Good afternoon, everyone. Thank you for joining us for today's webcast as part of our ongoing Genetic Medicine for Generalists series, where the tagline is, "Genetic Medicines are complicated, but the conversation around them doesn't have to be." And as you might know, the goal of our conversations is to take things back to the basics and bring everybody up to speed on the latest and greatest in the space. On that note, the more the merrier, in terms of audience questions.
So please don't be shy about asking questions. Feel free to enter them into the webcast interface, and I will work them in as we go. And importantly, remember, there's no such thing as a stupid question, so please ask away. And with that, I am very pleased to be joined today by Kevin Fitzgerald, Chief Scientific Officer at Alnylam. Kevin, I'll turn it over to you to give a brief intro to yourself and your background.
Sure. I'm Kevin Fitzgerald. I'm our Chief Scientific Officer. I've been with Alnylam for nearly 20 years, and I've been studying this, you know, new area of biology called RNA interference for probably 25 or closer to 30 years. Happy to be here with you today, and happy to sort of discuss something that's near and dear to my heart, which are RNAi therapeutics, especially as we're moving into the, the central nervous system with, with these therapies.
Definitely, definitely. Excellent. No, thank you. Thank you again for joining us today. And you are the perfect person to be having this conversation with today, I think. And, I should also say for everyone on the line, we will start high level, as I said, and kind of drill down into the details as we go with a focus on the CNS pipeline. So I forgot to come up with, like, a HELIOS- B joke at the beginning, but assume I did, haha, laugh. Now we're moving over and focusing in on the CNS stuff, because we are very excited about this as kind of the next, next area of the platform, as I know a lot of people are as well.
So, with that, as I said, taking it all the way back to the basics, what is RNAi, RNAi interference? How does it work? If you were kind of somebody's brand new, like, what is this cool new thing we've been talking about?
Yeah, so where I like to start is anybody who's, you know, had a cup of coffee this morning, this afternoon, congratulations. You know, your naturally occurring microRNAs, or RNAi, has happened in your liver. And so it's a way that it's a mechanism that organisms over time have developed all the way from this soil worm called C. elegans, it's microscopic, all the way to people to control the way that genes go up and down. So I think of it, you know, sort of as a switch to turn things on or off or reassess. So more of a, you know, the ability to turn a gene up, you know, in particular, turn a gene, more towards the off position. And so you can really control the level of gene expression.
And the way that it works is that there's something called double-stranded RNA, and these are short double-stranded RNAs that was really discovered won a Nobel Prize by Andrew Fire and Craig Mello, a number of years ago, where they discovered that this was working in that same, you know, soil worm. And then, you know, Thomas Tuschl and others were able to show that this worked in more mammalian cells. And so what we've set out to do is to mimic that natural, naturally occurring system by using a synthetically made small RNA that we actually dose subcutaneous in general, you know, and, you know, it goes in and it sneaks its way into the liver and into this particular case and then turns the expression of a gene down at the messenger RNA level.
And so it's a way to take something that may, you know, if you think about, sort of antibodies that everybody's familiar with, they sort of mop the floor, and this, you know, RNAi is a way to maybe turn down the faucet or turn off the faucet, as a way to control gene expression.
I like that analogy a lot. I love a good analogy. That's excellent. Okay. And so you mentioned how it turns off the faucet. It's kind of modulating, kind of the expression of some of these genes. How does it do that? It's like binding to the RNA copy and then or not?
So.
Explain to us how that works.
So it sounds a little bit like science fiction, but we'll inject our molecule subcutaneously into the skin. It will then survive going from the skin into the bloodstream. We then have a ligand and receptor pair, so that's something that it will bind to in the liver cells as it's going through in the bloodstream. It will grab a hold of that, and then it will be swept into the cell, into a compartment called the endosomal lysosomal system. It will survive that and then go into this complex that's called the AGO complex.
And that's the complex that sort of does its function. So it'll bind in there, and then that complex will scan through every messenger RNA that's being made or every RNA, and that's what produces proteins in the cell body. It will find the one that it matches, and then it will clip it. And so by clipping it, it will degrade, it will turn off. And so that's happening in 280 billion hepatocytes simultaneously with this technology. And so what happens out of that, if there's no messenger RNA, there could be no protein, and so protein will go down.
And so you could measure that. You know, for instance, one of our early programs was a drug called inclisiran, which is now known as Leqvio, and that was for hypercholesterolemia. And so that drug you inject subcutaneously, every 3 to 6 months. And what happens is that that goes in, does all those things that I said, and ends up in the removal of a protein called PCSK9. And then more cholesterol goes into the liver and is taken out of the bloodstream. And so you lower your LDL cholesterol.
Got it. That's really interesting. And I guess, are all silencing RNAs or RNAis or RNAs, sorry, that kind of turn down the faucet created equally? Are there different ways to go about this? And I guess, what's the special sauce, I suppose, about the way that Alnylam does it?
Yeah. So, you know, very early on when we tried it with just sort of I told you it's sort of a naturally occurring process. So we tried to mimic those naturally occurring molecules. It didn't work at all. And so what we've had to be able to do is to chemically modify. So while we call it RNAi, you know, RNAi therapeutics, there's really no RNA left in the molecule. It's all a different chemical modification. And what that does is it stabilizes it because there are things in the body called endo and exonucleases that love to cleave RNA.
So they chop it into very tiny pieces. And so what we do is we put chemistry across the molecule so that those endo and exonucleases can't chew it up anymore. So that allows it to survive long enough for its action. And so we spent a large number of years trying to figure out sort of that complex pattern of what you could modify and what you couldn't so that it would maintain its ability to go in and do what it needs to do, which is to bind AGO2 and then cleave the RNA, yet be resistant to degradation, you know, so it had enough time to get there and do it.
