by mRNA for our infectious disease vaccines and products. We make a lot of proteins and characterize them biophysically to understand their performance, and we have a structural biology team. We are using all of these capabilities in service of the infectious disease portfolio, but for sure in service of strain update. Today, I am just going to talk to you about some of that work and focusing on how AI, we are using AI to improve and accelerate the annual strain update process.
I think we are all on the same page, and Stephen already, annual strain update has already been discussed, especially in the question section, but I have this one slide to just remind everyone on the same page that both COVID and influenza rapidly evolve, and related to our vaccines, specifically what is changing on these viruses are the proteins on the surface of the virus that mediate infection of human cells. They are mutating their surfaces to escape neutralizing antibodies, and our vaccines are encoding those sequences for those proteins. The better matched our vaccine is to what is circulating, the more likely antibodies that our vaccine induces, or T cells, will cross-react and block the replication of the virus. The bar at the bottom says we monitor viral evolution and assess vaccine strains continuously. That is because these viruses, they are evolving all the time.
They are typically updated annually, but there is no guarantee for all of eternity that the viruses are just going to cooperate and do it that way. We need to be ready to actually put out vaccine whenever it is needed, and we are just trying to be ready for that. It has already been discussed that we have four, Stephen reviewed this, we have four seasonal vaccines, and that is five different antigens. Rita mentioned that mNEXSPIKE, which is 94% of all the Moderna vaccines in the United States, is actually a mini domain vaccine having N-internal domain RBD, and it is super effective, but that is different than the whole spike. When we are updating these antigens, we have got to update both of those COVID antigens, and also for flu, we have to update three different hemagglutinins for H3, H1, and B.
They don't always change every season, but we have to be ready to do that. That is, in my view, an amazing respiratory seasonal vaccine portfolio. I don't think any other company has this kind of portfolio. But it means that the annual strain update process is really important to Moderna. It's a core capability, and we're trying to optimize it all the time. As part of trying to optimize it, per Moderna's overall philosophy, we're always trying to innovate in the strain update process. You can think of the innovations coming in three different pillars shown here. One is on speed, in terms of continuous monitoring and evaluating emerging viral strains, and proactively making candidate vaccines and evaluating them, and I'll take you through that. Precision, and making sure we have the right antigen design, and it's well-matched.
Then in scalable manufacturing, Juan talked a lot about scalable manufacturing already related to INT, and those same kind of ideas apply. I'm not going to talk about them today, except for maybe a little bit at the end, but obviously, it can matter here to compress our manufacturing timelines. All of these innovations, and I'll go through some in more detail, are designed to allow us to keep pace, as it says in the bottom, to keep pace with viral evolution, to bring strain-matched vaccines to patients. As you might imagine, if you look at the different functions listed one, two, three, four, five, six, annual strain update is a company-wide effort.
It takes a lot of work from many different individuals and different teams, especially if you consider that we have four seasonal vaccines and COVID is updated annually, typically, and influenza twice annually for each hemisphere. It's a lot of work, it's a lot of coordination, it's a lot of dedication. You can also imagine there's a lot of room for optimizing such a complex process. I don't have time to go over all the different things, and I don't even know all the different places where we're optimizing, but you can look at what Juan and Stephen and even Jamey talked about, removing waste and improving efficiencies in INT, and you can imagine similar kinds of things are happening across the company for ASU.
One other concept that is happening across Moderna, even for INT, is, I think it's a very interesting effort led by Tracey Franklin, where her team is using AI to examine our workflows and the ways we work within functions that are shown in these boxes here, and also between functions, and trying to figure out how to change the way we work to get rid of what we call air gaps, places where there's friction, where there's rate-limiting steps, where we're just waiting for one person to read a document and make a decision. Looking for a lot of efficiencies, and I think that is a really cool thing to do organizationally. It's going to help Moderna generally, and it's definitely going to help ASU, so I wanted to call that out.
I'm in research, my team is in research. For the rest of the talk, I'm going to talk about how activities in research are trying to improve and accelerate the ASU process. Fundamental to what we do for strain selection is this AI-enabled platform that we call mStrain. It's a surveillance platform that, at the top level, does what the title says. It can distill thousands of circulating COVID-19 and influenza sequences from around the globe and perform multiple different analyses and distill those sequences into a few candidate vaccine strains that are most likely to rise to dominance and actually be recommended as a vaccine. We need to be able to do that in advance so that when a regulatory authority recommends certain strains, Moderna's ready to go, and we've prepared as far in advance as possible.
Scientifically, it's super interesting. I'm going to walk you through just a couple of things, but if you see the 365 days on the slide, that just means this is a continuous activity all the time. The sequences are coming all the time. Every week, we update the sequence, and mStrain redoes its analyses. It's fundamentally trying to answer the four questions listed there under that circle. What strains are circulating? Where are they spreading across the globe? How fast are they growing? In a sort of different flavor, how much immunity might different strains escape? I have a slide on that. It's a really important and very difficult thing to assess.
In the next couple of slides, I'm just going to walk you through a few of the principles we're using and methods we're using inside mStrain as part of the strain selection process. This slide is just showing a snapshot in time of the global distribution of COVID strains. Different colors correspond to different related sets of strains. You've got red covering most of the globe, and then there's some blue in Asia Pacific, and there's a few gray to indicate others. mStrain takes in public sequencing data from around the globe, and as I said, we update every week, and this is the fundamental basic summary that we see every week, what's circulating and where is it.
When you're doing an annual strain update, we at Moderna and also the regulatory authorities are most interested and concerned with strains that have global dominance, and that makes it obvious. You see red across the whole globe, that is likely to be the strain that you want to go for. If you see red and blue, as here, you have to answer some other questions. It does raise the possibility, and we use this in our thinking, we use this in our monitoring of the potential need for regional vaccines. This plot alone wouldn't tell you that you need regional vaccines. It depends on how related these two viruses are antigenically, and we'll get to that. This is just basic data that mStrain takes in, and we get this view. Very critical to selecting which strain should go into a vaccine are basically two features.
One is how prevalent is that strain globally? What fraction of all sequences does it represent? This graph is showing on the x-axis, it is the fraction of all the global sequences for one particular variant X, and you can see there is a 26%. It has risen to 26% as of that time. This is actually real data. The red dots are actual measurements that we have from sequencing data. You want to know the prevalence, but you also want to know the rate of growth. That is really essential for us because it would be relatively easy to wait until a certain strain was 70% of all circulating strains and say that should be the vaccine, but that is actually way too late because we need to have prepared, we need to be ready far in advance of that.
We are measuring the rate of growth at earlier stages, sort of like indicated here, to anticipate which strains might rise to global dominance. That is really important to give lead time for the rest of all the processes that need to be carried out to make the vaccine and supply it and do the commercial deals to sell it, like Stephen talked about. There is a lot here, but we look at growth ranking, we look at growth advantage for each strain, how much faster is it growing compared to all other strains, and what is the doubling time, among other features that go into these.
I mentioned that we do this proactively, so we are modeling this growth, data is coming in all the time, and as soon as we see indications that a strain, the mStrain, based on all of the inputs, considers that a strain has potential to rise to global dominance, we actually proactively make it. We gather at least pre-clinical data. We make the mRNA LNPs and gather pre-clinical data so that if it does rise to dominance at a certain point, or if a regulatory authority makes a recommendation that that kind of strain should be in the vaccine, we already have a lot of data and we are ready to go. Furthermore, gathering that data proactively and building data packages, we actually use in communications with regulatory agencies, and our data actually informs, I think it is pretty fair to say, our data can inform their decision.
