Session with Sana Biotechnology. My name is Alec Stranahan. I cover SMid Biotech at Bank of America, I'm also the analyst covering Sana. Pleased to be joined today by Steve Harr, President and Chief Executive Officer of Sana. Thanks for being here, Steve.
Thank you for having us.
Yeah.
I appreciate it.
Looking forward to the conversation.
It's a pretty, well, it's actually a dry hot day in Vegas, I guess, right?
Exactly. I guess maybe to start, Steve, you know, you've, I guess, significantly tightened Sana's focus over the past year. How would you sort of describe the company's identity today? Is it primarily a Type 1 diabetes company? Is it an in vivo CAR-T company, or is there a common thread, maybe underlying what you're going for?
Well, as you know, we'll make forward-looking statements so people can take a look at our 10-Q, which was filed last night actually for some really up-to-date risk factors. Again, thank you for having us. I guess what I would say is it's no different than when we started the company, and our goal is to engineer cells, right? There are two different ways that you can engineer cells. One is you do it outside the body, and your goal in that scenario generally is to replace cells that are either missing or damaged, right, and transplant them in and hopefully can replace them.
The second is we can engineer them in vivo or inside the person, and there the goal is to kind of repair a damaged cell or to change the signaling so it can have a different function. We continue to do both of those. You know, as all or many novel biology things are, they prove to be very challenging, and it's taken us some time to get to where we are. To your point, I do think we have a clear focus right now. I would say for good or for bad, and as an investor that might be for good, as an operator it might be for bad, these are very, very uncorrelated risks, right? Within Type 1 diabetes, you know, this is a really big market.
I think it's sometimes easy to forget or underestimate the problem and scale of Type 1 diabetes. To give you a sense of the unmet need, I actually was looking this up earlier. I have a 22-year-old daughter, and if your 22-year-old daughter could be diagnosed with breast cancer, HIV, or Type 1 diabetes, the shortest life expectancy is actually Type 1 diabetes, right?
Of those, obviously, the day-to-day management of that in terms of, like, every meal, every activity you do, every time you get sick, am I going to dinner with Brian, who sometimes shows up late, Nikki, who's a slow eater, how do I have to modify what I actually, you know, how much insulin I take, those things are in their decision-making every day.
The second is it's 10 million people, and people often ask us about competition, and we may go there, I don't know.
I always just say I don't worry about it. That's not being arrogant. Let's just assume, like, the greatest thing possible happens, and that is somehow this works, and it works perfectly. It works one treatment, and a person never has to take another therapy. It works 100% of the time, and we scale it, and we're curing 100,000 people a year of Type 1 diabetes. We'll take the global growth rate from 5%- 4%. If we just launch this in the U.S., we take the U.S. growth rate from 4% to a - 1%, right? It's a large enough market that you have to assume that others will play around.
There'll be other ways to solve this problem. I think the more successful all of us are, the better it is. The in vivo CAR-T is a totally different risk. There's a much more vibrant and dynamic competitive environment we have to go and deal with. You know, that's something where, you know, speed, breadth of clinical development, and our overall profile is gonna be really important in figuring out where do we fit in as, but hopefully the best answer for patients. I'll pause there for my introduction. You know, that's a little bit what we're up to.
No, that's great. Maybe we can start with Type 1 diabetes. We saw really kind of groundbreaking proof of concept. Now you've got follow-up in that patient out to month 14. I guess, what would it take, or is this already happening in terms of number of patients, duration of follow-up, to really have full conviction in the program and, before, you know, really scaling manufacturing heavily?
Yeah. I'd separate those two. So I'm gonna take a step back. Type 1 diabetes, we know what its problem is, right? It's the immune system comes in, and it kills the pancreatic beta cell. The pancreatic beta cell in the patient is the only cell in the body that makes insulin. Up until 100 years ago, that was a death sentence, right? You couldn't get sugar from the bloodstream into the patient's cells, so they'd starve to death, ironically, right, even though their sugars were sky high. In 1923, there was the advent of exogenous insulin. People have done okay. They've done pretty well, right? Not great.
