Regeneron Pharmaceuticals, Inc. (REGN) Earnings Call Transcript & Summary

Welcome back, everybody. We're here with our pièce de résistance, our grand finale, if you will, of the H.C. Wainwright virtual event unlocking the full potential of RNAi with world-class novel target identification, looking at Regeneron Genetic Center and Alnylam’s RNAi Platform Collaboration update. We're extremely excited about our 2 guests that we have joining us here today. from Alnylam, Chief Scientific Officer, Kevin Fitzgerald; and the Head of the Regeneron Genetic Center, Aris Baras. And we hope that you enjoy this as much as we will. We worked very hard in getting these 2 companies together. It's not often that 2 great companies in the biopharmaceutical space like Alnylam and Regeneron come together and collaborate to form what hopefully will be a breakthrough and transformational drug. So I think we should jump right into it and kick things off. What we'd like to do is start out with a little bit of history of Regeneron Genetic Center, and then we're going to try to move this as rapidly as possible to talk about the intersection of the target discovery and drug discovery and development. And please, if anybody has got questions for our guests, don't be shy, please e-mail us at [email protected] or to Patrick's e-mail, and we'll try to get you on the calendar of questions.

So let me kick it off with Aris. Aris, I was reviewing a lot of the RGC press releases over time. And it's interesting that we're coming up very soon on the -- I guess, it will be the eighth year anniversary of RGC?

That's correct. Yes.

So maybe talk a little bit about how it was conceived. Who came up with the idea? How did you kind of synthesized what components were going to be necessary? What kind of inputs did you need? And maybe if you can give us a little bit of color on the formation of RGC. I think it will be instructive for us as listeners to understand how the process happens.

Sure. Absolutely. So as with many good stories, there's hopefully a lot of good thinking and rationale and planning, but there's also just quite a bit of luck and just some really good stories involved. So you do have to go back about 10 years when we started this whole effort. And back then, we affectionately referred to it as the human genetics initiative, so HGI at Regeneron. It was a very small number of us who all realized, of course, that human genetics was really important to modern-day drug discovery and development. And if you look at the history. I'm, I guess, a bit of a historian of biotech. If you go back to how we started doing drug development. We're talking about screening natural products, crossing our fingers, blinking and hoping that you'd be having anticancer or autoimmune effects. And then that went to, of course, rational drug design, medicinal chemistry, biotech revolution, what Kevin and our partners did to kind of set the path forward for genetics medicines, amazing innovations in the tool chest that we have, right? But if you contrast that with what targets to go after, that was really a challenge for us, or as we call it a bottleneck. We realized that if you look at all the approved medicines and those that were investigational or experimental, it was really only about 5%, max 10% of the genes in the genome. And so that was really unacceptable. How can we really move forward knowing what's so few of the genes and what targets could be for really important diseases. Of course, we've seen that in our hands at Regeneron that if you follow the few human genetics examples back then, you really could have a quicker path and more successful path to drug development. So that was the idea. The initial effort or attempt at Regeneron was actually to do a very large scale partnership with deCODE Genetics. So we had talked about something really large and sweeping. And I mentioned 10 years ago, that plane crashed and burned in 2012 when, of course, they were acquired by Amgen. So we were back to the drawing board. We had some other ideas. But luckily, we just said, look, let's just build this thing ourselves. We'll build it for purpose. Hopefully, we'll do a pretty decent job. So if you get 8 years later now, we've sequenced a couple of million individuals and there's no stopping. We're on the path to 5 million, 10 million, if we can, or more and really have hit a nice stride in terms of being able to unturn and uncover human genetics discoveries that have led to rapid paths to new therapeutics.

Well, yes it's a fabulous background, but maybe devil's advocate a little bit. I mean there had been a human genome project, human genome sciences, millennium insight, all these guys that were developing drugs that were supposedly driven by the understanding of the genome. What did you guys think that you would do differently, better, faster or some other competitive advantage that would allow you guys to succeed where others may not have realized the full potential of the genome?