I mean, we are actually providing a lot of data out in front. It is very helpful for the community. Moderna is really helping make sure COVID vaccines, this is mostly about COVID vaccines, similar concepts apply to flu, but the regulatory framework is a little bit different. Moderna is really being super helpful in the framework. This slide is talking about, I mentioned, are the red and the blue antigenically related? If you remember back two slides, there was the global picture. It had red virus, blue virus. A key question when you see two big co-circulating variants is, are they antigenically related or not? Meaning, if you would make a vaccine based on one of the two, would the antibodies induced by that vaccine protect against the other one or not? If they are antigenically related, then you only need one vaccine.
If they are not antigenically related, you might need to think about having two different vaccine antigens. To help, again, we need to assess that in advance. We need to do our best to assess that kind of information well in advance, rather than after the fact. The team has developed a machine learning model to predict how strongly, as it says in the black tagline under the title, how strongly a given virus will escape from neutralizing antibodies induced by a given vaccine. On the left of the slide, I am not going to walk you through all the data, but on the left of the slide, there is a table, and it says, "Method validated prospectively across four seasons." What that table is showing is, the community, including Moderna, selected vaccine antigens and had vaccine strains, were supplied and taken by many humans.
We gathered clinical data on the neutralizing antibodies induced by those vaccines and assessed, do those antibodies cross-react to other viruses? The new variant column is what they are tested against. Before the vaccine went out the door, mStrain predicted what was the immune escape risk, how antigenically related different viruses were, and that is in the predicted escape column. We gathered real actual clinical data and did assays on neutralizing antibodies from humans that received our vaccines, and that is the escape is in the measured escape column. You could just see the numbers are very similar. They are very closely matched. The very first time we did it, we predicted nine and the escape was 11, then the agreement got even. That was already pretty great, but then you see the rest of the alignments, 5.81, 5.82, 1.82, 1.78. It is actually scientifically pretty. It is very impressive.
The reason why that matters is because seeing that, this was not retrospective, this was prospective. We made a prediction and then find out how well we did, and we did this multiple different times. Seeing this good agreement gives us confidence in using this method, and that helps us make better decisions when we are proactively assessing strains and deciding what should we evaluate, what should we be prepared to send out as the vaccine. In some cases, what should we do a preliminary, a phase I clinical trial on? This method helps us make those decisions, makes higher quality decisions, and makes them more rapidly. On the right-hand side of the slide, I am not going to take you through it is just an example of how the data plays out when you are trying to decide what strain to use.
Well, that data is showing actually real data that we use to help select the current strain, XFG, which is in our current vaccine. I mentioned then, maybe I did not completely explain it, but we look for evidence of growth. We trigger proactively, we collect data on various candidate vaccines. At a certain point, it becomes evident, even to the regulators, that it is down to a couple of strains. One of these is dominant. Decisions are made beyond that. Ahead of that, another thing we have to do is assess, will these new strains express appropriately and present the antigens appropriately, express well, and fold appropriately from our platform? What is shown on this slide is that we are using agentic AI and wet lab analyses to rapidly evaluate vaccine antigens for emerging strains. We are actually not waiting for mStrain to make predictions about growth.
In some cases, it takes months to see evidence of growth. We're actually taking every sequence that comes in every week now, and we have this agentic AI layer, this process that's hooked directly up to mStrain. You see mStrain surveillance on the left. Sequences are coming in, updated every week. Every single sequence that comes into mStrain, then we predict the structure based on the sequence. We evaluate sequence-based and structure-based metrics for the folded antigens, and we can rank the different strains for how well we think they're going to behave or perform in a folding, in a structural biological sense. We can even design alternates. If we see a problem, we can automatically design point mutations that might adjust the expression up or down to keep it in line with where we're going. Then that leads to wet lab. This is an example.
This is a set of tools that we've basically just stood up, completely enabled by agentic AI, and we're really excited about it and making it better and better and better. To improve our ability to use agentic AI to recognize potentially problematic strains and engineer fixes to them, should that occur, we are actually developing custom AI models to do that better. In order to build, we're already using frontier large language models, all the best models that are available. How are we going to do better than that? We just signed a deal to do a collaboration with the automation and AI company, Lila Sciences, in which we are gathering bespoke experimental data on our seasonal antigens. We're starting with 1283, and this slide shows examples related to the mNEXSPIKE antigen, but we're planning on doing it for all of them.
We're gathering bespoke data on expression of natural strains, many different natural strains, and also the effects of all kinds of different mutations on many different strains. We're going to use that data to train new models that we believe will perform even better and allow us to more rapidly and with higher confidence make predictions about how different strains are going to perform on our platform. This is my last slide. We've gone through a couple different principles and methods that we're using and how AI is accelerating and improving some of those. We wanted to close this presentation with this slide.
Now we're pivoting to flu. We've talked a lot about COVID, to say that all of those accelerations and improvements that we're doing that I showed for flu, sorry, for COVID, we're going to apply for flu. We're going to combine that with mRNA technology and all the other manufacturing improvements that I kind of alluded to. The ambition of Moderna is to reduce the time between flu strain selection and vaccine supply down to two to three months. We think this is like trying to maximally capitalize on the advantages of RNA. In a way, it's a no-brainer to try to do this, and Moderna is the right team to try to do this.
You see the timeline, and Stephen mentioned the disadvantages of egg-based manufacturing. You see the timeline there, and if we get down to two to three months, we'll be much faster. And the real purpose of that is that it could enable late strain selection, which would mean typically better antigen strain matching, which should mean better vaccine effectiveness. Our vaccine is already very effective, but we are trying to dial it up even more. This is a difficult compression of the timeline, but Moderna has solved many, many difficult problems, so we will solve this. We think it is the right ambition for patients.
I will thank you, and David is next.
Thank you very much. It is clear that Moderna is a premier infectious disease vaccine company. In August of this year, Moderna also became an oncology company. It is my pleasure to walk you through that oncology program. First, I am going to focus on intismeran, and I am going to focus initially on the background, then I will summarize the phase III data for those who have not seen it, and then we will talk about what is coming up next. The immune system serves to detect and eliminate cancer, and it does this in what I colloquially call a front end and a back end, and it is a simplistic term that I have made up. The front end is the detection end, and here, neoantigens, which are encoded by mutations in the cancer DNA, either diffuse or are carried to a regional lymph node.
The regional lymph node has antigen-presenting cells that process those neoantigens, present them to T cells, and activate T cells. I call that colloquially the front end. The activated T cells then go throughout the body to search for the cancer and to kill it, and I colloquially refer to that as the back end of the immune surveillance process. Clearly, cancers can escape immune surveillance, and it can do this by defects in the front end or the back end. For example, there may not be enough neoantigens. Those neoantigens may not diffuse appropriately or be carried to the regional lymph node. The antigen-presenting cell may not process the neoantigens. The HLA type that presents the neoantigens may not match or may not be able to present those neoantigens. There may be an immunosuppressive environment from the tumor that prevents all of that from happening.
On the back end, we know T cells can become exhausted. Beginning in the mid-80s and in the mid-90s, the first evidence came that we could therapeutically activate the immune system, first with interferon, and then in the 90s with interleukin-2, and this began a long journey of, can we pull other levers in the immune system to reverse this cancer escape? The first major insight came at ASCO 2010, where YERVOY's phase III, ipilimumab phase III in metastatic melanoma was presented. For the first time, we saw that you can intervene and have a large treatment effect in metastatic melanoma. That was point number one. Two years later, nivolumab, ASCO 2012, demonstrated that you could reverse T-cell exhaustion via the anti-PD-1 brake and have activity in metastatic lung cancer. This led to the observation that immunotherapy was not only a melanoma-specific phenomenon.