About 25 years ago, a scientist in Canada named James Shapiro discovered that you could take pancreases from someone who just died, isolate the islet. I'm gonna go back and forth, so I'll pause here for a second. Pancreatic beta cells are the cells that make insulin. Think of an islet as the beta cell in a support structure. It's the easiest way to think about it.
He'd isolate islets and transplant them into patients, he found that if they got enough islets, they could be insulin-free for a long, long, long time and do very well. They had to be on lifelong immunosuppression like any organ transplant, that's not good. There aren't that many people for whom lifelong insulin is worse than lifelong immunosuppression,
Getting cells from a cadaver is neither scalable nor replicable, right? It's very variable in quality. That's huge proof of concept. That's step one. Step two, over the last few years, we've seen several parties take stem cells, grow them, and then differentiate them into islets, right, and transplant them. Now you have a much more replicable supply source, and it's almost certainly meaningfully more scalable, right? You still have the problem of immunosuppression.
What this study did, that you mentioned, is it was the first example that I'm aware of where we gene-modified cells it was a recently deceased donor, right? We took his pancreas, isolated and gene-modified them, and transplanted them into a person who's had Type 1 diabetes since 1987.
This person is now, for the last 14 months, been making insulin for the first time in over 40 years, and he's doing it with no immunosuppression. We now know that three things, right? Long-term transplants cure patients. Second thing, you can make them from stem cells. Third thing, if you put the right gene edits in them, you can no longer transplant without the need for immunosuppression. Now I would argue a cure is inevitable.
Like, someone has to take and put the whole thing together, and that's what we're doing with SC451, our drug. Hopefully we'll know the answer to that within a year. Our goal is to start the study this year and figure things out pretty quickly. I would argue that a cure is inevitable. Just someone has to put all that together. To your question, what do we need to know for manufacturing, I would think about manufacturing as 3 phases, For us one is good enough for phase I. Like, we're in the midst of making this stuff, right, the tech transfer into a CMO.
It's good enough for phase I, but not much more than that, just to be clear. The second is good enough for a really nice commercial launch, right? I think of that as thousands and thousands of people per year.
We have work to do on that, it's not a investment number. I'll come back to that. The third is, you know, tens and tens of thousands of people per year, what we talked about earlier, that's gonna take us some time to get to. That middle one we're already investing in. Again, I'm gonna divide this into two problems, cells per run, number of runs. Right? That's how many cells you get a year.
Cells per run is a science problem. Number of runs is a capital problem, right? Right now we're on the science problem, we are going at that full steam. We didn't start doing that though until we knew we had the phase I process done, right now we're going full steam at that problem.
I'm more optimistic than I was three to six months ago that we'll get through that, and ultimately it'll be a capital problem. First we have to make some science advances. That's how I think about that, in terms of answering your question there.
No, that's helpful. I guess in terms of the IND filing that you're working on for SC451, is the last gating steps just sort of the GLP toxicology , or is it the tech transfer to the CMO that you mentioned? I guess, you know, how close are those two to completion? You know, what are sort of the best estimates for when first patient dosing happens?
Well, I hope they're pretty close, right? They're, you know, which one ends up being a rate limiter is you never really know until they're done. I would bet you it's probably getting manufacturing all buttoned up. It's a complicated drug to make. I don't wanna, like, kind of sugarcoat that.
Our phase I process is a phase I process. It's not a, it's not a commercial process. There are a lot of things we still need to automate, and scale, and clean up. I think it will be good enough. You know, we're in the middle of that tech transfer. You know, things could always go a little better than we planned. That rarely happens. Things could always take a little bit longer than we planned.
I think we have some buffer built in our timelines. You know, you know, that's probably gonna take us the longest amount of time. We're also finishing up the non-clinical testing, right, which is a whole host of things related to GLP toxicology, efficacy, genomic stability, a whole host of things.