And so all of our molecules are essentially fully modified at this point. And then we've taken this ligand, you know, put on the end of it. It's a sugar called GalNAc. And it turns out that there's a receptor, and that's something that it binds to in hepatocytes. That's about 1 million copies per cell. And that allows it to go in. Now, as we pivot to the central nervous system, a lot of that, you know, those learnings, absolutely true in the central nervous system, but we did have to use a different ligand. So it's getting into cells via a different mechanism.
Mm-hmm. Okay. That's helpful. So as you've just described, you have these modified RNAs, which maybe are not really RNAs anymore, but modified, kind of to do their job. You're adding this ligand. I kind of like to think of it as like a tag or maybe a key you're attaching to the molecule.
An address. Yeah. It's like an address.
Yeah. It's like an address. Yes. Okay. So in the liver, that's GalNAc, and you all have made a lot of progress there, progress there in that front. So yeah, talk to us about the CNS. And I guess maybe let's start off with, in terms of the modifications that you make to the RNA itself, are there... is it the same modifications? You kind of have to, like, start all over when you think about targeting the CNS or different organ systems as you go along the way?
Yeah. So there are some slightly different modifications. In particular, the ligand that we use is a long it's sort of a sticks sort of a fat on there instead of a sugar. And that allows it to distribute throughout the brain. And then some of the modifications are a little bit different, you know, on the molecule itself in order for it to be able to similarly survive in the right cells and get to AGO2 within the different parts of the brain. Now, the brain's much more complicated. There are, you know, trillions of neurons instead of billions. So there's an order of magnitude different difference in complexity.
Mm-hmm. Got it. Okay. That's helpful. Another really, like, taking it back to the basics type question for me before I turn it over to, to Juan on my team who's the expert to dig into the weeds a little bit further, but why is getting stuff into the brain so difficult?
Well, it turns out that the brain has evolved to not want to have bacterial infections or viral infections or other things that might get into your bloodstream, into your brain. And so there's something called the blood-brain barrier, which is essentially like a big wall that only lets a, a few things through. Certainly not very large charged molecules, which our RNAs are. And you might imagine that viruses and bacteria have their own RNA, and viruses in particular, the one thing they'd love to do is to take over your cell machinery and make more virus. So you have an immune system that recognizes that, and then you have this thing called the blood-brain barrier that basically excludes anything that's too big, too charged.
And so, that's been, you know, even in the small, even in developing small molecules like, you know, the types of things like, you know, aspirin and those kinds of traditional small molecules, you have to design them very specifically to get across. Antibodies can go across, but only in small quantities. And these, without some sort of an engineering, because these RNAi therapeutics are large, they don't really go across at all on their own. Now, we've got technology now that is allowing us to shuttle some of them across that blood-brain barrier. But currently right now, we're actually going straight into the spine, in order to get across that blood-brain barrier and into something called the CSF or the spinal fluid.
Got it. Okay. Super helpful. I think, I'm gonna turn it over to Juan now to dig into maybe that fat I think you mentioned attached to the molecules.
Sure. Thanks, Winnie. Appreciate it. Yeah. I'd love to dig more into the address as you called it, or the ligand, the fat. Can you start off by just telling us a little bit about Alnylam's approach to CNS delivery with respect to that ligand or that fat?
Sure. So we use something called C16, which means there's 16 carbon chains, right? And that's, you know, there are 16 carbon chain fatty acids found, again, naturally occurring in your body. And they traffic, you know, in different ways and can get into cells, in different ways. And one of the reasons that we wanted we were looking actually for something do you imagine as you go into the CNS, as I mentioned, there are different cell types. You know, there's neurons. There's something called astroglia and microglia versus just, you know, mostly hepatocytes in the liver.
And most of the diseases, there's huge unmet medical need within the central nervous space, you know, diseases like Alzheimer's and Parkinson's, Huntington's disease, to mention a few others. And what, you know, when you look into the targets that are validated genetically in the human genetics of those diseases, what you find is that a lot of those targets are expressed in almost all of the cell types. So there's something called almost ubiquitously expressed. And so when we were looking for a delivery strategy, it was a little bit different than just trying to target hepatocytes.
Now we had to try and target multiple cell types. And so in doing that, we found and we screened through a bunch of different fatty chain lengths and places to put them on the molecule. We found that C16 was very effective at getting distribution throughout the brain after a single intrathecal injection and getting into the many cell types that we were trying to target in a lot of these diseases with high unmet medical need.
It sounds like you've touched on this a little bit earlier, but in terms of testing out different versions of C16, how much optimization kind of went into it, whether, you know, were you looking at C15 or C17, or was that something that, was it just found that C16 was the most ideal?
No, we looked at a wide variety of chain lengths, a wide variety of where do you actually attach it to the molecule? We looked at a lot of iterations of that to try and find, you know, the one that we thought would be both safe, effective, and also, you know, easy to scale. So the other thing that you have to be able to do is the molecule is it can be the, the greatest silencer in the brain in the world, but if you can't manufacture it because when you're trying to put it into a vial and solution, it all falls out, then it's not probably gonna be a good drug. And so there are multiple things that you're optimizing for when you're trying to think about making therapies. And so we went across all of those different types of modifications.
It wasn't just fatty acid chains that we've tried. We have also tried other ligand receptor pairs and continue to work on that, by the way, 'cause there are cases where maybe you only wanna get into one cell type in the liver, in the CNS, one brain cell type. And so we continue our efforts there to sort of target some of them, but for many of the diseases, like I said, you really want broad distribution. And C16 turned out to be, you know, give us the ability to rapidly knock down a target throughout the CNS, including in deep regions of the brain like the striatum that typically have been hard to reach, with antisense technology.