Really important two landmark time points. Now, since then, there were lots of anti-PD-1, anti-PD-L1 phase III trials, and what was really remarkable here is the treatment effect sizes that we began to see. When I started in oncology over 20 years ago, we were designing phase III trials with a 22%, powering them for a 22% benefit. All of a sudden, with the anti-PD-1, PD-L1 class, we were seeing treatment effects that were greater than 30%, sometimes even 40%, and that led to a lot of excitement. Can we, as an industry and a community, academic community, can we pull more levers on the T cells to try and further increase treatment beyond what, for example, anti-PD-1 could see? The answer has essentially been no.
No matter what levers are pulled, except perhaps for LAG-3, there have not been other levers on the T cell to meaningfully improve over anti-PD-1. So the field essentially got to a point where they felt that the anti-PD-1, CTLA-4 has maximized what we can do. I propose, and the data I'll show today, that perhaps we have maximized what we can do on the back end, but there is certainly room on the front end, and I think that's what this phase III data shows here. What intismeran does is it analyzes what's in the tumor and maximizes presentation in the lymph node. It's the definitive way to maximize the front end. Here's how it does it. It's essentially two major steps. First, we take a biopsy of the tumor. We analyze it algorithmically. We identify the best neoantigens.
We turn this, and you'll see this later, into an mRNA cassette, into an injection. It's injected into the muscle of the patient. Now, we know from non-human primate studies, and we know from rodent studies that when you inject mRNA-LNP into muscle, actually it doesn't go into the muscle. A lot of it gets transported to the regional draining lymph node. Here, three things happen with our intismeran. First, we get neoantigen peptide expression and presentation in the exact cells you want it, in the antigen-presenting cells. There's no need to rely on diffusion or carrying from the tumor. Second, it's in the optimal environment. It's far away from the immunosuppressive tumor. Third, because we're activating CD8 and CD4 T cells, we are getting the optimal cytokine milieu that leads to activated killer cells. I'll show you some of this data in a few minutes.
Here more specifically is the process. Both tumor tissue and normal blood are taken because we need to understand what is a neoantigen specific to the cancer relative to the wild type genetic background of the patient. We sequence and identify the mutations. We design the cassette, and this, by the way, takes a few hours to design. We manufacture a single individual lot per patient, and you'll see that in a few minutes, and then, of course, we send it to the site and administer it. It's actually incredibly complex when you see it on paper, but it's amazing that we've been able to do this for 5,000 patients already, and I'm confident that Juan and his team will continue to improve this. Now I'm going to get to the exciting INTerpath-001 data, and I hope I'll convey why I feel this is so important.
Stage II and stage III melanoma. Pembrolizumab has done an incredible job. In two separate randomized trials versus placebo, versus placebo, intismeran prolonged relapse-free survival and distant metastasis survival, and the treatment effects were large. They were initially hazard ratio of 0.57 in KEYNOTE-054. With longer follow-up, it became 0.63. But essentially, a 37% benefit is incredible in both of these diseases versus placebo. However, unmet need still remains. 44% of stage III patients will eventually recur, and 33% of patients with stage II will recur. When we showed this data at ESMO a few weeks ago, one of the comments I heard was, "Yes, but this is melanoma, and everything works in melanoma." Actually, it doesn't. Here are two key phase III trials that should have worked because everything works in melanoma. PD-1 plus CTLA-4, we all know it works in melanoma. It works in metastatic melanoma.
It's better than PD-1 alone. Yet, in the adjuvant setting, increased toxicity, zero benefit. PD-1 plus LAG-3 works in the metastatic setting versus PD-1 alone. In the adjuvant setting, zero benefit, increased toxicities, and TIGIT as well. This was the background, and the hypothesis was perhaps if we intervened on the front end section by maximizing neoantigen, this could unlock more benefit than pembrolizumab alone. The trial was a very well-conducted, large, randomized phase III trial of stage II and stage III adjuvant melanoma. Patients were randomized 2:1 to six months of intismeran plus one year of pembrolizumab versus a blinded placebo, also six months, on the background also of one year of pembrolizumab. And the primary endpoint was RFS, and the secondary endpoint was distant metastases-free survival. There are certain populations I think are important because they provide some context.
The ITT, intent to treat, is always the primary endpoint for an experimental phase III trial. Here, there were 757 versus 380, exactly what you would expect, a 2:1 ratio. We had a pre-specified analysis called the modified intent to treat, which was for efficacy, and it was analyzing or comparing only those patients who actually made it to receive the blinded study drug, intismeran or placebo. Here in this case, 31 patients on the randomized to the intismeran plus pembrolizumab never made it to receive intismeran. They either had a recurrence or they had an adverse event, and 15 patients on the control arm never made it. So once again, a 2:1, exactly what you would expect to see. The ITT will measure the clinical trial outcome. The mITT will measure the true treatment effect of intismeran, and the as treated is the safety population.
91% of the patients who entered the trial had a full 34 neoantigen cassette designed. We actually designed cassettes for all patients. We only manufactured them for those who were randomized to the intismeran arm. And of those who were randomized to the intismeran arm, so of the 757, 99% had their intismeran drug product made. Only one patient out of that 757 did not get a drug product. The median time to first dose was about 64 days, and we've talked about that, and the median number of doses was about nine. Baseline characteristics were relatively well-balanced in some regards. It was a slightly higher stage group of patients on the intismeran arm, but generally well-balanced for a well-conducted trial. Now, here are the phase III results I'm going to pause on for a second, because to me, they are landmark.
In fact, ESMO 2026, in my mind, goes in the pantheon of ASCO 2010 and ASCO 2012. The treatment effect here versus pembrolizumab, a great drug already, is huge. 42% reduction in the risk of recurrence or death. 42%. It's incredible. At 24 months, there was a 12 percentage point difference between those who recurred versus those who didn't. This is the first time ever that a phase III trial for a therapeutic cancer vaccine has been positive, and the first time ever a positive phase III versus anti-PD-1 in the adjuvant melanoma setting has been positive. I'll come back to this treatment effect size, because I think this is the really, the most remarkable thing that I've seen in years. What do we think is going to happen to that hazard ratio of 0.58?
I think it's going to continue to get better with longer follow-up, and here's the reason. When we conducted the phase II trial, which was roughly similar, although only had stage III patients in it, no stage II, the hazard ratio was 0.56 at the primary analysis, with a roughly similar follow-up of about two years as the phase III. With longer follow-up, the hazard ratio actually improved, and you can see that reflected in why in the Kaplan-Meier above. I do expect the hazard ratio to improve beyond 0.58, although I will say 0.58, in my opinion, is an incredible result. In the modified intent to treat, once again, patients who actually received a blinded study product, the mITT hazard ratio is 0.51. This, I believe, is the true treatment effect of intismeran. It's a home run hit. It's a home run hit.
The DMFS, distant metastases-free survival, was also statistically significant, a hazard ratio of 0.62. I'll remind you that this includes stage II patients, so these patients obviously are going to have a slower event rate of distant metastases, and with longer follow-up, I think this will also continue to improve. One reason I do is we conducted a modified intent to treat on the DMFS as well, and here the hazard ratio is 0.55. To me, this bodes well for studying this in the metastatic setting, because essentially this is a measurement of can you control distant metastases. The subset analyses were all generally consistent with favoring intismeran, and I think most important, where the box is, that we saw roughly a similar treatment effect in both the high-stage patients and in the low-stage patients. So a very well-conducted and analyzed phase III trial.