Again, I think, you know, those are getting pretty close to being wrapped up. They're not done. Until they're wrapped up, something could always surprise you, right? Could end up being the long pole in the tent. For right now, we seem to be on pace with both of them to kind of meet our goal. What we've said is we will, you know, both, you know, If things go as we hope they will, we will both, you know, clear our IND this year and get this study going.
Yeah.
You know, exactly when we'll have data will lead to another time to figure out.
Yeah. I think you've noted, you know, that proof of concept could come pretty quickly, maybe within, like, weeks of dosing, you know, whether the cells engraft, whether they evade rejection, produce insulin, et cetera. I guess, what are sort of the data points you hope to gain initially.
Yeah
To know that, you know, the new drug product that you've made is doing what you hoped.
Yeah
In replicating the first one?
I mean, just approach this first of all like from the most important thing in a first-in-human study. Like, this is CRISPR gene-edited stem cell-derived islets, right? It's a combination of gene editing, stem cell biology, immunology. You know, it's a novel way of delivering these things. The first thing is safety we need to get through. I know that's not what you're talking about.
Once we have safety, you know, we're gonna transplant these cells with no immunosuppression. We're transplanting a cell the patient already has a known immune response to, right? Already has killed all of their own beta cells, and we're transplanting an allogeneic cell, meaning it's coming from someone else. It should be gone within days, right?
If it's not, and it's there, you know, just like with the previous proof of concept, we said if it's there in one month, it's going to be there in one year, right? I think if it's there in 1 month, we're going to feel really good that in this new way of manufacturing this, we've overcome transplant, allogeneic and autoimmune rejection. The next thing is it was a really low dose that we transplanted, right? We don't want to just see a really low dose of.
Take a step back. When your beta cell makes insulin, it actually makes something called proinsulin. Then when it's secreted from the cell, that's cleaved into C-peptide and insulin. The amount of C-peptide in your blood is a direct measurement of how much insulin the patient's making, right?
We want to see that the C-peptide at one month is very robust, right? It's on its way much higher than what it was, and that gives us a sense this is likely going to be something that works. That's step one. That can happen very quickly. Step two is we're actually not trying to overcome allogeneic and autoimmune rejection, right? We're trying to make a drug product where a patient will be able to come off insulin, have normal blood glucose, and never be on immunosuppression, right?
We want to see that, and that likely takes a quarter or two, right? If you look at that usually takes a while to kind of get these cells to really kind of function really well afterwards. Let's say there's the first step, which is can you transplant them successfully?
Second is do you get people off insulin? The third is how replicable is that, right? Let's just say we're five out of five or six out of six, you're gonna feel really pretty good about it, right?
Let's say we're three out of six. You're probably gonna say, "I wanna see some more." Right? Exactly how long that takes we'll have to see, but again, those are the types of things I think we'll figure out next year.
As we move through the year. I'd expect pretty early we'll figure out, hey, do these cells, you know, overcome immune rejection and function? Maybe as we move through the middle of the year, this time of the year next year, we start to understand are we gonna get people off insulin, right?
Do we have the right dose, all that stuff. The latter part will be later in the year most likely.
Okay. When it comes to SC451 you've got the things that the company can control, right, on the manufacturing and the lot to lot, reproducibility, and then you've got, you know, the clinical handling at the hospital, right? How does the Mayo partnership that you signed recently sort of establish.
Yeah
A good foundation for that?
That's a super important question. Like, one of the things that concerns us is what happens from the time the drug product leaves our hands to when the patient goes home, right? There's so much that has to happen in that period. These are live cells.
Right? They have a very short window that they are actually gonna live. They have to be taken from their shipping container and prepared for transplant. They then have to actually be transplanted with a procedure that is replicable across many surgeons, across many sites.
Over time, right? You have to standardize how you take care of those patients so that afterwards, you know, we, you know, we can be confident that they will safely go home and hopefully function quite well. That's really to start with. You know, I hope we get a lot out of this collaboration. They've been wonderful so far. We're only a few weeks in, but I actually have to say it might be the honeymoon phase, but the first few weeks are better than I hoped. Right?