Mm-hmm. Mm-hmm. Just to really kind of focus on the differentiation point of this, can you tell us just a little bit about what normally happens or what would happen if you were to inject just naked siRNA intrathecally or through ICV?
Yeah. So naked siRNA by itself, it doesn't distribute. It doesn't have properties of, like, binding protein. So it, it tends to stay closer to the site of injection. It also, without the chemical modifications, would get degraded very rapidly. And so while you'll see a little bit of activity with that, maybe locally and maybe a little bit up the spine, depending on the dose, it really wasn't optimal, you know, for a therapy where, you know, what you're what you're really trying to do because it's an intrathecal dose at this point, we will get across the blood-brain barrier. It's just a matter of time. You know, you wanna do that injection as infrequently as possible.
That's where the stabilization chemistry comes in so that, you know, you're looking at once in 6 months, maybe once in 9 months or a year, you know, possibly depending on the target, you know, injection into the CSF.
Mm-hmm. And if I'm hearing this correctly, the stabilization chemistry that kind of goes into this C16 modified siRNA, it's different based from some of the previous generations of siRNA in order to enable that sort of protections and nucleases and that distribution?
It's a lot of the same chemistry, but there are also a couple of additional modifications that you use in order to get activity across the brain. So, you know, it's very similar. So we could take all of the learnings from the liver, and we didn't have to start, you know, all over from ground zero. But there still were some learnings that we've had to do along the way for both, you know, safety and the efficacy.
Gotcha. And I guess looking at differentiation again a little bit more, when you're thinking about, like, large molecules or some of the antibody conjugate approaches that have been, used for CNS delivery, how is this differentiated, I suppose, from some of those approaches?
Yeah. So, you know, I think so far we have a lot of activity with antibodies to try and get across the blood-brain barrier as others do. A couple of different targets there, transferrin receptor, other targets that seem to get some material across. Maybe you get a 50% to 60% lowering of the target across the brain, pretty high doses and a lot of doses IV in order to get there. So there's definitely some optimization work that needs to be done on that side. So I said it's not really a matter of if, but more when as we continue to optimize that approach.
But right now, you know, the go-forward approach is, you know, to get, you know, 90%+ knockdown throughout large regions of the brain is to really go in, you know, into the intrathecal space and give a dose there.
Awesome. And in terms of the regions of the brain that you are accessing, can you speak a little bit on that? And are there any regions of the brain where there might not be substantial uptake in your chemical?
Yeah. So it is a little bit dose-dependent, right? But so that a little bit higher of a dose will push it a little bit further into the brain regions. But in general, we have, you know, good expression, good, good knockdown and rapid knockdown even within deep regions of the brain. I would say the one cell type, I think it's the oligodendrocytes that tend to have a little bit less silencing. But in general, across the broad level of cell types and, you know, in different regions of the brain, we have really nice silencing. And again, it's a once in six months to, you know, likely once in a year injection.
I guess kind of going off of that in terms of the oligodendrocytes, what is the significance there? Is that something that you wanna target more or less of, or?
You know, it depends on the disease and the disease area, right? For the targets that we've chosen, you know, luckily the oligodendrocytes aren't highly involved. And, you know, again, that is also a matter of dose. So if you move the dose up a little bit higher, you can get more into those cell types.
Of course, you guys have done quite a lot of modifications in order to have a great safety profile. Can you speak a little bit on that in terms of the additions that you've made or safety concerns or concerns that have been done to alleviate safety concerns?
Sure. So, you know, luckily, you know, within our, you know, our clinical experience so far, we've had good luck with ALN-APP. In our preclinical experience to date, you know, these things are highly effective, and, and we're very happy with where we are in the safety profile. And I think when I think about safety, I think about two things. One, I think about dose, and I think about dosing interval, right? So how much dose do you have to give? 'Cause safety is always a product of how much drug exposure do you get, and then how frequently do you have to dose? And so very happy with, you know, where we are with very low doses of, you know, you know, 50 to 75 mg, you know, milligrams, giving us up to 6 months, you know.
So, you know, that's a very low dose to be giving very infrequently. And so you'll find that as you dose a drug less and less frequent, you're gonna have a nice safety profile. And so that's one, I think, of the benefits of our platform over some of the others that are out there is that we've been able to show this remarkable, you know, rapid knockdown of target, but then also, you know, this really remarkable duration across all areas of the brain.
Definitely. And I'd love to talk now on move towards the data side. I think you've already referenced a little bit about it and love to hear more about it for sure. How did you go about sorting through the different targets and diseases and deciding where you really want to go first with the innovations?
Yeah. I mean, so for me, you know, my background actually starting early on, you can take it all the way back to, you know, I talked about that soil worm. I used to do genetics in that soil worm where RNAi was discovered. And then I went on to look at human genetics. And so the way that I think about targets is I look at human genetic data first, right? And so if you think about the pipeline that Alnylam has had historically, all of our targets have had been based in validation by human genetics.
And what do I mean by that? So let's take PCSK9, which was one of our first liver targets. There are people out there that have so-called gain of function or too much PCSK9. They have more than normal. They have very high LDL cholesterol levels. They get heart attacks early. Then there are people who have half as much as normal. So they have a mutation in one of their two PCSK9 genes. Those individuals have lower, lower LDL cholesterol on average and tend to be protected from heart attacks and strokes, right?