From a safety standpoint, the adverse events were generally what we expected to see. The rates of severe adverse events and serious were roughly the same. There was a slightly higher rate of drug discontinuation on the intismeran combination arm compared to the control arm. We looked into this. There doesn't appear to be one underlying cause, just a lot of single individual events here and there. There were eight Grade 5 adverse events due to any cause on the intismeran arm compared to the control arm, and it's worth pausing here for a second to understand this. Of those eight events, those Grade 5 adverse events, adverse events leading to death, five of them occurred during the lead-in pembrolizumab phase before the patient even was eligible to receive the intismeran. Clearly, just bad luck, nothing to do with intismeran.
Two of those five were pembrolizumab-related. Once again, nothing to do with intismeran, and probably what you expect to see for the background rate of pembrolizumab. Three of those Grade 5 events occurred after intismeran started, but they were judged to be not related to either pembrolizumab or to intismeran. So eight Grade 5 events versus zero. I think this is very remarkable because if you read the New England Journal, the paper that came out today, you will see that there were 56 death events on the trial. Even with eight events tied behind our back, just by chance, against intismeran, there still is a trend in favor of overall survival, hazard ratio of 0.77. This is really remarkable. Just by imbalance, we had eight out of 56 events, yet there still is a trend in favor of intismeran. So really incredible.
The safety events, as I mentioned, were exactly what we expect to see. You can see the tornado plot for pembrolizumab-related events were generally the same, any grade and severe. The AEs for intismeran were exactly what we expected to see, most commonly pyrexia, injection site pain, and fatigue, and they were mostly low grade and transient. So an incredible RFS benefit, an incredible DMFS benefit, and a side effect profile that is very similar to an mRNA-LNP shot. In summary, we were able to demonstrate that intismeran reduces the risk of recurrence or death by 42%, which is really incredible. In the modified intent to treat, which is the true treatment benefit, a 49% improvement in RFS, benefit in most of the pre-specified groups, OS immature, and it is ongoing, safety consistent with what we expect to see.
Importantly, we delivered this at a global scale, and we have multiple ongoing trials. Beyond melanoma, what do we see coming up next? That is always a question, and there is still an unmet need in many tumors that are PD-1 sensitive, as well as, of course, in tumors that are not. I have listed here the tumors that we are currently studying. The common question, the most frequent question that we get is, will intismeran work in other tumors? I think the answer is likely yes, and here are my three reasons, which I will dive into deeper. First, T cells. T cells are the common cell that kills cancer, and I will explain to you why I believe the activation of T cells from intismeran gives us reason to believe. Secondly, the tumor mutational burden data from the phase II trial. I will share that with you.
Finally, the large treatment effect. I will end with that. So let us first deep dive onto T cells. T cells are the key killer cells of cancer, and we now know there are two ways to activate T cells. You can either, on the back end, reactivate T cells that are exhausted, that is anti-PD-1, and we now know today that you can also generate novel T cells on the front end. Both of these end up activating T cells. Any tumor that is sensitive to T cells, i.e. sensitive to anti-PD-1, we believe should be sensitive also to intismeran. I just want to, as an aside here. Something that I was thinking about yesterday, and it is still so remarkable to me, that there is a significant percentage of patients who will never respond to an anti-PD-1, but are still immunotherapy sensitive.
That's the key scientific insight we make from the data. We thought anti-PD-1s revealed the global breadth of immune sensitivity, and we know that's now only a fraction. INT plus pembrolizumab generates novel T cells, in fact, more novel T cells than pembrolizumab alone. The y-axis here is measuring the frequency of novel expanded T cells, and we measure it at four time points: baseline, after the lead-in of pembrolizumab, but before they get their blinded vaccine, sometime in the middle of their blinded vaccine journey, and then during long-term follow-up. You can see during that pembrolizumab lead-in, the number of novel T cells is identical, exactly what you expect to see. With pembrolizumab, it plateaus. You get all of your bang of novel T cells after the first cycle.
With intismeran, we continue to see an increase in the number of novel T cells as we administer the product. The next question is the increase in novel T cells associated with benefit? We think it might be. Here, the y-axis is roughly measuring the same number of novel T cells, and the time points are the same, but we've split it out into the intismeran plus placebo on one side. Sorry, intismeran plus pembrolizumab on one side and placebo plus pembrolizumab on the other side. Then we split up the two populations into those who have no recurrence, this is from the phase II trial, who have no recurrence, i.e., are having definite benefit, versus those who had a relapse, i.e., are not having benefit.
What we see with intismeran on the lighter color, those who have benefit continue to have an increase in novel T cells, whereas those who aren't appear to plateau. They appear to just get the pembrolizumab-like effect. On pembrolizumab, we don't see a similar separation, which is consistent with what we see with the overall no increase in novel T cells. I think this is one reason to believe. Now, the question has come up is, what are those novel T cells? Are those just random T cells that are being generated? This is an important question, and I think it is something we need to continue to study. We have been able to study it in seven patients. It does require a lot more blood donation from the patients, so it's not something that can be done in a large number of patients.
What we do is we take the seven patients' blood, and then we analyze them against the 34 neoantigen cassettes to see, do we see T cells in that patient's blood that can react to any one of those 34 neoantigens? What we see is, on average, one out of three neoantigens that we program are immunogenic, meaning they can generate reactive T cells. We see a mix of CD4 and CD8 T cells, and we see a range of between one to 18 neoantigens are immunoreactive. I think, by the way, this might be an undercount just because we're not sampling patients at every time point. I would say one out of three is the lower end of what we expect to see. What are these T cells that are recognizing? Well, they're polyfunctional, and that's an important thing to see.
CD8 T cells are probably the major killer of tumor cells, the most important cell. When we do flow cytometry, if you look in the upper right box of each one of these figures, you can see these T cells are interferon gamma positive and TNF-alpha positive. These are both cytokines that are important for functional T cells. You'll see one out of three, 31% of CD8 T cells that reacted to neoantigen 14 are polyfunctional, and 75% of the T cells, CD8 T cells, that react to neoantigen number 14 are cytotoxic, ready to kill. I think this is another reason to believe intismeran is generating novel killer T cells. We were able to clone, using single-cell seq, to clone individual T cells that reacted to the neoantigens, and we can then go back to whole blood and track them over time.
What we see is that for the first pembrolizumab lead-in, there's no change in these T- cell clones. After we administer intismeran, there's a sudden increase, and these clones remain present in the peripheral blood long after intismeran has stopped. Just as a side note, scientific note, sometimes people think there's one T- cell matching to one neoantigen. Actually, there's multiple, perhaps even dozens of different T cells in the blood that can recognize a single neoantigen. Just an interesting scientific observation. Secondly, let me talk about tumor mutational burden as a reason to believe. In the phase II trial, which we've presented before, one of the subset analyses was on tumor mutational burden, and we subsetted it into TMB high versus low or non-high. What we see is that the hazard ratio was roughly the same.
How does this inform or provide guidance for where else intismeran can work? Well, here is a plot of tumor mutational burden on the y-axis and a lot of different tumors on the x-axis. The ones in red are known to be T cell-sensitive tumors because they are anti-PD-1 sensitive. We have drawn a line where we believe that high versus low cutoff was from the prior slide. You'll see that if you focus on the lower end, you don't have to go all the way down to the one or two patients who have the lowest, but even if you focus on kind of the mid-lower half and draw an imaginary box, you'll see that it does still cover most of the tumors that we're studying.
