It's the first time there is a cancer vaccine working. The field has been doing that for 20 plus years, more than a thousand clinical trials that have all failed.
What was different this time? What is it about mRNA technology that enables the immune system to learn in a way that other approaches were unable?
We all have cancer cells all the time in our body. Our immune system is very well trained to basically notice those cancer cells very early and get rid of them. But if your cancer grows, then the question is how can you reteach the immune system? We're going to basically take a biopsy of your tumor. We're going to read all the letters of its DNA, and then we're going to do the same things with a healthy cell of your body. And we're going to literally compare letter by letter, nucleotide by nucleotide. And then we're going to use an algorithm to identify which one of those mutations are the most relevant. And so when this is injected in your body, it teaches the immune system the signature of your cancer cell that it missed.
What gets regulated here? Because every dose is different. So obviously every dose doesn't get approved.
Hi. Welcome to the a16z podcast. I'm Jorge Conde, a general partner on the a16z bio and health team. I am thrilled today to welcome back Moderna CEO Stephane Bancel. For folks that have been longtime listeners may recall, Stephane joined us on the a16z podcast back in December of 2020 when we were talking about all of the work Moderna did to bring us the mRNA COVID vaccine. And at the time, if you can go back and listen to that episode, you'll hear how quickly Moderna was able to react to the existence of the virus, to analyze it, to essentially print a vaccine that would protect people against the COVID-19 vaccine, and hence put us in a much better position with respect to the COVID pandemic. We titled that episode "The Machine That Made the Vaccine." And the reason why we're talking again today in August 2024 is because Moderna has put out news on a really big advancement on what they can do with mRNA technology when it comes to cancer. And so I want to hand it over to you, Stephane. Again, a very big welcome. Thank you for coming back. But maybe the place to start is let's lead with the news. Moderna and Merck announced earlier this month in August that you had conducted a Phase 3 clinical trial in melanoma and have gotten very encouraging results. So why don't I hand it over to you and tell us what have you announced? What have you seen in this Phase 3 trial, and then I do want to dig in into what Moderna is doing in cancer.
Wonderful. So Jorge, thank you so much for having us back. We're very happy to be with you. So indeed, last week now we shared the news with our colleagues at Merck that after working 10 years on an individualized treatment against cancer using mRNA technology, that the Phase 3 was positive. It's a first of many. It's the first time that there is an agent in melanoma that is better than KEYTRUDA alone, so it's a big deal for patients, of course, with melanoma. It's the first time there is a cancer vaccine working. The field, as you know, has been doing that for 20-plus years, I think more than a thousand clinical trials that have all failed. And if you look at the Phase 2 data, because what we announced last week is that we met the primary endpoint of the study, which was recurrence-free survival—i.e., people having the cancer back or dying—that we met.
And then to our own surprise, because this was the first interim analysis—this is not the end of a study, it's a first interim of a study—what was a surprise even to us is we met the secondary endpoint, which was distant metastasis-free survival, which of course takes more time to mature because it means that you have distant metastasis from your primary tumor. And we also met that endpoint, which was great, again unexpected from our side, but again means it is really good. We will share the data very soon at a big medical oncology conference, which is, as you know, what the field does. But just to give you a sense maybe to orient kind of directionally, we showed at ASCO, the big oncology conference in the spring of 2024 a few months ago, that our Phase 2 study, which was also randomized against KEYTRUDA alone—so the same type of study—showed that around 50% of people had recurrence-free survival versus people only getting KEYTRUDA. And this is 5 years after treatment. And as you know, in oncology, 5 years is considered by doctors like a cure. And so it's a big, big deal. And if you look at the data from overall that Phase 2, you had around 80% of people that were disease-free 5 years after their treatment and their surgery of melanoma. And so we're very excited about what it means for the field. We are working very hard already with regulators to file so that the drug can be available to patients as soon as possible, and we hope in 2027, and we're going to try to make it as fast as we can. The factory is ready in Massachusetts, where we have figured out how to make and scale a product for every human being at a time.
Well, there's so much to unpack here. This is an extraordinary advance for the treatment of, in this case, melanoma, and hopefully over time cancers more broadly. So let's unpack some of this if we could, Stephane. First, talk to us, for folks that are less familiar with cancer treatments: what is KEYTRUDA, and why is KEYTRUDA alone not sufficient? Why was Moderna or this particular mRNA cancer vaccine necessary in conjunction with KEYTRUDA?
