Welcome back, everyone, to our slightly delayed next session of the 2024 Global Biopharma Conference. I'm Monte forrest , Senior Analyst, Genetic Medicine . I'm very fortunate to be hosting John Leonard, CEO of Intellia Therapeutics. John, how are you doing?
I'm doing well. How are you doing? You just monitored the big show, right?
With Dave Risinger. I co-cover with Dave.
Very good.
You'll forgive my breathlessness from running down the hall. But apropos of breathlessness, let's talk about how perspectives have evolved on gene editing. We are less than a year from—well, can any of these companies actually dose patients in the U.S. to where we are now, where.
Phase III.
Phase III, multiple pivotal studies, not just the one phase III. Let's talk a little bit about how regulatory conversations have evolved and to what extent that changes how we should think about the speed-to-pivotal studies for you guys and potentially other in vivo gene editing, base editing, etc., technologies.
Well, in our case, I can't say the regulatory world has evolved that much. I mean, it's. I think there was a sort of false narrative that things couldn't happen in the United States, largely as a result of the path that we chose to follow because we thought it would be fastest to get to the answers that we were looking for. I mean, we've cleared five INDs, if you include, you know, the partners that we've been working with, Regeneron and Novartis, all in the 30-day window, whether ex vivo or in vivo. And so from our standpoint, it's really a matter of understanding what the FDA is looking for, having a really good notion of that, taking, you know, very, very provocative tests, etc., and following through on that.
You know, our interaction with the FDA, as has been the case with essentially all the regulators that we dealt with, has been actually pretty positive. So, I think some of the stuff about, you know, doing work in the United States, being harder, etc., is a false impression that people have had. We're here. We're doing, you know, our, as you pointed out, our phase III trial. We'll have a second phase III program this year with HAE. So, things are going very, very well.
Let's talk about HAE first. Obviously, it's—you know, it's a market with a couple of a few different approved products, a number of agents in development, including an antisense oligonucleotide, which takes a sort of a cousin of your approach in terms of target. But obviously, one-time therapy versus chronic, very different economics. Let's talk a little bit about how you interpret that data and what it means for your commercial strategy. Whether or not we should think of gene editing for HAE as predominantly something for new patients, for the most severe, for the least severe, the youngest patients, where you can gain the most financial benefit. How—where do—what is a commercial strategy by niche, and what's the lowest hanging fruit?
There's about five questions in there, Monte, but I'll do my best.
I counted at least seven, but okay.
Look, you know, we're trying to have a very broad-based approach where we think the therapy is going to be relevant to all of those patients, at least eventually, in terms of who's going to be the earliest adopter. I think most of the time, you know, physicians look at it a certain way as to patients, typically with the most severe, patients moving on to new therapies. The space has a lot of propensity to switch. I mean, we know that patients are constantly trying different things, so we think that that's, you know, an advantage for us. But ultimately, the proposition that we're offering is we think in many patients, something approximating a cure. I mean, that's what we've seen so far with, granted, unlimited data, separate from phase I. Patients are looking to get rid of the burden of whatever their care is.
Your point being, you know, that many of these patients are diagnosed during adolescence, which means a lifetime of whatever it is that they're taking. What comes with that oftentimes is adjusting your life to avoid stressors, etc. T hen there's the financial piece that comes with it, which can be very, very extensive. We think if you go down that list, you know, from an efficacy point of view, we will raise the bar. But, you know, from a burden perspective, we think that many of these patients are going to be able to dispense completely with prophylaxis and on-demand therapy. Normality will be determined by people not having to think about the disease anymore, and we'll be looking for that in our phase III work.
T hen from an economic point of view, this is an incredibly expensive set of therapies that we're quite confident we'll be able to offer some really significant resource-sparing to the payers. So, you know, from our perspective, it lines up really well there, where we think we're advantaged pretty much across the board.
L et's talk about exactly the dynamic, the normality, and of taking patients out of functionally being professional patients and building their life around the disease instead of the other way around. How long does a patient need to go without a rescue or on-demand therapy for you/the company/us as a society to be comfortable with them not carrying a rescue therapy in their pocket or in their bag?
Yeah. I don't know yet exactly what that answer is going to be. Obviously, the longer, the better. You know, for people who have had many, many, attacks going to something that is, you know, very infrequent, less than once a year, I think many of those patients will feel liberated. A big part of that will be if there's an attack, what's the severity of the attack.
You know, what we've seen so far with what we report out in the data, in our phase I program is that a patient who had, you know, real problems with this disease, you know, had the lowest degree of editing, had a single attack as a result of a sports injury, where, in fact, a physician had difficulty discerning whether it was truly the disease or a result of getting, you know, kicked in the hand with a soccer ball, didn't need therapy. So, you know, I think each doctor and, you know, the patients will probably decide for themselves, but that will come with time, obviously.