And then there are a couple of individuals that were identified, three or four, that have no PCSK9 at all. And they have an LDL cholesterol of 20. They'll never get a heart attack. And they're, you know, appear to be healthy and happy. And so therefore, right, that target to me is genetically validated. That means that I know that if I can knock it down 50% or more, I'm gonna have a benefit in the long run in the disease of hypercholesterolemia. I know that if I go too low, there, while there's people that don't have any of it, so that's okay.
And I know that it's causative because, you know, the people who have too much always get the disease, right? So those are the kinds of targets that we think about. And if you pivot to our first target, which is amyloid precursor protein or APP, there are human genetics that suggest there are people out there that have mutations in APP. So they have an irregular APP where it has too much function. Or there are individuals that have multiple copies of APP. So they have too much function.
Those individuals get early onset Alzheimer's disease. And so they can get Alzheimer's disease, unfortunately, in their thirties and forties. And so we know there that lowering that back towards normal or below normal should be helpful. And that's been some of the hypotheses around it for years. Now, nobody's really been able to do it in the way that we're doing it. So people have had antibodies to these things called A beta 40 and 42, which are fragments that come off of APP. And those fragments accumulate in something called plaque in the brain.
And those are so-called Alzheimer's plaques. And, you know, you have antibodies that go and bind those and try and clear them, okay? And so what we're doing instead, instead of trying to do that, we shut off the production of the protein and let the body clear it naturally. So there's always this mechanism of all of us are making those fragments. They're trying to deposit in our brains, but they get cleared. Over time, as we get older, it seems that that clearance mechanism is less robust.
So it's like a little bit like a partially clogged sink, right? So first you've got water running. You've got, you know, water going through the sink. It gets partially clogged. If it gets too clogged, eventually the sink fills up and overflows, right? And what we're doing is really turning off the faucet and allowing the body, the, you know, what's left of that drain to sort of clear, right? And so that's the hypothesis. It's very similar to what we've been doing in the TTR space where there's a protein that misfolds. It aggregates in these things called plaque, in this case, in, you know, either in the heart or in the neurons. And then you shut off the source and, you know, lo and behold, the tissues start to clear.
Fantastic. Wendy, I'll turn it over to you if you want for APP.
Excellent. So yeah, that was a really helpful kind of introduction, I think, to how to think about APP. And you mentioned, you talked a little bit about what goes wrong, but before we get there, I guess, what do we know about the APP protein? What does it normally do, in patients who don't have an issue, I suppose? And then we'll kind of dive in a little bit more to what happens when they do.
Yeah. So, you know, what we know about APP is that normally there are, you know, it's actually a very complex protein. It's got, you know, a portion that's inside the cell and a, and a large portion that's outside of the cell. That, that outside portion tends to throw off these peptides, A beta 40 and 42. 42 in particular in Alzheimer's disease seems to be an issue. And we'll talk about a different disease later called CAA, which is not, I call it, it's almost outside Alzheimer's disease of the blood vessels instead of the portion of the, you know, instead of the, the brain itself.
And so, you know, what we know is that in the disease, like I said, if you have too much of it, there are other mutations that, in a different gene called presenilins that actually clip that APP protein prematurely. It gives you more A beta 42. They also get early onset Alzheimer's disease. So, you know, what we know is that, you know, that protein is intimately involved in the development of Alzheimer's. And so the hypothesis is that if we lower it, both the intra and the extracellular domain, that we can, you know, help with that disease.
The intracellular portion, there's not as much known on what it does, but we do know that it aggregates inside of neurons and it makes, you know, some of the structures within those neurons irregular. So we also think that lowering that could also be quite beneficial in these diseases.
Helpful. And then I guess relative to CAA, so you kind of just mentioned it, but in Alzheimer's, so you're saying the plaques or the clogging up of these proteins happen in the brain, in the neurons themselves, but as you alluded to in CAA, it's happening, same thing happening, but just in different cell types in the blood vessels. Is that right?
That's, that's technically right, although, you know, it's not that straightforward in that, you know, up to 20%, probably, probably more because we haven't been doing brain imaging that long as a diagnostic. A lot of it is a mixed disease where you will have plaque in both places, right? And so, you know, part of that's getting picked up now where, you know, the antibodies that have been recently improved in the news that bind, you know, A beta plaque, the individuals who actually have CAA or plaque in their blood vessels actually don't tend to do so well.
It's something called this, something called ARIA, which is, you know, in, in the brain, which they're actually now trying to avoid. And so there's a lot more imaging going on, which is actually finding more CAA patients or these more of a, more of a mixed phenotype. Our data, you know, in preclinical animals, there is a rodent model of this disease where they get plaque in both places. So they get it in the blood vessels and they actually have the what happens when you get it in the blood vessels, the blood vessels become fragile and you actually start to bleed in the brain.
First you have small bleeds called microbleeds and then eventually you can have much larger and they tend to lead to much larger bleeds or stroke. And so even the microbleeds can impact, as you imagine, if you had bleeding, you know, bleeding in the wrong part of your brain, it might impact cognition, right? And so in our preclinical models that mimic both, when we lower APP in those models, we actually clear out of both places. And so we clear the blood vessels up. We actually prevent the bleeds and then we, you know, clear that plaque out of the neurons as well, and the neurons start to look more normal.
Got it. Got it. Okay. That's helpful. Once again, this is sounding a little like TTR to me, and like in there we were talking about heart versus neurons and maybe some patients have mixed disease. Here it's sort of the same, but all in the CNS.
Yeah. It's a very similar, you know, plaque and plaque, right? And yeah, so plaque is just basically the accumulation of misfolded proteins, a little bit like clogging a sink, you know, it's like a hairball you stuck down in the sink and, you know, sometimes it's partially clogged, sometimes it's, you know, you try to keep it from being fully clogged.