I think this is one of the additional reasons to believe that intismeran can work in tumors that are a lower tumor mutational burden than melanoma. We have ongoing phase II or III studies in these indications. Finally, the treatment effect, and I think this is the most important piece, reason to believe. If you recall, I mentioned when I started over 20 years ago, hazard ratios of 0.75 were considered practice-changing. Here with intismeran, even in the ITT, not even counting the mITT, we're seeing a hazard ratio of 0.58 versus KEYTRUDA. If you look at KEYTRUDA versus placebo, the initial hazard ratio in KEYNOTE-054, 0.56. That was versus placebo. Just think about that for a second. Almost identical hazard ratios, one versus placebo, and the other adding on top of KEYTRUDA versus KEYTRUDA.
KEYTRUDA, of course, then went on to be very successful in other tumors, kidney, lung, and MIBC. We are studying them, but I believe that there is enough headroom with that efficacy for us also to be positive in those tumors. Here is where we are. Melanoma is in the process of being submitted, filed with the FDA. Lung cancer, the first phase III has completed randomization. This is in patients who never had any prior neoadjuvant therapy. We have two other lung cancer trials ongoing, including those who did not have a pathologic complete response after neoadjuvant, and stage I. Stage I lung cancer is an interesting study of ours because it is the study that is having intismeran as a monotherapy. I think that the field moved to believe that anti-PD-1s were required for any immunotherapy to work. You have to have an anti-PD-1.
I personally don't feel that is the case, and I think this is going to be the proof of concept that intismeran monotherapy can work. Then we have the renal and bladder cancer studies, which are fully enrolled, and those are, of course, event-driven. We have first-line melanoma, first-line lung, and then some other solid tumors as well. I am now going to turn from our individualized program to our off-the-shelf cancer vaccines, and that is because Moderna, 10 years ago, set on this journey to pioneer individualized neoantigens. Of course, we partnered with Merck, a very strategically important partnership. But we have now a number of other cancer antigen therapies that are off-the-shelf, and it is incumbent on us, as the company that pioneered individualized neoantigens, to also see if we can pioneer off-the-shelf cancer antigen therapies.
There are two main groups, tumor-specific. Those are ones that are only present in tumor and not in normal tissue. Frameshift mutations, mRNA-4194 for Lynch syndrome is one of those. Those are antigens that the immune system has never seen before. They are almost like foreign antigens. Then we have tumor-associated antigens. These are ones that are either cancer testis antigens, so these are antigens that are in immune-privileged sites and are aberrantly expressed in cancer, overexpressed antigens, and then tumor microenvironment-associated. We are proceeding in all of these, but today, I am only going to focus on Lynch syndrome. Lynch syndrome is a genetically inherited gene where individuals with Lynch syndrome face an elevated lifetime risk of cancer, usually colorectal cancer, if they are women, endometrial cancer, but other cancers. It is actually quite common.
About one in 300 people will harbor this mutation in one of five mismatch repair genes, and so that is about 1 million people just in the U.S. will have this predisposition. Current management is essentially surveillance. Aspirin, based on the CAPP studies, can be used to reduce the risk of colon cancer. As mentioned, it is due to an inherited defect in one of five DNA mismatch repair genes, and this leads to an an accumulation of what are called frameshift mutations. These frameshift mutations lead to an abundance of neoantigens. A patient with Lynch syndrome will develop a polyp or a precursor lesion. They have one mutant allele, and they have one normal allele. If that normal allele undergoes a second hit, the tumor will blossom into what is called MSI-high, microsatellite instability-high cancer, which will have all of these frameshift neoantigen mutations.
People who are non-Lynch syndrome can also develop MSI-high cancers spontaneously if they have a double knockout of one of their five mismatch repair, or if they have a DNA methylation event which leads to downregulation. Both of those MSI-high cancers have an overlap, whether it's spontaneous or if it's in a Lynch syndrome, there's an overlap in the frameshift peptides. In fact, even in pre-malignant polyps in Lynch syndrome carriers, there's an overlap with those frameshift peptides. Because of that overlap, it really creates an ideal situation for an off-the-shelf cancer vaccine, in this case 4194, which encodes 194 frameshift antigens. Based on processing, that's not only 194 neoantigens, because these are pretty large sections, they can actually encode hundreds of potentially different neoantigens based on how they're processed.
MSI-high cancer, whether it's due to Lynch syndrome or whether it's spontaneous, is a very sensitive anti-PD-1 disease, and hence, it is a very sensitive T-cell disease, and that's because of these abundance of frameshift peptides. Like you heard for intismeran, since we know MSI-high Lynch syndrome is a PD-1-sensitive tumor, that is T-cell sensitive, our hypothesis is, what if you could generate novel T-cells that never existed? Could mRNA-4194 have an approach as an off-the-shelf in what is a very large population just in the U.S., 1 million carriers in the U.S.? Here's the hypothesis that we'd like to test. Without any intervention, a healthy person who's a Lynch syndrome carrier has an increased risk once they have an adenoma of it becoming malignant. Can we administer 4194 before the adenoma is detected and actually intercept the cancer?
Not just the adenoma, colon cancer, endometrial cancer, but any cancers that could form. The concept of cancer interception. We have an ongoing first-in-human phase I trial that is in partnership with Oxford. Part one is the standard dose escalation, which we fully expect this to be well tolerated and to generate immunogenic T-cells. Part two is the interesting part. Once we have a dose, part two will actually enroll Lynch syndrome carriers. We'll do colonoscopy on them. If they have adenomas that are between 2- 10 mm, we will leave those adenomas in place, and that's considered appropriate care for a short period of time. You don't want to leave them forever. That will give us a window interception opportunity where we administer the 4194, and then we go in and remeasure those adenomas and then excise them to see what we can do.
It's a very nice window opportunity study to see if mRNA-4194 has the ability to intercept or act early on adenomas. I'm going to now turn in the last few minutes to T-cell engagers. There are clearly lots of T-cell engagers out there, mostly for hematologic cancers, growing for solid tumors. Most of them are targeting a single antigen and then targeting CD3. There is now evidence of dual tumor-associated antigen targeting, so you could call those a trispecific or at least two different targeted antigens. For the first time ever, with mRNA-2808, we have succeeded in generating three tumor-associated T-cell engagers in a single product, and this is by in vivo expression. What we do is we have the mRNA-2808 mRNA, which encodes the three separate T-cell engagers. We administer to the patient.
The patient then makes their own T-cell engager on their own, just in their body. We are targeting GPRC5D, FCRH5, and BCMA, which are all three validated targets. This is part of our Sentinel program. Myeloma is a crowded space, but this is a great opportunity for us to show that we can have an impact. I think by targeting three antigens, we potentially have the ability to have a best-in-class, most efficacious T-cell engager. The phase I trial is still ongoing. We have done dose escalation. The plan is to expand at a target dose. I am very pleased to announce that we were accepted for oral presentation at ASH, which is pretty remarkable for a phase I ongoing dose escalation trial. We are seeing multiple responses in heavily pre-treated myeloma patients, including those who have previously been treated with BCMA and GPRC5D.
I think that this is another validated modality for Moderna, and it leads us to explore what else we can do with our T-cell engager systems. To bring this to a conclusion, intismeran autogene for me has been a landmark in immunotherapy. I think this is the beginning of a long journey for us and for Merck. I think it is going to show us that there is additional headroom above anti-PD-1. I personally believe in other tumors in addition to melanoma. We will pioneer and explore whether cancer antigen therapies, off-the-shelf cancer vaccines, can work, including our Lynch syndrome program, which I just mentioned, but we have other approaches as well.