Sure. It's differently, right, all the things you mentioned, and it's the focus on a specific area of genetics. Genetics is so big now, right? It's unfair to say it's 1 field. And so what we were really focused on is sequencing, understanding very large effect genetic mutations and those that gave you a very clear therapeutic hypothesis, that's simple. So let's talk about some examples. Our friends at Alnylam, for example, and we as well have had examples where if you find a mutation that causes disease, oftentimes, it's in a rare condition. But if you know exactly what's causing disease, you can formulate a therapeutic hypothesis about how to replace, restore, correct and hopefully have a great therapeutic benefit. And so that path has been followed. But for the most part, you're talking about small rare diseases. There are some -- we heard our speaker talk before about PNPLA3. There are examples like APOE4. There's a few of these causative mutations that have a huge effect that are very common. So the thing that was different though was not those, but we really were focusing on trying to find protective genetics. And I heard you guys allude that came in and out of following the great speakers today in your sessions. And there was a lot of questions about this. And so we really wanted to find -- we had experience with PCSK9, for example, right? This was before we had embarked on our genetics discovery efforts. When you have examples like that, people out there, hundreds or thousands of them, if you can find needles in a haystack, and they have gene variants that are safe and that they give you a clear idea of how to mimic that genetic effect and have a very beneficial effect on a certain condition, that's what we were looking for. The key is you have to sequence hundreds of thousands, millions of people to find them. These things are in 1 in 1,000. So you really...

So it's sort of -- it's rare, it's upside down, where you could do small populations with rare diseases, you need huge. So that explains the numbers. It's just not a numbers game. It's...

Exactly right. It's upside down. This is really important. You have to find the 1 in 1,000, the 1 in a million to have these genetic superpowers, but when you find them, that finding is generalizable to the masses, right, not to the rare disease population.

Right. And why only exomes, how come we're not doing whole genome sequencing?

We are. We are doing whole genomes in non-European and diverse populations, so we can better get a reference genome there. We're getting into the details, but we genotype everyone, so we get an imputed genome. We actually know about variants all across the genome, but then we really go to town and we sequence in great depth the exome. So we get all variants we can find in the genes themselves. That's where most of the bang for the buck is.

Okay. I have some other geeky questions, but let me table them for now because I want to, again, try to drive this into how you guys intersect and really understand what drugs you're going to develop together in. So I guess the question becomes how do you do what you do? Do you go in with a hypothesis, hey, we're going to look for protective genes in these large conditions, diabetes or vis-a-vis high cholesterol, et cetera? Or do you just keep sequencing until you feel like you've got a signal. So how does the prioritization and how does the sort of disease selection come about?

Yes. So we do it both ways. We go in with hypotheses when we've got burning questions that are so important to our development programs in our company, take ANGPTL3, for example, right, evinacumab; or if you look at IL-33, we have an antibody against that. We had really burning questions about what indications could these therapeutics be beneficial in. We were able to find humans loss of function mutations that are a great surrogate for those drugs, and we were able to do really informative studies to say, hey, you knock out ANGPTL3, it's really beneficial for heart disease and some other things as well. For IL-33. It's really beneficial for asthma, but hey, also COPD and a few other things. And we now, after that, have proof-of-concept studies moving into registrational studies. On the flip side, we don't go in with hypothesis. We say there's a whole slew of, you can imagine hundreds, at least dozens, of diseases of great unmet need, where if you could find that protective genetic story and then create a therapeutic mimic and get that thing to approval, you would have done a fantastic thing. So we have teed up a lot of those. NASH, for example, we've talked about, lots of cardiometabolic disorders, lots of autoimmune disorders. Maybe the cherry on top or icing on the cake, we've even found these in cancer.

I was going to ask that. I mean, not everybody who smokes gets lung cancer, got to be a protective allele or 1 or more in lung cancer.

Yes, we are looking for that. It's a numbers game. So the first example we found in cancer is related to skin cancer, where, guess what, we happen to have in our databases, that's the largest data set in cancer, right? We don't have as much in the other cancers yet. So I am very hopeful, if not confident, that the example you provide, we'll be able to hopefully find some examples of that in the near future.

Okay. Well, maybe we could start to move towards getting the 2 companies to talk their collaboration together. And I'm just curious, you have a combination of -- you got NASH on the 1 side of things. You've got a potentially large population of PNPLA3 too as well. And then you've got rare disorder relatively well, I guess the neurogen aren't so rare, but they're a tougher nut to crack, let's say. So maybe you could talk about how you guys got to some kind of an agreement. All right. We're going to choose these 3 and then move from there.

Yes, well, look -- go ahead, Kevin.

Yes, I can jump in a little bit, just to say, first of all, why Regeneron for us, right? And my background is in more human genetics than anything else, right? And I spent a lot of time in personal medicine. We're very like-minded in terms of -- if you look at the Alnylam pipeline, it's been driven by human genetics, right; the target selection, the ability to knock things down. And so that's really, I think, increased our likelihood of success. So for us, both from a scientific perspective as well as an interest in the belief in human genetics is sort of a natural match. And then where we overlay that is, the tissues today where we've got the ability to go in and silence any genes, right. And so that's the liver that's with Regeneron, the CNS, and the ocular space. So you sort of overlay the genetics around the diseases of those as well. And it turns out that when you find a genetic marker of disease, sometimes one therapeutic modality works and another doesn't, right? And so there are cases where something may be intrinsic to a cell and not secreted or not cell surface. So maybe an antibody isn't the right approach, but an RNAi is. I think those are also the intersection of where we choose things.