Yep. Yep. Okay. That is helpful and seems like a fairly straightforward problem, I guess, as you've set it up related to APP, but has one that, a problem that's been hard to solve so far, at least from an antibody approach perspective. So I guess can you talk to us a little bit more about kind of what makes this disease hard to target from an antibody perspective? You touched on it a little bit, in the sense of kind of, you know, your approach is shutting off the faucet versus trying to, I don't know, chew up the hair clog maybe, but there's different antibody approaches as well. So can you help us understand maybe just where the challenge is and why maybe your approach, which sounds to me like kind of going further upstream maybe, is the better way to do it?
Upstream. Yeah. So it is upstream. And, and again, going back to the analogy of sort of mopping the floor, right? You know, that's kind of an antibody trying to mop it all up that's already there versus shutting off the faucet. You know, and so, you know, the antibody is number one, you know, they need to get across the blood-brain barrier. You know, you're not putting them in directly. Number two, they tend to bind these plaques, and create inflammation.
And part of that is creating inflammation to sort of clear. And so, the good news is that they are able to clear the plaque out. The bad news is that in the process, sometimes you can get an inflammatory response. The other aspect is that I talked about the, the sort of extracellular. So that's the stuff that's outside the cell that's going to other cells. The antibodies are good at touching that. The stuff that's actually going on inside the cell, the antibodies don't go inside the cells, right? And so what we're able to do is now shut off both the stuff that's being secreted and goes outside the cell, those fragments that are coming off the surface when APP is cleaved, but also that intracellular domain that we think is very important also in the disease.
Got it. That's helpful. A related, audience question here. How is your mechanism different from BACE inhibition?
Yeah. So again, the BACE inhibitors, if you look at what they're doing, they're affecting the cleavage of A beta 40 and 42. But they're not actually touching the intracellular domain of that protein. And there are other peptides that come off besides 40 and 42 that the BACE inhibitors didn't change. The other thing with the BACE inhibitors is, you know, a little known, well, probably if you've studied the BACE field and I was at Bristol Myers, one of the things I worked on was BACE inhibitors. They don't just hit APP. So they have a lot of other, you know, there are other substrates that they go off and cleave. And so it was never really sure whether some of the effects of those were due to them cleaving something else off target.
Interesting. Interesting. Okay. Okay. So just so I understand, and I am a little bit fuzzy on, or I have not studied BACE inhibitors, let me sort of preventing the cleavage to prevent the fragments from forming. Is that right?
Some of the fragments, but not a.
Some of the fragments from forming. Yep. Yep. Okay. And you, your kind of silencing APP would just be preventing the production of the thing that gets cleaved to begin with.
Yes. Well, and, and not just the stuff that's being cleaved, but also the other end of it. So we get both.
The other end of it.
Yeah.
Yes. Yes. Yeah. Yeah. Okay. So that makes sense, as you said, kind of even further upstream. Got it. Okay. And then, you know, I guess what's different about the Alnylam APP approach versus maybe other silencing or ASO approaches, for this disease?
Yeah. So, there aren't any other that I know, either antisense oligos or analyzed the APP. I'm sure some will come, after we've been able to, you know, sort of show proof of concept. You know, the antisense oligos, you know, have been tremendous for the field in terms of if you think about some of the diseases that they've been able to, to treat, you know, Spinraza's been a good drug. I think one of the things of that class, however, is they're full of these things called phosphorothioates.
And those modifications, depending on the dose, can be fairly inflammatory. And so you see, you know, white blood cells go up, which are the immune cells in the compartment. When you look in the CSF, you know, in the fluid of the spine, you can start to pick these up. You see proteins go up and a few other things. And so to date, we've not seen that. And so, and that sort of reflects similar things that you see in the liver, right, where, you know, especially the early days of the antisense oligos before GalNAc, they had pretty, you know, interesting, inflammatory markers go up in the systemic circulation versus RNAi that's been silent.
And so I think, you know, they are different. They use completely different mechanisms. So RNAi is a naturally occurring mechanism. Like I said, it's AGO2 happening all the time. We take advantage of it. The antisense oligos actually use RNase H. So they co-opt an enzyme that's has a different purpose, right? It's not its normal function to do this. And so, you know, there's some differences there. One of them's double-stranded. Ours is double-stranded. The other one is single-stranded. So I think those are some of the key differences, but, you know, whatever can help patients, I hope they're both wildly successful.
Definitely. Definitely. Okay. Perfect. That's helpful. All right. So we, we kind of have talked about figuring out delivery. We've talked about APP itself, which kind of brings us to ALN-APP. What is the target product profile of this as you all set out to, to develop this program?
Yeah. So, I mean, I think what we're looking at is to try and lower, you know, APP, you know, and A beta 40 and 42. And we won't be able to measure the intracellular domain, but we do have all of these biomarkers that we can measure the beta fragment, the alpha fragment in the CSF to know that we're lowering it significantly. And so what we're gonna do is we're, you know, we're in the middle of doing single ascending dose, to go up and see how far we can lower it. So far, so good.
We've been able to, you know, knock it down, you know, in the 75 mg, you know, has been quite successful. We've dose escalated to 100. And, you know, what we're gonna, what we're in early onset Alzheimer's patients. So we're, and we're gonna be looking at imaging. We're gonna be looking at all of these different aspects of biomarkers and, you know, it's a small trial. So trying to see some differences on imaging and cognition, we'll have to, we'll have to say it's gonna be very small numbers, but we're looking for some, looking for signs.