We're just learning a lot about that portion of it. How do you create, ensure that we have something that is standardizable, that is safe, that will deliver this product in a predictable way to patients? That's what it's for, and so far so good.
Okay.
They're really good at that stuff.
Yeah.
Right?
Yeah, no, that makes a lot of sense. I guess, you know, you alluded to questions that you get around the competitive landscape. I agree, like it's such a large TAM, it's kind of a moot point, but, you know, Vertex, I think CRISPR has had something in the works for a little while anyway. I guess how do you sort of see fast followers given that you've now kind of proven the mechanism?
Well, I think that we can't claim they're fast followers until our actual drug really works. Right? Let's, we'll first get there. You know, I would like to be first in what we do. I think there's some real value in that. I also think there's a lot of value from learning from the field.
There's no doubt, you know, we've learned from the field. I'll give you an example is one of the things that Vertex saw early in their trials is stem cells sometimes don't engraft perfectly. They die and they release insulin granules, and some people ended up with, you know, low blood sugar.
Super easy to treat. You just give them sugar, right? Now we know that that's one of those things you have to monitor from, and I hope that, you know, they can learn from us some things that we do and learn as we progress as well. You know, our goal here is to make progress for the field, and I'm sure that if our stuff works, I'm sure we'll do fine. I'm very confident there will be competitors.
Yeah.
Right?
There's a lot of know-how when it comes to actually making the thing.
There's a ton of know-how. Yeah.
You're actually building that out from scratch.
Well, there's a lot. Like, Yes. It took us years to make, to actually define this problem, and that is these stem cells are a little bit genomically unstable. When you gene edit them, they become even more unstable, and you end up selecting for, if you're not very, very careful, mutations that kind of select for cells that grow quickly.
That's called cancer, right? Yeah, that's a know-how it took us to get around. Defining the problem though, I think others now can run more rapidly behind us and say, "Okay, we have to go after that challenge really early." They know it's there, right? We're pretty transparent about what it takes.
You know, we have to be because we're pretty small. You know, if the things had gone perfectly, we would've treated the first patient a while ago.
Right? We learned, right? It took us some time to make that the science really work.
Yeah. Yeah. Just for the sake of time, I wanna talk about the in vivo CAR- T platform. This is really the emerging part of the Fusogen platform that you guys have built the company off of. Maybe we can talk about SG293. I don't know if you wanna give a quick sort of intro on that, but whether it's the B-cell depletion you're seeing in monkeys or anything else that you're seeing coming out of that program and sort of what you hope to replicate in people.
Let me start with there's this in vivo CAR- T space, and there are two broad sets of technologies, and then within, one that we're in, they're like cousins, right? There are two very, very essential assumptions we made at the outset of this, right?
That is if you're gonna try to make the idea of these in vivo CAR T cells is you're gonna deliver some type of genetic material to a T cell, and they're gonna make it into a CAR T cell that can go and attack some target cell, whether that's a cancer cell or a B cell or whatever you want. We made two critical assumptions. One is that cell specificity and delivery really matters. You only wanna go to the T cell.
There's an alternative viewpoint, which is, you just need to get in enough T cells to have efficacy, right? Don't worry about the off-target stuff. They'll take care of themselves. The second is we thought, we feel like because you're going to make, I don't know, 100 million CAR T cells and you have tens of billions or hundreds of billions of cells you have to eliminate, you have to get the DNA to integrate into the T cell so that you can get what we see with CAR T cells.
There's a logarithmic expansion. They grow. Like, every time they see a target cell, they kill it and they divide. You go from 1 to 2 to 4 to 8, you know, you just keep dividing till you have many, many cells that will kill. Those are the two assumptions.