Right. Kevin, I'm curious, and I know this is something Patrick wants to explore as well. Did you guys have to get to a point where you were comfortable enough with the chemistry, both from a safety standpoint as well as a deliverability standpoint before you felt like you could really sort of maximize the value of the relationship?

Well, I don't know about maximizing the value. I think there's value across the board in both orphan as well as the larger disease indications. Certainly, we've built now a very large human safety database around sRNAs, the chemistries that we're using to give us confidence that we can go for rare orphan into the broader populations. And we've shown that with inclisiran as well as some of the others as growing databases, right? So I think that gives us confidence where we're going to start our journey shortly here in the CNS to do the same thing.

Right. Okay. Go ahead, Patrick.

Yes. Maybe I'd just ask 1 follow-up on that. So moving into extrahepatic tissue is one aspect of advancing the platform. I am also though curious just in terms of, for the liver-directed platform, if you can kind of talk about what advances can we expect going forward? Is it mainly a dosing interval? So biannual or annual dosing? And is that kind of the main advance we should expect going forward?

I mean, the IKARIA Platform, as we call it now, and Icaria, obviously, is a Greek island where people live for a very, very long time, being the Greek connection between the 2 companies.

I was just going to say. You're maximizing that...

So at end of the day, the platform is safe and the ability to flex the dosing, right? So actually not every target that you want to go after will be one that you want to necessarily silence with annual dosing. So it's the tunability of the platform to do what you need for target and the safety profile of the target. Early on, we had a couple of targets that had a little bit of liver enzyme elevation. We've been able to quickly research what that was, figure it out and design it out, because you don't want that as part of the profile. So overall, it's the ability now to design what you want in the liver and to silence the genes maximally or submaximally depending on what you require for the target. And then if you want biannual or annual dosing, the ability to get there safely. So I think it's really those key aspects.

Yes. I mean it's an interesting kind of jump off point to introduce some of the dialogue that we had with the KOLs. I know you guys were maybe not listening fully, but there were some -- so we had complement, we had Alzheimer's, and then we had NASH. And it seemed like a recurring theme was that, as opposed to sort of what I'd call the traditional Alnylam target set of putative target gene, that if you ablate it, curious to phenotype, here we're talking much more subtle effects. Do you really want to inhibit C5 permanently or even semi permanently. Or do you want something that's rapidly reversible? In the Alzheimer's area, we don't know whether walloping APP right away, or do we have to titrate up, or where in that inhibition process do we need to be. With the PNPLA3 variant, we have to be very careful about where we go. So maybe you guys could talk about the different challenges of both the target as well as drugging the target in those instances.

Do you want to start, Aris, and I'll jump in.

Sure. Yes. I mean it was really good to hear the perspectives from hematologists. I think it was -- remind me, again, his last name, I think it was Aston or something like that.

[ Atrin or Entrin. ]

Yes. And so you do hear concerns like that, questions like that. I'm not sure I fully agree, though, with the assessment in that, when you look at these different approaches, you all were talking this morning about eculizumab, and then the longer version, I mean, going from, I think you said 2 weeks to 8 weeks. I mean, that's a long time, that's not reversible, right? Those antibodies can't just be -- they're there, they're in the system there. They have their PK, right? So the combination of an siRNA and an antibody is looking to kind of achieve similar or perhaps improved dosing intervals. So I'm not sure that, that was -- and then the sRNA itself, right, isn't getting complete inhibition. So that was acknowledged as well. So absolutely, that's, a complement is complicated, and that is exactly the concern in terms of infection risk versus efficacy. And there was also mention to these additional agents, which to my knowledge, some of these small molecules, others have been added on top of C5. So now you're further inhibiting the pathway. So I don't know, let's see how it goes. Because there is a substantial unmet need still there in terms of patient benefit, dosing, convenience and, of course, the things that were mentioned today, anemia, transfusion dependency, that are still there with some of the current standard of care. So I think there's a way to optimize and thread that needle that you're talking about and keep that safety profile where you want it to be. It's similar concepts. Let's do a little back and forth here with Kevin, I know, who's been thinking a lot about and leading a lot of effort in the CNS. I have my thoughts as well. But Kevin, do you want to offer some thoughts or remarks on the...