And mainly we're looking, it's, you know, it's a phase 1. It's safety and efficacy. So we've been delighted that, you know, on our first try, you know, in the CNS, we're seeing, you know, 80/90 at a very small dose, a 75 mg single dose that's lasting out to six months. So that's really about as, you know, good a profile as I would've hoped going in, you know, given this is the first generation and, and, and our first time in this space.
Got it. Sorry, muting myself 'cause there's some beeping in the background. Apologies if you can hear that. So, so that sounds good. So you, as you said, you're in a single ascending dose study. You mentioned this a little bit in terms of what you're looking.
We're actually now in a Part B multi-dose and, and.
True. True. True. True. Fair. Fair. Yes. Fair point. You have progressed, but go thinking about the single ascending dose study and kind of what you were looking for headed into that. And you touched on this a little bit, but the alpha fragment, the beta fragment, 42 versus 40. For somebody again, who's kind of newer to this space, like what are all of these different pieces and what do they tell you? Maybe alpha versus beta and 40 versus 42.
Right now I'm looking for them all to be lowered. I want 'em all to go down.
Okay. That's easy. That's easy.
My mechanism is to remove the protein from which they're all derived.
Right.
So I'm looking for everything to go down, and so that's really what we're, you know, I'd love everything to be down 80/80, 80/90, and see where that, you know, where that is. Now I, you know, it may be that this drug is gonna be effective, you know, at an 80/60, 80/70, but in general, you know, if you're thinking about, you know, turning off the faucet versus, you know, you know, mopping the floor, I, you know, you wanna, you wanna get down where it's, where it's turned off probably to a trickle.
Mm-hmm. Mm-hmm. Okay. Perfect. And then kind of going back to sort of the genetic validation of the target that you mentioned earlier, are there patients, like, can you go too far, I guess? Can you, if you turn the faucet all the way off, is that a problem here?
In the preclinical models and in our safety studies and primates, it doesn't appear to be. The human genetics isn't quite as clear there. There aren't any people because APP appears to be involved in, you know, in development early on. This is a case where there may not be, you know, homozygous individuals that you can identify. And so that, you know, has been one of the questions that we looked at very carefully in our preclinical safety models. And we were able to go to very high doses within our safety models and show over a long period of time it appears to be, it appears to be okay.
Got it. Got it. Okay. That, that's helpful. All right. So kind of going back to then what you did see though in terms of knockdown, after a single dose, and you alluded to this earlier, but you were seeing, kind of remind us, I'll let you talk about it, but, you know, significant % knockdown, at the different doses, for a certain period of time. And that all kind of met your expectations or at least checked the boxes as you, as you move forward into the next phases?
Yeah. So I, and we, you know, we had up to a 90% lowering at 70, you know, at 75 milligrams. Continued to dose escalate given the safety profile we were seeing at that dose. You know, and that continues to go on. And then we, you know, started out to do a multi-dose every six months to see what the profile of that is. You know, so that's ongoing. So it's very exciting. You know, and if you look at the duration of effect, again, after a single dose, we've got this nice rapid knockdown of, of all of the different biomarkers that we looked at.
You know, and really to date, you know, we all of the markers that we've looked at from a safety perspective, that's something called neurofilament light chain, which is a marker of how well neurons are doing, you know, white blood cells, that's a marker of inflammation, and a couple of these other biomarkers, they all look great. So, very, very pleased with what we're seeing so far and very excited that, you know, that this type of an approach could be helpful in this disease and also the disease of CAA.
Mm-hmm. Mm-hmm. Okay. That's helpful. And then you mentioned neurofilament light chain. So let's dive into it a little bit because it does, like we hear about it a lot. You mentioned it in the context of safety, but can you tell us a little bit about what that is? You mentioned it's kind of a measure of the health of neurons, but what do we learn from that? What do you learn from that, more importantly? And is it just safety or is there an efficacy?
Well, it depends on the disease, right? So, you know, neurofilament light chain is a little bit of a crude measure of neurons dying, right? And so if you think about a disease like ALS, where, you know, it's a very quick progressing disease, what you'll find is that patients can have a very highly elevated level of NfL. And when you're going into a disease like that, you may look for NfL levels to come down if you're halting the progression of that disease or having a positive effect.
For a disease like Alzheimer's that, that transitions over a long period of time, even in the early onset, they don't tend to have that, an elevated, that high and elevated, NfL level to begin with. That's not that many neurons that are dying off over time. There you're looking to make sure that your drug from a safety perspective, in all cases, doesn't make the NfL go up, you know, over a long period of time because that might be an indication that things aren't going the way that you want.
Gotcha. Okay. That makes sense. All right. And then moving over to the ongoing clinical trial and in particular related to some recent, or recent announcement related to the FDA lifting the clinical hold, allowing you to initiate in the U.S. at least, multiple dosing in the Part B. Can you remind us again for people who may not be familiar, kind of what caused that hold in the first place and how did you convince the FDA to move past it?
Yeah. So we, you know, we started out doing safety packages. And when you start out with a very brand new platform like we had, we'd never taken it into people before. So we didn't really know, you know, what dose was gonna be effective. And so we could do modeling from what you see in, you know, in animal models. And you model it out and you say, okay, well, what's the highest dose we think, you know, would be reasonable for us to have to go to based on our preclinical models?
And that dose, you know, when we modeled it was somewhere in the 1.2 to 2 gram level, right? And so we had to do a safety study that was able to cover that kind of an exposure in people. Now remember, we are now at 75 milligrams versus where we potentially predicted at grams. And so, you know, what happened in that study is we dosed and we didn't know how frequent 'cause we didn't know the duration. So we didn't know. We thought it might be once every six months, but it could have been at, you know, maybe it would've been once a month, right?