I really do believe Moderna will be the company to answer the questions of, can you develop an off-the-shelf cancer vaccine? I have talked to you about the T-cell engagers. We also have a cell therapy enhancer program, which I did not have time to talk to today.
I am now happy to bring up Stéphane.
Thanks, David. Just have three slides left. As I talked about this morning in my intro, we are really excited about what the team has been able to achieve and accomplished to build a true platform making medicines. If you think about Horizon 1, we have, of course, the infectious disease vaccine platform with five products approved today. INT oncology, we spoke about today a lot. Rare disease, as we said, we should expect, because it is a time-bound study, to have pivotal data from the PA program before the end of this year. David talked to you very briefly about some cancer antigen therapies medicine from that modality, and just spoke to you about mRNA-2808, our Sentinel program for T-cell engagers. The team in discovery is working on additional program that you should see pretty soon.
As we spoke about at Science Day in the spring, in vivo CAR-T with mRNA-6007 is advancing very quickly to the clinic, and we have also in vivo CAR-M, M for macrophage, that is also being prepared to get into the clinic soon. As mentioned, with LUCY, we are working on inventing the next generation of technology so we can keep inventing even more modality over time. What is interesting is for a long time, for last few years, people thought about Moderna as a Spikevax company. Moderna is not a Spikevax company. Spikevax just happened because there was a pandemic to be the first product that we brought to market. Moderna, since the beginning, our vision has been, if we can make one safe mRNA product approved, we should be able to make a lot.
I've said since day one to investors, this will be a zero-drug company, or this will be a company with a lot of medicine on the market. I'm so proud of what the team has accomplished to build those modalities, to build those teams with different time horizons, to build the capabilities, whether it's research, clinical development, manufacturing, and you're going to have a tour soon, commercialization, and all the junior function to support it. It is quite remarkable where we are, and with every platform, the best is yet to come. I look forward to the next five, 10 years of what this platform and this company is going to bring to the world. What is driving us every day when we go to the office is how can we make sure that we deliver the greatest potential impact to patients through this amazing technology.
There's a lot of medicine that people need around the world, and I'm very proud of what the team has accomplished, and I cannot wait forward to look, to show you what's coming next. Thank you. With this, we're going to go into Q&A. Lavina, final Q&A, and then we'll go into the tour. I'm going to get my colleagues back on stage, and all the questions should be to David. There was a bingo during the earnings call last week about how many questions for intismeran. I think he won. Lavina is going to be master of ceremony like before.
Just like the writer.
Salveen Richter, Goldman Sachs. David, for you, can you just comment on the manufacturing failure rate for RCC given the lower tumor mutational burden status, and how many neoantigens on average are being successfully encoded per patient in this trial, and whether you see any differences here for clear cell versus papillary RCC? Just a second question on cumulative DFS events and whether they are tracking faster in line or slower than what you have historically seen with KEYNOTE-564.
I will not answer the RCC manufacturing question directly, but I will point you to the pancreatic data, because I think the pancreatic data and the melanoma data create even starker bookends than the RCC. If you look at the pancreatic manufacturing success rate was actually really good. I think that we have been able to successfully manufacture around the same for RCC, so I do not think that that will be an issue. In terms of the events, I do not think we are going to comment on the events that are happening.
Stephen, anything you want to add?
No, just we have not seen any problem with the RCC manufacturing that is not bookended the way David described. As far as events are concerned, no specific guidance, although our previous public statements where we thought we would see an IA in the early part of this year, and now the end of this year, and perhaps now next year. We are still getting our forecast right on that.
Thank you so much. Ellie Merle, Barclays. Thanks so much for taking the question. Curious, David, you had some interesting comments on your confidence in the biology and INT and other tumor types beyond the ones that you are currently studying. Curious, can you give us a little bit more color on the cadence and timing of how you are thinking about potential additional trial starts? Are you waiting for data from RCC and MIBC before starting, say, further phase III trials in other tumor types? I guess, how should we think about the cadence of further study starts from here? Thank you.
Yeah, it's a great question. I joined the company six months ago, seven months ago, and I was incredibly impressed that Merck and Moderna had already created such a large body of work of phase II and phase III trials, including an investment in essentially everything you can do in lung cancer, stage I, stage II, and three, no neoadjuvant, with neoadjuvant. Then of course, the RCC, MIBC trials, and NMIBC. I think there has been a very large investment. With the melanoma data, the first thing that we said was, "Where else do we need to go next?" So stay tuned on that, because I think that there is more to come.
Alex Hammond, Wolfe Research. Thanks for the question. Another for you, David. The reasoning behind the six-month lag to clinical effect in INTerpath-001 was clear and makes sense. Can you remind us whether there was a piecewise analysis used in, that was used in the adjuvant melanoma trials, also in the phase II adjuvant RCC trial, and whether the post-six-month disease-free survival could be used as a primary endpoint in the trial? I guess if it's not baked in, is that something that you could also change?
Yeah. I actually want to comment on that. I sped kind of quickly. If you visually look at the Kaplan-Meier, whether it's the ITT or mITT, it does look like six months there's a separation, and for the first six months, there isn't. It visually looks like that. However, when you do an in-depth analysis, piecewise looking at individual time points, you actually see that the treatment effect does not start happening at month six. It actually starts happening earlier. If you look at the Kaplan-Meier curves, what you can see is that the slope of the control arm starts to pick up speed relative to the slope of the experimental arm. Actually, the hazard ratio, let's say between month three and six, is actually not one.
It's one for the first couple of months when we're waiting for the vaccine, but the treatment effect actually happens earlier than that. It's not something we've obviously talked about. You can see it just by looking at the, by inspecting the curves. In terms of, I think we have taken the insights that we have made when we designed the phase II trials, right? Because we assumed initially that the phase II melanoma data, which is the initial data, that everything will kind of look like that there will be this initial delayed separation. But I think what actually might happen, I don't know. We need to see, because I don't think the treatment effect really only starts at month six. I think it starts earlier.
To your other question, sorry, just from an FDA point of view, from an EMA, Stephen and I were talking about this. If you were developing a vaccine for infectious disease, you would only start counting your events after the vaccine had been fully administered. In cancer, it is always done with an ITT approach. That is typically the way it is, yeah.
Yeah. I think you said it well in the presentation. As we looked forward to three-year, five-year, seven-year analyses, we think what happens after that initial vaccination phase is probably better predicted by the six-month plus hazard ratio. That is where we view it. That does not mean there is not a benefit before.
Andrew Tsai, Jefferies. Also for David, please. You mentioned how one of the key pieces behind your confidence is the high-low TMB burden phase II. I am curious if you guys have done the analysis in phase III, and what did you see? Maybe a teaser on that. Did you look at ctDNA or BRAF subgroups too?
Andrew, great questions. Data to be shared. That was the first thing that we need to look at now, so no teaser yet.
Thanks. Dina here, on behalf of Mike Yee for UBS. Couple of points or questions. On the editorial and paper that you published yesterday on INT, around 18% of the patients, I guess, were screen failures because they did not have adequate or unavailable samples, and therefore could not get into the study. Maybe just how does that translate into real-world practice? I think the discussion said that there was a high bar for the samples to get into the study, so just trying to think about that 18%-20%. Another question on MIBC. I know we have talked a lot about RCC, and everyone seems to be very focused on that, but MIBC is also coming up next, in the future. Maybe just how can you frame timing for that? I think the primary completion is April 2028, so sorry, 2027.