Yes. I mean, I think, first of all, the technology, the RNAi therapeutic technology, it's dose-dependent, right? So it's got pharmacology. If you want an 80-50, you go to a lower dose. And I think that's one of the benefits over sort of some of the emerging technologies that are really binary, it's kind of one and done, 0% or 100%. And one of the things that we do talk about, and I talk about it with my genetics friends, some of whom are at some of these companies, like that if you knock out a gene completely, it's not always what you want to do if you look at phenotypes across mouse studies, and Regeneron has one of the best mouse groups in the world, right? You start phenotyping things that are 100% versus 80% and sometimes there's a threshold. And if you look at sort of inborn errors of metabolism, you can look at things that are 95% down sometimes are okay, but 99% is not good. So I think those are things to think about. In that the other ability that we do have is something called reverse. So we're able to actually design molecules that if we have an annually dosed molecule or biannual, we can go in and reverse the activity over a couple of days with a different molecule ready with a competitor molecules. So I think that gives you exquisite tunability. And I think that's what you're going to want to see. Aris, I think you'd agree, in APP, especially the early onset mutations in APP or in presenilins that affect APP seem to be causative in the disease, right? And there are going to be a lot of arguments about Abeta, Abeta(40), Abeta(42. But a lot of the approaches that have been taken have not dealt with the other fragments of APP. It's a big protein, has a lot of involvement, both intracellularly and extracellularly, and turning off sort of the faucet by removing that protein or knocking it down considerably versus trying to soak up these various fragments that are aggregating, it's a very different approach. So that's kind of how I think about it.

I agree with that wholeheartedly. And the tunability in terms of just general knockdown, as Kevin alluded to, that pharmacology, that ability is there. What's harder to do, outside of thinking about Alnylam and this partnership, is to be able to say, "yes, I'm going to go after extracellular or intracellular," that's a big deal, right, to be able to hit it right there. I think also, some things are just not so simple, and the Huntington story, for example, is one of those. And I get quite excited about some of the things that we can do with Kevin and his team and their group around more specific approaches to targeting certain types of alleles, right, and preserving perhaps other alleles or function. And mind you that we can also, again, work together and assist these guys. We can look into our database and we can look into almost a couple of million individuals and say, what is this gene? Does it tolerate loss of function or knockouts, right? And we can incorporate that into the decision tree, right, and the mouse knockout, as Kevin alluded to. It's either totally tolerable and it's okay and safe to do that, or there is concern, as the neurologist who was talking about Alzheimer's earlier. We have data to support what level of...

Yes, I was just curious if you -- I don't know how much you can talk about it just based on competitive issues, but I was just wondering like, for APP or HTT, because I remember, I mean, at the outset of Alnylam's history, you guys are working on alpha-synuclein, right? You've got Huntington, you've got APP. How much querying of your database can you do, Aris, to figure out whether this subtype of the patient population will or should or may not respond or may not show a favorable phenotype?

So there are a couple of things wrapped up there, too, I think you mentioned. So one, if I'm gathering what you're asking is, we can actually look and try to get a sense of kind of dose needed. So in humans for the most part, we really have kind of a binary outcome. There's kind of heterozygotes, homozygotes. With more data, we get kind of variance in between. So we get kind of a dosage effect from genetics. And so we can put our heads together and say, "hey, yes, it looks like partial inhibition will have a great phenotype," right? Or man, we really -- it's like a complement thing, right? You really have to go all the way to get to any of that.

And can you look at something that -- all right, well, they had this variant, but they also have this other variant that negates the variant that we -- you can do that?

Yes. We can look at -- we might call those modifiers for example. And I think there's been lots of discussion today of PNPLA3 and HSD or APP and APOE, a lot of those types.

That's how Alnylam found fitusiran, right? You had the...

Yes. It was mutations in individuals that had an impact on a different living phenotype.

Right. So you can find that in silicon.

Yes. You can find that in silicon. I think the other is just also thinking about, as we're doing, sometimes you have extracellular and intracellular, if there's a target, you really need to hammer on, you can use both loyalties, right? And it's really opening up a whole new vista of thinking about how you go after these different diseases. We also have talked recently about our Gemini platform where we can now target 2 different genes at the same time, right? And so that also opens up the ability to think about these more complex pathways and to say, okay, I need to -- if I hit it here and I hit it here. Sometimes you want to hit it on both of those places 50%, right?

Sure.

But the combination of those 2 is going to be better than hitting any 1 of them, 80% or 90%. So that's also combinations that we start to think about it, and it gives you more real estate and more target space.

And how much you lean on VelociSuite, Aris, to kind of both valet targets as well as help inform pharmacology and...