And so you have to design safety studies to cover that too. And so what happened at the top dose in this study is we dosed. We dosed the animals very frequently at very high doses when we had a safety finding. And the FDA had questions about that, whereas other regulators in other places like Canada and the Netherlands didn't have the same questions. So, you know, we had to just, you know, go back, generate a little bit more data to make them more comfortable.
That, that's not unusual, especially in the central nervous system and, and not unusual in drug discovery in general. Now they, you know, they've now allowed us to go to multi-dose, up to 180 milligrams. And you saw the data that we had at 75, you know, and 100. So we think, you know, in general, you know, for the early onset program, we won't have to go to the doses that they've capped us at. So it becomes really more of a, less of an issue.
Got it. Okay. That makes a lot of sense. So yes, you are in multi, multi-ascending dose as you said. So as you move there, what, what new are you looking for, I guess, as you move from the single ascending dose? You're looking for knockdown and kind of duration. What, what's the next question as you move to multiple doses?
Yeah. So we're looking at, you know, again, when you go to multiple dose, you're looking at safety and you're looking at safety over time. Then you're looking to really try and figure out if you're, as you think about designing a pivotal phase 3 trial, you know, or a bigger phase 2 trial, what dose or what 2 doses do you wanna take forward into those trials? So you're really looking to get enough data on both the safety and efficacy to choose those doses correctly. So we're getting more data on that. We'll get more biomarker data over time to see if any of the biomarkers that we're measuring are going in the right direction. That will give us a lot of insight into how to design those later stage trials.
Got it. Okay. That's helpful. And you mentioned you're doing some imaging work as well. And maybe kind of going back to something we didn't actually talk about, but the early onset Alzheimer's population and kind of what the baseline image of their brains looks like, and the potential time course of any changes there. I guess can you talk us through that and should there be an expectation that maybe you'll see something positive from this current multi-dose study?
It's hard to know because, going into the trial, they are imaging positive. So they have amyloid. But it is a small number of individuals, you know. And, you know, when we're trying to figure out by this mechanism of natural clearance, we don't really know what the rate of change will be. And so that's part of what we're trying to answer in this multi-dose and get a feeling for before we go into a larger population where you would then look for statistically significant changes.
That's fair. That's fair. Okay. So if you turn, you turn off the faucet, but the unknown is still like how, how big the hair clog is, how fast the, the existing, you know, puddle is draining. So that's okay. Okay. That makes sense. Understood. All right. That's really helpful. And then I guess the ongoing study is in the early onset Alzheimer's patients, as you mentioned. What are the next steps or plans in CAA?
Yeah. So CAA is very exciting. So I, you know, let me explain a little bit about CAA too around the genetics 'cause I think, so there are individuals, in particular, there's a group in the Netherlands who, they have mutations in APP. And those individuals actually have CAA. They get a very aggressive form of CAA where, you know, they'll get bleeds within their thirties or forties. It's almost 100% penetrance. If you have this mutation, you will get brain bleeds. And it's interesting on imaging, you can measure when somebody's had a brain bleed because it leaves behind like, it's almost like a little iron deposit.
And so you can see those. And so you can, those individuals are getting imaged all the time. Once they get past having four or five, you know that they're then going to progress towards a severe stroke fairly rapidly in that population. So again, it shows by human genetics that, you know, this protein is involved, you know, and causative of that disease. So, you know, when you look in the general Alzheimer's population, there's a large number of individuals who may not have a lot of plaque in their neurons and in their brain, but they have a lot of plaque within their blood vessels.
And it's this amyloid that's in this case mainly A beta 40, not A beta 42. But certainly, you know, it's coming off of that same precursor protein. And so in our preclinical models, as I said before, when we shut off the, you know, we shut off the faucet, we see clearance within those blood vessels fairly rapidly and they remodel towards normal blood vessels and they don't have bleeds. And so, you know, very excited to, you know, you know, you know, start that trial, and get into that patient population and really see what benefit we can have.
And those patients are also now not really eligible for the antibody therapies that have been approved because of, you know, some of the risks of those. So it's a very underserved population. And so we're, you know, quite excited about it. And, you know, ready to get started.
Mm-hmm. And to follow up on that point on the safety side, and you touched on this a little bit, but you know, why, why shouldn't we be worried about ARIA here? Is it just because of the natural clearing process is happening versus.
It's a different mechanism and it's not going in and binding and inflaming the plaque.
Mm-hmm. Gotcha. Gotcha. Okay. Which, yeah, I can imagine is particularly important in the, in the CAA patients, in particular, as you said. Okay. And so in terms of next steps, you are planning to, well, actually I should say because you mentioned some Alzheimer's patients have plaque in their blood vessels. Are there any, do you have any hints, I guess, of CAA, like early looks at CAA, I suppose, from your Alzheimer's patients, or do you expect to, based on the enrollment and the ongoing?
I don't know at the moment. I mean, I think as we get our imaging, you know, imaging is actually fairly labor intensive, but as we get the imaging, I would be surprised, you know, again, we have small numbers on our phase one.
Yeah.
Like, you know, given what we think is the prevalence, if one or two of them had some evidence of CAA, I wouldn't be surprised, but I think, you know, we don't know that yet. And, you know, here we'll be imaging upfront, to again, you know, look for individuals that have CAA. And also we'll be working in that a portion of those patients will, will be in the Netherlands.
Got it. Okay. That's helpful. All right. And then as you move into studies here, is there any reason or do you, are you targeting any different level of knockdown, or anything like that, in this form of the disease, I suppose?
Yeah. I think it'll be very similar.
Very similar. Okay. So the dosing work that's happening on the Alzheimer's side pretty reads through directly to CAA.