Sure. So if you look at KEYTRUDA, which is kind of one of the leading immunotherapies that people might have heard of, it's basically, if I oversimplify for non-biologists, a molecule that basically opens the gates for letting the dogs out that are going to go and attack your cancer from your immune system, if you want. The thing about checkpoints is when they work, they're fantastic, because those people 5 years after treatment are in the cured in the sense they have no remaining disease. But only 60% of people are disease-free after 5 years, if you look at the Phase 3 published data of KEYTRUDA. So again, for those 60% of people, it's amazing. But it means that there's 40% of people where you go through the treatment, you're fighting cancer, and the treatment doesn't really work for you. And also, what is difficult is those treatments are wonderful, but they a lot of time come with very serious side effects, very different from chemotherapy or radiotherapy. The side effects of immunotherapy are mostly immune diseases.
So if you look at the label or the clinical studies, people that get checkpoints, whether it's KEYTRUDA or any other type of checkpoints from other companies, they end up having Type 1 diabetes, lupus, Crohn's disease, these types of things. Of course, it's better to have those diseases than being dead from your cancer, which is why those have become standard of care. But think about those 40% of people who don't respond to checkpoint. They get an autoimmune disease most of the time, and they don't get the benefit of the medicine. And so what we tried to do with Merck—and it's really a technology that emerged from Moderna labs back in 2015-2016 when we did a partnership with Merck as we were looking for one of the best companies in immunotherapy to partner and to have a complementary approach—the idea that we had at the time using our infectious disease learnings from our infectious disease vaccine, we learned a lot about the immune system and how mRNA interacts with the immune system. We thought we could develop a mechanism of action that was totally orthogonal, so very different from immunotherapy, because you will be able to start from a sequence of your tumor...
So that we could design a product to basically teach, if I go back to the dog analogy, to teach those dogs what to look for very specifically. And that's really the beauty about our technology. If you think about KEYTRUDA basically unleashing the dogs, but they go a bit randomly—sometimes it's your immune system—whereas Moderna's product is able at the molecular level inside your immune system to very specifically teach your T cells, "This is what you need to look for, and that thing is actually on your cancer cell," so that those T cells go and basically attack your cancer cells.
Okay. So now that that's where the personalized cancer vaccine technology will make a big impact on the treatment of melanoma. We'll come back to the personalized piece, because I think that's just fascinating not only from a technological standpoint, but just from an operational standpoint. So I do want to come back to that, but let's focus on the word "vaccine." Typically when you think of the word vaccine, it is to prevent a disease. Here in this context, these patients already have cancer. So in a sense you are preventing something. You're not preventing the cancer; what you're preventing is the return of the cancer, which is in and of itself an extraordinary thing to think about from a therapeutic intervention perspective. Number one, is that a fair characterization of how...
...characterization. And the reason the field has used the word vaccine—it was not us using it, we just followed the field, as I mentioned, there's been a thousand-plus clinical trials—is because it's about teaching your immune system. If you think about a COVID or flu shot, you teach your immune system before you get the virus infecting your body. Here, you teach your immune system not about the virus, but about basically the cancer signal that your immune system missed. Because what we know today in the field is that we all have cancer cells all the time in our body,
whether it's outside factors or just as you have cell replication and you have mistakes that happen that create mutations of DNA that are cancer cells. Our immune system is very well trained to basically notice those cancer cells very early and get rid of them. But if your cancer grows, then the question is: how can you retune the system? So I think that's why the field used the word vaccine for that approach as well. Even, as you said, it's a therapeutic treatment approach post-cancer, it's about the teaching of the immune system.
Okay. And so as you point out, the field has tried this many times before. On the order of a thousand clinical trials have tested this theory. They've all failed. You and Moderna and Merck have succeeded here. What was different this time? What is it about mRNA technology that enables the immune system to learn in a way that other approaches were unable to be successful?
Yeah, I think there are two components. One is the mRNA technology, and I think the other one is the individualization by designing a product for one human at a time. So let me go through those two. On the technology of mRNA side, what we have known and published actually with Karolinska—as you know, the institute in Sweden that gives the Nobel Prize in Medicine back in 2015—is that with our technology (I cannot speak about other mRNA companies that have different mRNAs, different lipids, and so on), but with our technology, when we inject our mRNA in a muscle, whether it's a COVID shot or flu shot or this cancer treatment, basically the mRNA goes down to your lymph node and enters the APCs, the antigen-presenting cells, which as you know are key components of your immune cells. And the mRNA gets inside the APCs. This we've demonstrated and proven at the time with Karolinska. And then it basically translates the message contained in the mRNA inside the APCs, inside your immune cells, and presents it from within. So we think it's a very important differentiation from most of the previous vaccines in cancer in the field that were made by protein or peptides that basically are made in reactors, are injected in the patient, but are basically turned into the blood. Because as you know, recombinant or protein, when you inject them, they just go into your blood and they turn around. So your immune system sees them, but not in the same manner from within as is done with the mRNA. So we think that's one very important component of immune presentation, if that makes sense. The other component is really individualization. In the past, a lot of time people have tried with non-mRNA—i.e., protein technology or peptide—but also we tried a shared antigen. Whereas here, what we said is because cancer is a disease of DNA...