A lot. Probably more so for the latter. So when you've got human genetics data, yes, it's terrific, like the recent obesity example we had. It's really terrific to see that so quickly the mouse knockout validates what we saw in humans. But I would say even more so, your point about animal pharmacology, that's really important, right? Because you get human genetics, but then you want to ask critical questions about can I have evidence that if I'm treating -- not having lifelong genetics and preventing conditions, but if I'm treating in some model of disease, can I have an acute benefit right there. And so the VelociSuite technology is fantastic. It allows us to humanize these genes, put in the exact gene knock-ins we've seen in humans, and also test our therapeutics in these more fully human systems. So we win in a lot.

Okay. Patrick, did you want to go?

How closely is Alnylam working with Regeneron on the discovery and identification of the RNAi drug targets? And then how quickly can Alnylam move from this genetic validation in an animal model to siRNA ready for human trials? And do you see a potential to accelerate development timelines?

Yes. I mean, I think, to answer the question, we work very closely across the board on the tissues that are of interest at the 2 companies. And we've generated tool compounds for them. and we do it ourselves. They also do it themselves with antibodies. We use all the different things that are available to try and intersect the human genetics with mechanism, with the ability to have biomarkers and all of the things that allow you to be quite successful in clinic, and then generally move things relatively quickly through the pipeline. Some of it depends on a little bit how the size of the gene and the target, right, and how much real estate you have is how quickly they move. But in general, we've been able to move things quite rapidly, as you've seen with APP and HSD and some of the emerging. I think you'll see more over the next couple of years as we move into the pipe.

Yes. I would echo that. We do work very closely from beginning to end. Alnylam has a terrific genetics group. They've been involved in U.K. Biobank and other projects like that. To your question about right at the initial steps of new target discovery, we're thinking about known targets, but really difficult ones, like the ones we talked about, Huntington and others. I mean, indeed, these are not solved by any means. And then the biology we do together, I think, is really important and valuable.

I'd agree and then just point out that Aris was kind of, very early on, our first deal with Regeneron was our U.K. Biobank and that led to discussions around NASH and then like, "Oh my God, we could do so much more together. Let's get together and build a pipeline within a pipeline."

Well, I don't know if people are aware of that. Again, just amazing amount of information on the Regeneron website site, but you have 30 collaborators now, Aris?

In genetics?

Yes.

No, we got to fix that website, it's outdated. It's over 100.

Wow. Well, I mean, just as far as sourcing genetic input is concerned, [indiscernible].

Yes, it's over 100...

Over 100, wow, okay.

The team pulls together about 20 or 30 a year. Why? Well, despite what we've talked about today and how amazingly it's worked here and there, we're also very self-aware that there are limitations to our current data set, right? If we want to be as successful as we've been in obesity, we could study 600,000 people's BMI; or in NASH, where we've got imaging on tens of thousands of people and all that kind of stuff. We need similar depth and breadth of data on dozens of diseases. And so it really takes continuing to add dozens of new cohorts and studies a year and continuing to sequence 1 million people a year, if we can, or more.

I think Aris would agree that also that increasing the quality and quantity of the phenotyping data, right? So the ability to access information of -- it's one thing to be able to find an allele with some sort of an effect, but then to be able to track what that's done to individuals across time, right, because it's really the ability to figure out, okay, medically what has happened over time to these individuals and be able to deconvolute that with multiple individuals with those same alleles, right, that are now causing something similar because every individual will have a different history of what's happened to them over time. And so some of the key in the numbers is deconvoluting what's similar, right, because they're going to have some differences.

The phenotypes are key, and let me give you a very stark contrast. We've been studying things like APOE, Huntington, all these things we've talked about here. And we know a little bit about what their mechanism is and what they're doing. But every time you read about it, it says, well, the function is still unknown or largely unknown.

That's what our expert said. We don't know what it does.

Yes. Then you look at something like HSD, which had very few publications before the discovery and collaborative work together with Alnylam. And to Kevin's point, the depth of the phenotype data told us so much, right? Your expert, he was terrific. NASH physician scientists could talk about constantly that, "Oh, we know that this gene is involved in hepatic lipid droplets. We know it's not involved in liver fat. It has no effect from human loss of function on liver fat. It has a big effect on inflammation and fibrosis and all that. So to Kevin's point, if you do the right phenotyping, imaging, biopsying, you add that to the genetics data, you really can start to understand the function of these genes and their variants.

Yes. I mean this might be a silly question, but I'm just curious. I don't even know if you know the answer, but what proportion of the new data sources that you access go to this sort of validation of the phenotype, meaning building on what's already been the foundation versus bringing in possible novel target discovery. Do you not know that ratio right now?