It should help us. Yes.
Okay. Excellent. Excellent. Okay. Really interesting stuff, I guess, you know, as again, having solved delivery presumably and kind of starting to get some preclinical, sorry, clinical data, from the Alzheimer's side, as you said, how much, in your mind does that de-risk the rest of CNS? So is it like, all right, we've, we, as we talked about, we've, you know, figured out C16, we now have shown it works, in, in Alzheimer's. So now we're just off to the races in CNS. Or are there any kind of new technical or platform challenges as you move from target to target?
Yeah. For a lot of the targets, I think, you know, if you de-risk the platform, you de-risk the platform, right? And I think that's exciting because that means that, you know, every target behind it will learn from the one in front of it, similar to how we, you know, have had a platform in the liver and, you know, have learned along the way and applied those learnings. I think, you know, it's early days in the CNS for us, but I think we're excited about where we are and we do have other programs coming along in Huntington's and with our partners at Regeneron on SOD1 and ALS.
And so I, you know, we are building a central nervous system pipeline with, you know, genetically validated targets that we're confident in and, you know, and so far, so good with the platform. So I think all of that, you know, if I had to imagine a few years ago, 'cause we didn't, we started this endeavor not that many years ago that we would be able to go in with a single injection, you know, into the spine and have, you know, 90% knockdown at a dose of, you know, 75 mg, single dose. I would've been pretty happy with that and use that as a basis to build the foundation for, you know, for CNS, a CNS platform.
Mm-hmm. Mm-hmm. Okay. That's helpful. And you've talked about two new INDs by 2025, I believe. And as you just said, you kind of highlighted SOD1, ALS as well as Huntington's as being IND enabling. So are those the two we should be thinking about? Or are there others?
There are two and there are a host of others behind those, you know, and the timing of those we'll see. But, you know, it is a very similar type of chemistry and a very similar type of platform. So that's one of the benefits of having a platform is that the iteration time of moving from one to the next to the next is quite short. And so now, you know, the art and the science of it is obviously to let the clinical data and the first couple of programs emerge in time to make, you know, adjustments if necessary on all of the others.
Right now, we're, you know, very happy with where we are on the safety and efficacy side and, really driving forward to build the central nervous system portfolio of drugs that we hope will really change the medical landscape of these central nervous system diseases that really have tremendous unmet need and not a lot of therapies.
Mm-hmm. Mm-hmm. That makes a lot of sense. And just to be clear for the SOD1 and HTT programs, are both of those kind of plug and play in the sense that they are also C16, or have you talked about that?
We haven't talked about it, but they are the same platform.
Okay. Okay. Well, all right. Just going back to something you alluded to earlier, all of these are kind of direct to the CNS dosing, but you talked about looking at or kind of continuing to work towards systemic dosing to target CNS. You talked about kind of antibody conjugates in that regard. Have you guys laid out timelines or I guess how much of focus is the systemic dosing to reach the CNS for you all?
Yeah. So we're working on that ourselves and also mainly with our, you know, with our colleagues at Regeneron who are, you know, the best antibody experts in the world. So who better to have a partner when you're trying to make an antibody to get across the blood-brain barrier? So we're very confident that we'll have a solution to that. And, you know, that will be, you know, the next generation of these molecules that come through. And, you know, what'll be interesting about it is that there's only some aspects you can change out the delivery of it.
But, you know, you've learned a lot about that sequence and the SI, the SI side of it could stay the same. So you'd imagine that it's a, you know, sort of a life cycle, you know, innovation on it. And just gotta make sure that, you know, that the dose is low enough that you're not having to do consecutive high-dose IVs. You know, because then that becomes, you know, if I think about a single intrathecal dose once every year versus a bunch of IVs, you know, we'll see how that shakes out over time. So we're working very hard to bring the dose levels down and define the right delivery solution to get us across the BBB.
That makes a lot of sense. Okay. Perfect. And maybe just a bonus question at the end, you know, thinking about other tissue targets. And you sort of highlighted some of this at your R&D day as well, but, CNS is just one additional tissue target and you're working towards some others. So can you remind us where else are you focused for the, in the nearer term? I can imagine you're probably looking everywhere, but, for the nearer term and, kind of how are you thinking about accessing those from a technology standpoint?
Sure. You know, when I started out to come to Alnylam, you know, I left a small molecule company and people over there told me, "You're crazy. It's too big." I was like, "Well, it's an engineering problem. I love engineering problems." And so every tissue is an engineering problem, to be solved. And that's really how do you get it into that tissue. Beauty of RNAi. You know, I've talked about a cup of coffee. Well, if anybody went for a run, guess what? Your microRNAs went up and down in your muscles.
And so the system behaves in every organ that we've tested it in so far. So it's really about how do you get delivery into that organ. And so we're working very hard across different tissues in the body where we think, you know, we have really, you know, high-value targets that will help patients, right? And so that's how we look at the lens of where do you go first, second, and third. You know, we have ongoing efforts in muscle and heart and a bunch of other tissues.
Very interesting stuff. Perfect. All right. Well, this has been really interesting. I learned a lot. I think we, as I said at the beginning, you know, we're very excited about the CNS, and the additional tissue types, as you mentioned, as kind of the next wave of where this platform could go. Let me know, we are also excited about HELIOS- B. And so we look forward to seeing those results in due course. But, I think, you know, the minute that news is behind us, you know, we'll all be talking more about what's next.
And so we really appreciate you taking the time to walk through this side of the platform with us. And thank you all for joining us as well. We'll be talking to you all soon in our next installment of this series, tomorrow. So thank you again, Kevin.
Thank you for inviting me.