Just thinking about, is that still remaining on track? I think when you look at that time for primary completion, it was kind of given a very long time ago before the study even finished enrollment, so any adjustments there? I think the multiple myeloma therapy looks interesting, and that it will be at ASH. Maybe just let us know what your expectations are, or what we should be seeing at the ASH presentation. Thanks. Sorry, a lot in there.
No, this is why I have a piece of paper. Do you want me because let me take a first stab at them. I think that the 17%, 17%-18% inadequate tissue reflects just a first pass. It is seen with every new modality. I remember at AZ, EGFR testing also took a while to finally get entrenched. It is also, in my mind, very similar if I think back to ipilimumab toxicity management. Initially, it was a very high bar, and now it can be handled even by community doctors. I think now that there is a need for adequate tissue, and it is not a lot of tissue, now that there is a need, there will be a will and a way to do it. We have a special dedicated team who is going to be training pathologists.
David, can I just build on that?
Yeah, of course.
Yeah, it is also worth noting in that same publication, like one out of a thousand times, we were not able to convert that tissue into product. It is a really remarkably high success rate. Probably more than it needs to be. We were conservative in what kinds of tissue, amount of tissue we would need to get going. Obviously, it is a phase III trial. You do not know until you run those experiments. We may be a little tighter on those requirements than we need to, and may be able to address some of those people for whom we would have said we did not have the appropriate amount of tissue.
The other thing is, a lot of this is probably just how it is getting processed. Right? It's not actually that the tissue wasn't biopsied. It was just people weren't aware, the pathologist or otherwise, that there was this opportunity. So, obviously people are now aware. Surgical oncologists, pathologists may change some of their behaviors as well. We hope to make it available broadly to many more people and just not have that be a permanent 18%. I think that's what's being referenced in the editorial.
I think with regard to MIBC, we're still on track for next year. No additional comments on that. I think you got that. Then myeloma, yeah, ASH, I think what I would do is look, it was a later data cut, so we're obviously going to have more patients and longer follow-up. I think the key question for us is, are we going to be active in patients who have progressed on prior T-cell engagers, including double T-cell targeted therapies? Then in an earlier line, can we generate stringent CRs? I think those are the two key questions. We're also interested in looking at safety as well, because we know that with T-cell engagers, one of the major risks is cytokine release syndrome, which is a Cmax-driven effect, especially when it's very rapid. With repeated dosing, you get tachyphylaxis.
With our platform, interestingly, you're not administering protein on day one. You're administering mRNA that has to get slowly encoded into protein over a day or two. With the slower ramp-up, the question has been, can we actually have induced tachyphylaxis during that slow protein production that you would never see when you administer high doses of protein instantly? So that's just one of the questions that we're asking.
Thanks so much. Terence Flynn, Morgan Stanley. David, I guess the first is for you. Just in the editorial last night, it mentioned, talked about one of the outstanding questions is sequencing the INT after neoadjuvant immunotherapy. Just how do you think about, based on the data you guys have now, how do you think about that, or what might we see in the future to address that question? Then, one, on the manufacturing side, you started to talk about some of the off-the-shelf approaches that you guys are taking. Essentially, if that proves to be an easier way to address a larger number of people, can you pivot and scale what you've done today here in Marlborough to use for off-the-shelf approaches? Thanks.
I will answer the first one. So right now in the U.S., about 20% of macroscopic stage III melanoma actually receives a neoadjuvant treatment. It is not a large amount, and actually, of course, stage II does not get any. It is an important question to ask, and it is something we do need to ask. Can you do it post-neoadjuvant therapy? Of course, we are studying it in the lung cancer trial, where we are enrolling patients who had neoadjuvant IO chemo and who did not have a pathologic complete response, because we obviously need tissue in order to make it. So, I think we can do it if there is tissue available, and we do need to study it to inform doctors.
Yeah. On the manufacturing side, if you think about it, because those are shared products, it is exactly the same technology as COVID-19 or flu shot, so it would be done at our facility in Norwood. Because those products are not seasonal, we can actually do them, let us say, in Q1 as an easy example, when the factory is actually going into low capacity, low demand, because we are working mostly in Q2, Q3 for the season. If you think about it, actually, all the products that are not seasonal, whether it is shared antigen for the CATs or 2808 that David just spoke about, or PA, those products can be made at the time when the factory is actually not really used.
I f you think about it, all the fixed costs, going back to the platform, all the fixed costs on facility depreciation, staff, all will be absorbed by the respiratory business. We're going to have only in term of margin for those products, much more incremental margin in term of cost of goods. That's going to be quite interesting.
Great. Thanks so much. Tyler Van Buren, TD Cowen. Just another couple for David. On INT, what do you think is the probability of success as a monotherapy, and when do you expect to have meaningful clinical proof of concept there? Is it the lung study, including stage I? Then kind of the same question in the metastatic setting. What gives you confidence in the combo beyond, of course, I guess, the DMFS data that you just highlighted?
Yeah, it's an interesting question. What gives me confidence in the monotherapy? I think if you believe the immune surveillance, which is my first slide there, you believe that the immune system can control emerging cancer clones and eliminate it, then of course, you don't need pembrolizumab or PD-1 for that to happen. It should happen spontaneously if you believe in that. So my belief is that, if we can give intismeran to generate novel T-cell clones, it should be the same thing as what normally happens during immune surveillance. So that's a scientific reason to believe. Secondly, the large treatment effect that we're seeing, and the fact that, to me, really bodes well that we can see monotherapy effect.
Now, I don't think we'll see it in the metastatic setting, monotherapy, because just I think that's where cancer vaccines in general, therapeutic cancer vaccines, have had a hard time for a variety of reasons. But I do believe it makes sense to study it, and we have two places we are studying it. One is in the stage I, phase III, which will take some time to read out. We do also have a monotherapy non-muscle invasive, part B, I think it's called, in the non-muscle invasive. So that will probably be one of the first places that we'll get data.
Your second question about what is the probability of success in the metastatic setting, so I kind of addressed that. I began my career at the NIH, and I collaborated with Steve Rosenberg on studying cancer vaccines in the metastatic setting, and really none of them have worked for the most part. There are a lot of reasons why they haven't worked, and the fact that intismeran does work in the adjuvant setting, I think opens up a lot of hypotheses that still need to be tested. I think it can work in the metastatic setting. I have an open mind, and we'll find out with the melanoma trial whether it does work. But I think we need to have an open mind. Anything?
Hi, this is Adi on for Cory from Evercore. There's discussion on neoadjuvant in that macroscopic stage III, but our KOL checks, we speak, and KOLs tell us that in the lower risk stage II, III-A melanoma, currently some patients forgo adjuvant pembro because of the risk-benefit trade-off profile. Do you expect INT primarily to convert existing pembro use to combination, or could the added efficacy bring patients currently choosing observation into the treatment?
I think, first of all, we studied it in the context of combination. If we move forward or fortunately get approval, that'll be the label. That doesn't prevent a physician from looking at it as a monotherapy, even in settings where we're not currently studying it in stage II, as you're pointing to. I will point to, the question was a bit of, do we think it's just going to be at the same time as, is always going to be in combination? Even in the phase III clinical trial, that wasn't necessarily true. Approximately 10% more participants received all nine doses of INT than completed their nine-cycle course of pembro. It's about 70% versus 80%. There already were, in our phase III trial, individual treatment decisions being made by investigators and patients to continue INT, but not do it in combination with pembro.