Well, again, because we sequence everyone's full genome in a sense, right. We're never really just adding kind of a niche hypothesis add-on data set. It's opening up the possibility to information about every gene, right? But the in-depth phenotype you're referring to, oftentimes, yes, that is very detailed phenotyping about someone's brain imaging or cognitive function or their autoimmune state, we're doing kind of massive immune profiling of the blood. Those are the types of phenotyping you might add only in some cohorts or studies where it's possible. And obviously, we haven't done that in several million people. So I don't know if that answers your question, but each data set really has the chance to inform...

Well, I'm just curious, like if you get whatever, an academic group, or like using GRP, you have the university in Mexico. Do you sequence every single individual in that database?

Yes.

So how do you do that?

How do they do that?

How do you find them all?

Sorry, find the...

Find the individuals, yes.

Well, yes, it's, I guess, simplified to 2 things. One, we collaborate with the existing community that's out there, and they've been working, in some cases, for decades on building the Mexico City study, or in new cases, they're building prospective new studies like that, right? Or we just have to start from scratch. And we say, we really want to work on Alzheimer's or a rare autoimmune disease. And we have to go start the studies, enroll the patients, do the phenotyping that we need for that study. So it's a long process.

Wow. And that's now I can see why you guys are so aligned with Alnylam. This is what Alnylam did with ONPATTRO, and went to the investigators, the polyneuropathy patients in Portugal and all these far flown places to...

To go build it. If you don't have it, you have to build it.

Right. Creative stuff.

So yes, I have a follow-up question for Kevin on the CNS platform. I think with the liver platform, I think there's a lot of confidence, rightly so based on all the success there. But I'm wondering if you can describe in more detail the CNS platform that Alnylam has developed with the C16 conjugate, how it's differentiated maybe from some of the other approaches? And then maybe I have 1 more follow-up.

Yes. So one of the things that we're quite excited about, right, is we know from our liver platform that what we see in nonhuman primate species, these preclinical species translates really well into human, right? And we've seen that time and time again with our liver platform. And the chemistry of what we found is that the CNS tissues are very responsive to RNAi. And part of that is, it goes back to genetics, it's Ago2 and RNAi, that whole mechanism, that whole pathway is conserved in all the different tissues, right? And it's being utilized every day. So we're just taking advantage of a system that is functioning in you and I constantly every day. So we have microRNAs that are moving in and out of that. So you have the pathway that is highly conserved. We've found that the chemical modifications and the things that we've utilized in liver by and large are very similar. So the duration of action is quite long, similar to how it is in liver. So part of what we needed to uncover is how do we get better distribution. So currently, there is a blood-brain barrier that everybody is working on. We continue to work on it. But right now, we're an intrathecally dosed therapy like SPINRAZA and some of the other oligos that have been out there. If you're going to be intrathecal, one of the benefits that you should try and look for in the drug is to be long-acting, because you really don't want to access that space. Every time you do, it's inflammatory and there's risk to the patient. So having very long-acting agents, which we have with our APP molecule, and then the C16 actually helps good distribution throughout the CNS, even into deeper brain regions and gives us, especially in the primate models to date, really nice 80-90 knockdown across different tissue types. And so we're fairly confident. Again, the proof is in going into individuals. So we've been able to clear our safety studies and show that the molecules have both really nice long-acting duration, really good pharmacodynamic activity and are safe enough in the preclinical species to go into a human trial. So I think that's where we are with the platform and we're hopeful. But again, we'll have to show, just like we've done in the liver, we need to prove it. And so with our colleagues at Regeneron, we're about to start that journey into human individuals in the Alzheimer's space. The benefit of doing APP, one of them is that there's really nice biomarkers, there's human genetics. So we'll know very surely that we've engaged APP, that we're lowering different forms of APP through measuring in the CSF, that allows you, like in the liver, with some of our early programs to get the dosing right, to the point earlier to make sure you dose up slowly and you see what you see and make sure you don't go too far. So I think those are all the benefits of actually starting and one of the reasons we decided to start with APP.

I'll say the preclinical data are really compelling and something that Kevin reminds me, it should not be lost on people, right, that there's different generations and iterations of these platforms. And one of the many great things we love about working with Alnylam, they are truly a science and technology development company. So just look at how they've been a pacesetter and continuing to advance the liver platform, and imagine what the possibilities are in the CNS and other places that we're working together as well.

And some of the differences that we see with the antisense, how it goes, some of the recent trials on SOD1 and unfortunately, with Huntington's is that, first of all, those patient communities, it was just not good days, and I wish I had it all worked wonderfully. But at the end of the day, I think what they've seen is, some properties that they've seen with systemic dosing and some inflammatory properties of those particular molecules, which unfortunately hasn't enabled them to get to a dose where they're getting really significant knockdown, right? I think recent data with SOD1, I think it was 28% to 30%, probably just not enough. There's some hints there that, that thing was working. But I just think they weren't able to get to a high enough dose. And so far with our preclinical studies similar to the liver, what we're finding is that we don't have those inflammatory properties built into the molecule. So I think that's what we're hopeful for to continue to move this forward.