Let's talk a little bit about clinical trial execution. The concept of sort of rescue therapy, bar for rescue, it's one that in one of these earlier sessions we were talking about in a totally different indication, wet AMD. Obviously, very different. But in this case, you do have sort of a rescue therapy on-demand dynamic. To what extent is the use of a rescue or on-demand agent specified and structured in this study, and to what extent is it entirely in the hands of physician and patient, a physician and patient discretion?
For the phase III of the study?
For the phase III. That we expect.
Well, we haven't finalized the protocol. What we're going to try to do is not, you know, impose too many constraints on patients. I t'd be my expectation that a lot of it will be determined by the patient and his or her physician. But obviously, rescue therapy will be made readily available for these patients if they think they need it.
Is the choice of rescue therapy totally defined in the design, or can it be any FDA-approved product?
Well, again, from a phase III program, we're working on laying that out. We hope to be starting phase III in the second half of this year. My guess, based on where we are right now, is that it's not going to be pre-specified. It'll be whatever the patient's been using previously.
Great. I'm going to pivot elsewhere in the strategy. One of the things that we've talked about in a couple of different sessions, you've talked about earnings calls, etc., is your strategy around what indications belong in your hands and are in your wheelhouse, and what really should be outside of the four corporate walls of the operations of Intellia. We talk about cell therapy, for example, as one example. You've had, we'll say, some success for JV. How large a part of the story going forward is that? Should we think of that as, and how do you think of that as a place to utilize management, time, expertise, resources, etc.? Like, where does that fit into the story now that you're accompanied with multiple, fairly sizable and complex phase III studies to run?
Yeah. I mean, it's what you're raising is the manifold uses of, of genome editing. I mean, we've—what we tried to put in place is a toolbox that enables all of the different relevant types of, of genome editing that we think are applicable broadly for what we're interested in and what we imagine many other people might be interested in. We focused very much on the in vivo space, where we've made a lot of headway, starting the liver, knocking out gene, building genes back up now with the insertion programs, and then put in place a lot of work to move outside the liver. We now have five different modalities to do that. So in vivo, certainly, occupies a lot of our time, and we're really excited about, you know, what's there to be had.
O n the ex vivo side of the house, we do have some significant advances as well. We think we've cracked the code with respect to allo, that will be shown with clinical data. T hen it becomes this very, you know, large, you know, room that you walk into in terms of the potential uses. I think, you know, the way we think about that space is if you can get to some very fundamental insights, say allo, that then opens up any number of different potential collaborations, depending on the biology that another person or company might bring. So I would look to BD there. I would look to collaborations, etc. We've done, as you pointed out, a couple already. Kyverna was one, that, you know, we're quite excited about in the autoimmune space. AvenCell was a spin-out, you know, universal CAR-T approach.
I think, you know, to the extent that we see, biology that can benefit from what we do, we would look for collaborations there, in many cases, letting the other partner do a lot of the work.
P ivoting from BD back to the pipeline, let's talk a little bit about strategy and alpha-1 antitrypsin. Obviously, a space where there's been a lot of discussion, different approaches. There's other editing approaches in development, small molecule, oligo, etc., not surprisingly, even the size of the population it might need. Let's talk about how you see a world where there could be both one-time therapies and oligo chronic therapies, and where those fit and what patients should get what.
Well, yeah, it's going to start with the outcomes, you know, and it really, I think, you know, the primary source of the pathology is lung-based, right? And so what we believe physicians will look for based on our interactions with them and talking to patient groups as well is something that, as much as possible, normalizes the production of wild-type protein. I f it turns out that everybody can do that, then we'll see how that all sorts out. It just, you know, that hasn't happened yet, right? What we've shown is that in the preclinical setting and non-human primates, we are, in fact, able to produce levels in those animals that are human equivalents, you know, normal human circulating levels of protein that's wild-type. And, you know, to date, I haven't seen anything that tops that from a genome editing point of view.
W e think that that's a winning strategy, which we will prosecute to the bitter end, you know, as we sort that stuff out. We'll see what others come up with. But you know, when I think about, like, oligos and siRNA, that's primarily for a subset of patients with, you know, the disease, primarily those patients that suffer from hepatic difficulties, which is a really, like, 10% or so of the population. That's something that we're not addressing directly with the insertion approach that we're taking.
I think one of the debates around this market, around this indication, broadly speaking, is that it's, it's a little different than TTR. We have a lot where you have some behavioral modifications you can make, especially in lung disease, specifically not smoking, for example.