What we're going to do here, because the cost of sequencing has dropped so much in the last 20 years, is we're going to basically take a biopsy of your tumor. We're going to read all the letters of its DNA, the 3 gigabytes of its genes. And then we're going to do the same thing with a healthy cell of your body. And we're going to literally compare letter by letter, nucleotide by nucleotide. And then we're going to use an algorithm to identify over your hundreds or thousands of mutations which one, based on the current knowledge of the field of immunology and cancer, which one of those mutations are the most relevant. We select the 34 that we believe are the most relevant, and we stitch them together into one big mRNA molecule, which we make in 30-ish days for you, that is injected then in a hospital intramuscularly. And so when this is injected in your body, basically it teaches the immune system the signature of your cancer cell that it missed—not the signature of every other patient with a shared antigen, but the very specific signature of your cancer cell. And what we showed at ASCO and we published from our Phase 2 study—but we believe it's the same thing in the Phase 3 because it's mechanistic—is that around 90% of the antigens are different patient to patient. Because when we started, we had no idea, because again the field came from shared antigen. So when we started, we had no idea: are we going to get 2%, 5%, 90% of same antigens across all the patients? Actually, 90% of antigens are different from a human to another one.
Wow. So the only way this can work is through personalization, individualization.
Assuming that that carries over. And so in that regard, if you're doing, let's say, this normal-to-tumor comparison of the genome, you find the differences. I'm curious how you arrive at 34 as the right number. I'm sure there's a very good reason for that. But what is the algorithm that enables you to do that? Is this something that's proprietary to Moderna? Is this something that is known within the field? Help us look into that black box.
Sure. So I want to share a little bit about the black box—not too much, because there's a lot of know-how and things that are very confidential to us—but basically we started with, of course, what is known in the field. And so we basically used a lot of databases and publications and a lot of scientists and doctors kind of best-in-class in immunology and in oncology. And then from that starting point, we used a lot of internal data that we generated over time. We also partnered with some companies that, because they are in the diagnostics space or cell therapy and other spaces in oncology, had access to a lot of data, a lot of T-cell mapping and so on, that were very useful for the learning. The thing that is interesting about the data we showed last week is this is what I consider mRNA-4157 version 1.0, because the algorithm from the Phase 3 was the same from the Phase 2, was the same from Phase 1. But because we've been doing this for 10 years, it's a 10-year-old algorithm. So as you look at the data, it works pretty well, right? As we said about the Phase 2 data, 80% of people are disease-free after 5 years. It's amazing for those patients, but there's still 20% of patients that don't respond. And so one of the things we're going to be doing now that we have access to Phase 3 patient data and samples is to go back and mine that data to figure out why some patients responded and why some other patients did not respond, because we have access to all their blood samples, the sequence, everything. And we're going to try to see: can we improve the algorithm? And we will go to the FDA if we find scientific reasons why we should change the algorithm to go from, let's say, 1.0 to a 2.0 algorithm, and then change it. Of course, we have to do that in a very controlled way to ensure we don't lose efficacy, very obviously.
But the way I think about it is like when we talk about AI, we always joke that the current version of AI is the worst we're going to see in our lifetime. Well, it's exactly the same for mRNA-4157, which is the current version of mRNA-4157 at Moderna is the worst version you're going to see for the rest of medical history. And so that gives me a lot of hope not only in melanoma for those 20% of patients that don't respond, but also for potentially other tumors that have been really hard in the field, like pancreas cancer and others where immunotherapy doesn't work. We want to be able to learn a lot about the technology using also what the field has learned in the last 10 years, because the field has learned a lot, as you know. This is not even in mRNA-4157 1.0, so that's why I'm so excited about what's coming next.
That's fantastic. So looking back, you and I have known each other for a very long time. I won't depress you or me by saying how long,
You were very young. You were in kindergarten.
So I've had the benefit of seeing Moderna from the earliest days.
And one thing that was true then is true today: you are, first of all, an engineer at heart, and you have from the very beginning been obsessed with process, with operations, with being efficient. And those things need to be absolutely true if you're going to attempt to do what you're trying to do here with personalized cancer vaccines and make a medicine for each individual patient precisely because in 90% of the cases there's no overlap in terms of the antigens. Can you walk us through a bit the operational lift that is required here that you've already had to do to even run the trial, but that you would have to do if you eventually commercialize this product?