Yes. And I guess my only follow-up question then would be, can you just kind of talk about the competitive advantage having this collaboration provides to Alnylam with Regeneron, just in terms of identifying the CNS targets. I mean we're moving forward first with ALN-APP. But presumably, there's additional work going on, of course, with Huntington, but elsewhere, I'm sure. So maybe you can kind of talk through that, and how broad of a pipeline could there ultimately be on this platform? Presumably, it can be as large as liver, but maybe you can kind of talk us through that.

Yes, I don't think there's any shortage of targets in the central nervous system. I think it's a question of which goes first, second, and third, and why. And the impact that you can have to patients' lives is just measurable by personal experience in my family with Parkinson's that drives me. And there's just a lot of these diseases where what's available is marginal at best, right, to really have an impact. And so I think, in terms of working with Regeneron, I mean, I think, Aris mentioned, they have the genetics in a way that we don't. We actually obviously have access to U.K. Biobank, but they have access to a lot more. They're world-class in their animal model systems and the ability to generate those to humanize things and to generate that kind of data quickly around these targets. So that allows you to try and derisk some of it. And then they are 50-50 partners with us as we take this in the clinic. And so we bounce ideas off of each other on the clinical development side. And I think when you do that with companies that are like-minded and science driven, you always come to a better answer.

Just out of curiosity, how often do you guys meet up. Is it monthly, quarterly? weekly?

It's a very broad collaboration. So I would probably say somebody is talking to somebody else daily.

Right, right. That's awesome. Well, something like -- and I would think, again, getting a little maybe too granular geeky, but when you have a party like Regeneron that can curate these databases like the U.K. Biobank, because I can remember, I'm old enough to remember, when you were sequencing the genome and the quality controls were terrible. And if you don't get good data in, you don't get good data out. So if you got Regeneron acting as your sort of gatekeepers, so to speak, to these databases, you're going to get, as you said, Kevin, derisk it for you, that you don't go down blind alley. You're actually going after a target that has an approachable phenotype. Is that a fair statement?

I mean I would say, for us, it's been a wonderful collaboration on the human genetics side and allows us to do things that we wouldn't be able to do on our own, sure. We have our own internal group that's high quality and has been able to curate some of the data. But certainly, the collaboration allows us to, what I call, punch above our weight class, which is a wonderful thing. Aris, I don't know if you have comments around it, but...

Yes, it's a terrific working with these guys, and we really do a lot of thinking together. And to your point, we really scrutinize these findings and want to make sure that they're real beyond a shadow of doubt, and then we're off to figuring out the biology and therapeutic strategies.

Okay. I don't want to spoil the party, but can we talk about maybe bring up GPR75? I mean, great target, right out of the Regeneron Genetics playbook. I didn't have a chance to look at that. Do you not want to be in as big a market as obesity, you don't like the risks? Or was it something else?

So we believe GPR75 is a good target. I think one of the questions about GPR75, if you look at the overlay of that target with the technology, is, we have to say, well, is the liver alone enough in that case? Or are there other tissues and organs involved. So we're still looking at it obviously. And time will tell whether that target is suitable for where our technology is at this moment or whether it's not. And so Aris, I don't know if you wanted to comment further?

Yes. Absolutely. Kevin and colleagues took a look at it. We get findings that you can imagine, the excitement, and wanting to think through it together. So it's, as Kevin mentioned, we've got a lot of early enthusiasm that the CNS is where we want to be on that type of target. And can we make that all work out for obesity in that condition. And I think it will be fantastic if we get to some of those future iterations and platforms that we talked about, where perhaps we don't have to keep accessing through intrathecal. I mean there's morbid obesity, unfortunately, in so many individuals. How many people every year are going through bariatric surgery, very invasive, right; procedures where I think intrathecal administration is probably pretty attractive alternative for the more severe forms, right? But gosh, if you could take it to an even other access level and deliver that, we're talking about, obviously, the future, but future versions of something like that could be even broader impact. Anyways, we've got a lot of work to do, as you know, just...

Yes, I misspoke before. I think I said liver instead of CNS, but obviously, there's...

No, we knew what you meant. Yes.

Well, is GPR75 more widely distributed? I mean where is it found in like, or is it found in isolated number of tissues?

Expression is mostly in the CNS. I'd have to... We are working on so many things, I have to recall if there's...

I don't know if it was CNS, liver, pancreas, muscle?