Right.
That could potentially extend the time horizon to a clinical phenotype. So you have many patients who are not symptomatic, could become symptomatic with an infection, etc. So when you think about enrolling a clinical trial, do you want to enrich for patients who have shown an evidence of symptomatology, i.e., the most severe patients? Or do you want to enroll patients who reflect the majority, who tend to be asymptomatic for most of their life outside of timelines of acute stress? Like, what population set should you gather data from in a hypothetical pivotal?
Well, we're in phase I , hoping to dose a patient, begin dosing this year, and we expect to do that. We're certainly guided to that. You know, the way we try to do all of our work is to get to the broadest label possible. And, you know, the regulatory logic that we're applying in the case of Alpha-1 is, you know, you make the FDA's job a lot easier if you have normal levels of protein. T hen once you have that, you can start thinking about the broadest-based population, those who are severe in their disease and those who are in the earlier stages but have the most to lose. And so, you know, as we get further down the road here, I'm sure we'll have those debates.
I would certainly encourage my team, as we've tried to do with HAE and TTR, etc., to have the broadest set of patients possible.
I'll take this opportunity to congratulate both of us for getting halfway through without talking about TTR. But unfortunately, we've arrived here, or perhaps fortunately. Let's talk a little bit about pivotal strategy and how it's informed by data sets, because we've learned more and more about how this disease has evolved in standard of care. And there's a lot of debate around the benefit on top of, in addition to, in a tafamidis world, we'll say. When you think about a one-time approach, to what extent does it matter, quote-unquote, the prevalence and availability of tafamidis generic or otherwise? And do you think that's the population you need to stratify for in your data sets?
Well, we're clearly going to stratify it for it. I mean, you have to do that. I mean, the study that's underway now, called MAGNITUDE, looks at standard of care plus or minus drug, right? And, you know, we've said elsewhere that we expect about half the patients or so to be coming in on tafamidis, which we think is entirely appropriate. You know, tafamidis is a drug that clearly has a clinical benefit. You know, most patients progress on that drug, so it's clearly not solving the problem. It's helpful, but it's not definitive. So what we aim to show in our phase III trial is that, irrespective of your taking that drug, is there a benefit? Now, we expect to see a lot of benefit in patients not taking tafamidis, but we expect to see incremental benefit on top of that.
The study's designed in a way that we should see that. You know, down the road, you're talking about generic tafamidis. There will be a time. It's not exactly clear to me when that's going to happen, but, you know, I guarantee you Pfizer will do everything they can to forestall that, which makes perfect sense. But, you know, our expectation is that when we get to the market, that's going to be less and less of a consideration. I f it turns out that combining the agents is advantageous, we'll have data to support that, and we would encourage, you know, the use. If it is generic, it's clearly easier to do that, and it puts payers in a better position. But that would clearly benefit patients.
Let's talk a little bit about, you know, a obviously closely followed study, HELIOS-B, in the space. Maybe you've heard of it. Obviously, there's been debate around, you know, statistics, trial design, etc. And that's not the first study in this indication where we've seen pivoting. Obviously, AstraZeneca took a different approach, maximizing study power and scale. Some of that is a function of their existing infrastructure, I would presume. To what extent has Intellia preserved flexibility to potentially adjust statistical treatment? And to what extent do you think that is the right, that is, that would be the right thing to do for your therapy down the road, should you see unexpected results from competitor data?
Well, I think we're advantaged by where we are. You know, one of the things that's been lacking in the space is, you know, a good phase II program that measures the relationship between knockdown and clinical benefit. We had sort of a peak of that with Onpattro, with the study that they did. But we try to learn from all of these studies and have taken a, I think, pretty conservative view of what we think the event rate is from all of the different, you know, data sets that are available. We've, you know, added to that by interviewing physicians who are in the front line of caring for these patients who have their own databases, etc. W e think, you know, we have a pretty good notion of the rate at which things should happen.
Unlike some of the other studies that have been done, which were time-based, you know, you choose in advance a time where you're going to look to see how the two groups are separating, if they're separating. To me, that's been a high-risk approach based on not a great fund of knowledge in terms of knowing precisely when to look. I f anything, we've learned that it takes a while for curves to separate. So the approach we've taken is an event-driven study where, you know, it's the pretty traditional approach for lots of cardiovascular outcome studies where you, you know, anticipate certain effect that you're going to look for in a database. And then when you get enough of those events, break the line, so that's how it's set up.