Small numbers, 10%, but nonetheless, it's there. The question of how people perceive that at a physician level or a patient level in the context of the stage of disease is one that will ultimately probably play out in the real world before it plays out in clinical research.
Myles Minter with William Blair. On 2808, how are you controlling for the different mRNA doses and eventual T-cell engager doses you'd expect in those patients? Does that actually change from the run-in that they had on prior BCMA and the other TCE therapy? That is the first one. The second one is now FDA has got its first mRNA flu vaccine approved now. There is a 2.5-month gap between the flu strain selection and the COVID-19 strain selection. That is a legacy thing. Any update about your efforts to try and close that gap so we can actually get a strain recommendation that is closer to the actual flu that we are trying to vaccinate against that might be an advantage to you guys? Thanks.
I will take the first one on the 2808. Like any fixed combination, you fix into your vial the ratio that you want to deliver. What has really blown my mind since I joined the company is the rapidity with which we can adjust during the clinical trial. During the clinical trial, we started with one ratio fixed in a vial, which is what you would do even if you had a protein. By the way, we saw the roughly projected fold relative changes based on the relative molarity that we included. There was almost a one-to-one. You put this much GPCR protein in, you are going to see that much protein made.
What really blew my mind when I joined the company is how fast the CMC team, when we saw that and we said, "We want to adjust it this way and a little bit more of this," and within a very short period of time, they were able to do that. That is because of what you heard, the platform effect here. We can adjust based on what we see, and in fact, we are going to adjust based on what we see.
Thank you for the question. It is an area we are spending a lot of time. Just as framing, as you would have seen in our VRBPAC presentation, as you have seen in public health, there really are two main drivers of mismatch in vaccines. About six out of 10 years, it will be an egg adaptation. Hopefully, the impact is not dramatic, but it is there and consistently there, so it is actually quite frequent. About four out of 10 years, you will see a substantial strain drift between selected strains and the actual matched strain. We are obviously every year going to deliver that better matched as cell therapy or cell-based approaches, but obviously mRNA would be the non-egg based.
As far as the mismatch years, we are going to have to work with public health on it. The challenge there is that there is a global system. That global system has worked for years. There are a lot of stakeholders in it. It is not just the FDA and CDC in this country, it is the WHO globally, and it is the other manufacturers. You can rest assured that we are working hard to change that system, but we are also pretty reasonable about our expectation for change in one year.
Over time, we do not think it is acceptable that we are picking strains three months earlier than we have to for other seasonal respiratory vaccines, because there will come a year, it says four out of 10, there will come a year here where that mismatch will have a dramatic impact on public health. We are hoping to get ahead of that, but it will be a multi-year process to change the system, I think.
Thanks. Courtney?
Courtney Breen from Bernstein. Just a couple questions. I want to push a little bit on the pathologist component as we think about INT. Can you help us understand the degree of fragmentation of where you are going to have to do the work to do the education to get these up to speed? I know obviously you have a more than 100 clinical trial sites that you have already engaged with, but these community systems are obviously much more diverse and spread out. There may be some connection points and integration points that perhaps you can tackle many simultaneously. I just want to push there on what that process looks like in terms of getting these sites up the learning curve.
The second part, just as we are all trying to predict where on earth INT is going to work beyond melanoma. One part of it, as you have well described, is identifying neoantigens that can be replicated and produced, and that the T cells can replicate them. The second part is, can the T cells go and actually have an effect on that tumor? That is the part that I think we still have question marks over. We know where checkpoint inhibitors work, that probably the T cells are able to work, but now you are pushing beyond them. What data gives you confidence that T cells might be able to work in some of these places that checkpoints are not working today? Is it just directing them after the right things, or are there other checks that we need to see to give you more confidence there?
I'll take the first part.
Yeah, go ahead.
Yeah, I'd contextualize it. You raised it. We had 100 sites in the pivotal trials, in 42 countries. We've got a lot of experience about how we get tissue out of those sites. We're not going to do it alone. We have partners, sequencing and tissue management partners that are actually actively soliciting on the orders of hundreds of thousands of samples and tissues, for things like MRD assays, ctDNA-based MRD assays for monitoring disease. We don't have to build the infrastructure that gets tissue out and into a sequencing system. We're working with those who've already established that. There's still going to be some education, for sure. As we bring a site online, we are going to send technical experts to help talk to all the people, and we're going to get better and better and better over time at doing that.
But our track record through the clinical trial programs, again, across dozens of countries, has been, to our eye, satisfactory. We think we're in a strong position. For the first time, there'll be a reason to care, which is, we hope, an approved product that adds a real benefit to patients. So, we're really excited. We do think that partnerships we have will allow us to work through that, but we're also going to recognize it as a challenge every day until we get the practice changed.
Yeah, just to add on that before I answer the other question. The phase III melanoma trial obtained tissue retrospectively. The patient had the surgeries maybe somewhere else, and then they had to be screened, and then the tissue had to be obtained. Now that you have a drug approved, you can actually be proactive, and when the patient actually goes in for surgery, they know that there's a product on the other side. Not trying to minimize the obstacles, but at least a little bit hopeful. In terms of where else, what gives me confidence that intismeran can work where checkpoints don't work? Is that the question you have? I don't know. It may not. But I think it is very intriguing and appealing for me to think that pancreatic cancer.
People say pancreatic and colorectal don't respond to checkpoints. They actually do if they're MSI-high. T cells can get into pancreatic and colorectal cancer. It's intriguing for me to think that maybe one of the reasons that T cells don't work is because maybe the priming is not effective. I don't know for a fact, but that's why I'm so excited to test it, and I think that's the next wave of tumors that we need to explore. Does pembro not work, or PD-1s not work because there's ineffective priming? I don't know, but we need to find out.
Our last question before the tour.
Nice, I get to close out both. Daina Graybosch from Leerink Partners. I want to go beyond TMB and ask if you can talk more about the nature of the neoantigens in RCC and bladder and how that compares to melanoma, maybe the distribution of different types, and what gives you confidence from your own data or others, if there's a difference in the nature, that you can be effective with those different types of neoantigens?
That is a great closeout question, because I can only speculate now. In RCC, one thing is we are also looking at insertion-deletions, which are more common in RCC than they are in others, so in other tumors. We do include indels, insertion-deletions, in our cassette where they are available. I think the concept of neoantigen quality is essentially what you are asking, and it is something that I think is a fundamentally important question. We, 10 years ago, created our algorithm based on the best science at the time, what we thought made good neoantigen quality. It turned out that was a great scientific bet because we have a hazard ratio of 0.58.
Once you now have a randomized phase III trial that is positive, now you have the ability to go back and dissect what actually is a quality neoantigen versus what is a neoantigen that does not work. You cannot do that without the efficacy. You can only guess. We have the phase III trial in hand now. We are working furiously with Merck to try to answer your question, Daina, which is the fundamental question that I think will move the field forward. I think the moat that you have heard about, that Merck and Moderna has built, is only going to increase, because once we identify algorithm number two based on what makes a neoantigen quality, we are the only ones who have the efficacy data to be able to build on that.
Then we will get more data in other tumor types that will continue to build on that. I would say this is an exciting place to be if you are interested in immunotherapy. That is why I am here.
Hello. Thank you. Okay, we are going to now start the tour portion of the day. On your ID cards that you received when you walked in, you will have a color-coded, next to your ID, your name card. If you are in the green one group, please stand up and meet your tour guide on the left of the room.
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