Sometimes we get into that conundrum when it gets to actually the fatty liver or metabolic diseases more broadly. You have some things that are expressed in the liver, but maybe they're also expressed in fat and other places. But again, these guys wrote the playbook on having the reagents to be able to test that hypothesis and prove it one way or another. So fortunately, we get to triage those things quite quickly and have a very compelling portfolio, not just of HSD, but things behind that, actually, that are, frankly, even larger effect size and even more compelling and more broadly applicable that we're working together on between Alnylam and Regeneron.

Yes, I'd say one of the things that we like about working with Regeneron to the issue of, we'll find genetic targets, and then we can go ahead and validate what and where and how they work and do that in a science-driven fashion, and that drives decision-making on what MOU do you want to use to go after it, right.

Yes. Well, what's cool about it from a business model standpoint is that even though both companies have considerable market caps, you're still well below that of Merck or Pfizer or J&J, yet you have the speed, you both have lean organizations that can move quickly, and you're both yet small enough, that I mean enthralls my mind about covering Regeneron, because like if GPR75 really busts open, it's like, "Oh my God." Whatever you're at, $50-something billion, there's a lot more to come, same with Alnylam. So anyway, it's...

Yes. Now for both companies, right, that's exactly what you described. And I don't know how you feel, Kevin, but there's so much going on, right? It's been really, really rewarding. I think we're going into year 4 of this, right? And I think the initial 5 years talking about 30 programs potentially something like that. I mean I'm not sure people appreciate just how hard that is. I mean, we do have to talk every day to try to identify those 30 opportunities and ones that are kind of pragmatic and tractable. But you're right, it doesn't take many of those to hit when all of a sudden, this partnership is at a whole other level in terms of what it could deliver, potential value for patients and for each of the companies. I mean it's a really exciting to be part of.

Yes. Go ahead, Patrick.

Yes. Sorry, I was just curious because a comment was made earlier about how it's not so much is there -- are there enough targets in the CNS, but what should go first, second, third, et cetera. So I'm just curious from both companies' perspective, how do you decide that? What are the factors and variables that kind of come into play there? And when do you decide that, yes, this is, ALN-APP is what we're going to go with first?

Yes. I was going to say we do what you should do, which is we get the scientists and the clinicians together and we go through the data and what data needs to be generated and how are we going to generate it and then we go round and round and we go back and forth and we hopefully come up with the right answer, right? And as data comes in, sometimes we change our mind, right? And that's okay, right? And I think as long as you're data-driven, and both companies are like-minded that way, then you get to the right answer. But you also can't go round and round forever. So we do make calls and then decide what's going for second, third, fourth, and Why? And it's sort of integrating patient needs, you're integrating the size of the indication, the strength of the genetics, the strength of the biology behind it, and what's known about the targets, and then you choose. And we've continued to move a very sizable pipeline forward.

Yes. Nothing more to add.

And then just the other follow-up I had was on kind of delivery of sRNA to CNS, currently delivered intrathecally. Should we expect kind of an advancement on that front? Or how should we think about it?

I mean we think that an infrequent dosing in the IT space is sufficient for most of these diseases that are really high on that medical need, right? Obviously, we'd love to be able to get the molecule across the blood brain barrier, but it's been one of the holy grails of everybody and it's a hard problem. So do we work on it? Yes. Do I think it's coming tomorrow? I hope so. But maybe somebody smarter than me, but we're continuing to work on it, right? And so I'd say that that's one of those things that we'll continue to depend on because of the payoff for it. Although if you really have a very infrequent IT dosing, I think that's suitable for most of the things that we're trying to go after at the moment.

Yes. Again, not much to add. If every one of these things, knock on wood, if we were fortunate enough, that they worked, I don't think intrathecal administration would be a hindrance. And remember, we're the guys who 10, 15 years ago asked, "Hey, we'd stick a needle in someone's eyeball."

That's also true.

I'm kidding. Obviously, others have been working...

I'd actually like to see the e-mails that went back and forth around that at the time, because I'm sure it would be a bunch of nay sayers going, "Oh, you could never that. Are you crazy." All right. Well, I think we're good for now. That was awesome. Really appreciate the candor, especially, because you can't always get folks like yourselves to open up and give us some insight into what's going on at both shops. So we very much appreciate it. We'll keep a very close watch on this. I'm obviously a big fan of Regeneron. Patrick is a huge fan of Alnylam. So we wish you both the best of luck.

Yes. Thank you guys.

All right. Enjoy the rest of your day, gentlemen.

All right, thanks.

All right, take care. And thanks, everybody, for joining us. Patrick and I are around to have follow-up questions. Hope you enjoyed that folks. Take care.