We're not going to be in a position where Alnylam found itself where, because they had predetermined a point in time where they were going to look that they, for whatever reason, I don't know all the details, chose to extend that almost certainly to, you know, collect some additional events. We know what we're looking for from a total number of events. Now, we will have the data coming out from these other studies, which gives us plenty of time, given where we are in the enrollment. If there's something that deviates substantially from what we've already seen or surmised, we can certainly adjust. We'll have an interim analysis if appropriate. We'll be able to adjust at that point.
I think the basic approach that we've taken is going to obviate the need for anything other than a, you know, a really surprising outcome from, you know, one of these other studies.
You touched on, sort of, enrollment, proportion of patients on tafamidis, etc. One conversation that's existed in this space is, well, your tafamidis exposure and your patient population will vary by geography. The idea that, you know, you could potentially get a large pool of non-tafamidis patients who are tafamidis ineligible for economic reimbursement reasons by skewing your enrollment geographically. To what extent is that still true? And to what extent is that a little bit of like a 2021, 2020 narrative that, you know, that's a little long in the tooth?
Well, it is true that, you know, tafamidis is not reimbursed or available in certain countries. And so you can, you know, assure yourself of having some, you know, non-tafamidis using patient population in your study. You know, we expect to have lots of patients in the United States. We have many, many, you know, have and will have additional sites in the United States. So that will, you know, be reflected in that patient population that comes in. But in aggregate, as we look across the many countries where we will be, we think we're going to wind up with about 50% or so patients taking tafamidis and, you know, the other half not. If it's a little different from that one way or the other, it's not really going to matter from the results of the study.
I think one of the debates, certainly among the more sort of skeptical investors, is around the uncertainty around event rate, which has played out around debates around the stocks of other competitors of yours. But in the case of Intellia, it becomes more a question of duration of the study and what that means for implied operating expenses across the course of the study. Let's talk a little bit about what the cash burden to run this study is, and how we should think about it either all in, annualized, and just how people should model it in a fairly in as much nuance as you can give us, recognizing that, you know, this is like a, is four years out from now, potentially, in some cases.
Right. I mean, what we've said and, it's, you know, exactly how we look at the world here. You know, we started the year with about a billion dollars. We've prioritized programs internally. We took some other actions, etc. You know, people mistakenly believe that there's a lot of new expenses coming as a result of the study. In fact, much of this has been done in the preceding year or so where we manufactured a lot of the material that was going to be necessary for a study. Granted, you know, it's clinical expenses. But with that billion dollars, we're very comfortable that we get to the middle of 2026, which, aside from expecting that this study will be fully enrolled in that timeframe, we should have had the HAE program in its entirety play out.
We would expect to be assembling or submitting a BLA, which we've been talking about. We think we're going to have a read on the insertion work for Alpha-1, which I think is going to speak broadly to not only that program, but a whole category of things that might follow. And, you know, when we think about things yet to come, we've got five programs now to get outside delivered. We, you know, I would expect, in that timeframe that we will have a development candidate or two to go beyond that. T hat set of activity, including, you know, a program on the ex vivo side, which is this allo approach that we're quite excited to approach about, should start yielding some clinical results. All of that is in that billion dollars.
You know, yeah, it's not the last, we haven't raised the last dollar that we're going to need to raise, obviously. But we've planned very, very carefully for getting to a point where, you know, we can start thinking about being a commercial company with inflows of dollars from completed programs and where we go from there.
When you think about assets on the balance sheet, you're talking about cash. But obviously, you guys, thanks to the JV, the JV structure, you do have other assets that are available to you financially and otherwise. Rather than talking specifically about any individual holding, how do you, where do you fall philosophically on retaining an ownership stake in a JV after it goes public?
You know, we look at each of them individually. It's the difference between what monetizing that asset might bring to us in terms of our own pipeline or what we see the utility of the product might be. You know, a case in point would be—you didn't reference specifically—but, for example, we have a relationship with Kyverna. Recently, very successful IPO, a lot of interest with CD19 and, you know, the autoimmune space. We have an option to participate in an allo form of that. We are significant shareholders in the company, which we're very excited about their success. We could go either way. You know, we can take the money and apply to our own pipeline, or we could opt in and go and work in the autoimmune space. And we'll take those decisions as—as appropriate. You know, we can do that with what we're doing with SparingVision.
You know, we have a relationship with AvenCell, which is essentially a spin-out of the company where, you know, they're in the clinic with the new allo approach as well. So we'll see what the data are, and we'll make decisions as the information becomes available.
Great. And with that, we're actually over time. Obviously, an exciting year ahead, and looking forward to seeing more data throughout the year.
I'll be happy to share it with you when we have it.
Pleasure is always, John.
Thank you.