If we're wrong, other technologies will end up being faster and easier, to be very clear, right? We believe we're right, but we really believe cell specificity matters and you have to integrate. That's part one. That's part one of the competitive landscape. With what we've seen, I think that the big differences that we have versus others in this kinda like virus-like particle space is we're more specific, at least in preclinical settings.
I think we have a different way of entering the cell. Both of those should end up, if preclinical science is right, being safety advantages, right? It may prove that that's easy to see in a clinic, it may prove to be really hard in a clinic, it may prove that we have some other problem, right?
Until you dose the patient, you don't know. you know, what we see in the non-human primate, which is a really good model, right, of efficacy. What we're trying to do is we give them a single injection of our drug, and it makes a CAR T cell that will target B cells in the monkey. We see a dose-dependent complete elimination of detectable B cells, right? That's true. We, whether we look at peripheral B cells, lymph nodes, spleen, then you see this thing that you have seen with Georg Schett's data in the autoimmune setting where you have this B cell reset.
Meaning it's all naive cells that come back. It's kinda Control, Alt, Delete on that, on that, B cell repertoire.
That's something we haven't really seen from others, right? Where it's just clearly just naive cells coming back. We also seem to have a very good toxicity profile. It's very cell specific. You don't find this in the liver. Right? You just don't find that. Like I, you know, I challenge you to look at any other data and see that. You don't find it in gonadal tissue.
You don't find it in the heart. You don't find it in the lung. It is just in T cells, right? The second is, we, you know, there's been this kind of infusion reaction that many have seen in the field that's been pretty challenging. We don't seem to have that, at least in non-human primates. They had a little bit of a fever.
One dose of Tylenol was all the animal needed, did very well. We think we'll have a differentiated drug on safety, maybe on potency and efficacy because we have a better safety profile. You know, this is a novel category drugs, we need to get into humans and see what it looks like, you know, we'll start doing that this year. We're optimistic, we have to see what happens.
Okay. Obviously, this is a pretty hot space. We've seen large pharmas stepping in through M&A. I guess versus some others that are in the field, would you say it's really the specificity of the edit that's the driver of?
It depends. I mean, LNP mRNA, two things, right? One is integration, second is specificity of the cells, of the delivery, not the edit, the specificity of delivery. Like, those things are going to be in the liver. It's just mRNA. You, when the cell divides, mRNA won't go into the progeny, right? You only have a limit. You can redose it, but you have a limited number of cells it can kill. It's unlikely that's as potent.
Maybe good enough. I mean, I don't think we know, right? We need to see that. That hasn't really been tested in humans yet in a really robust way. The second is, though there've been a number of acquisitions in that space off and off of preclinical data, right? The second is you have these virus-like particles, there you integrate your signal into the target cell's DNA, right?
There the difference in what we have versus others have had human data when they've done these partnerships and acquisitions, we need to get that. I think that will help us understand what we have and, you know, from there we'll figure out what the right path forward is for us to develop this drug.
Okay. I guess in terms of gaining the go forward, obviously we'll see, you know, how the activity of SG293 looks in people. You recently, you know, nominated a BCMA-directed asset to SG227, that, you know, could enter clinical study as early as maybe middle of next year. Is that is pushing that asset forward sort of dependent on SG293 or are they separate?
Yes.
Yeah.
If it turned out that we deliver Our delivery vehicle is not safe, we're not gonna do two.
Okay.
If it turns out that our delivery vehicle does not work, we're not gonna do two. If it turns out that it works, we're ready to exploit that opportunity with taking forward this drug SG293, which targets CD19 in oncology. We're gonna take it forward in autoimmune diseases, we'll be ready to take forward a BCMA, you know, not long after that. It's really more, you know, ensuring that we're prepared. You know, getting prepared is not that expensive.
Actually executing is expensive. Both in terms of opportunity cost for patients, also capital for us. If it turns out that our stuff isn't safe or effective, we won't take it forward. It's the second drug, right? If it is, we'll be ready.
Okay. I guess, you know, the initial step is in oncology. Autoimmune you mentioned. Is that something I guess it depends on sort of the activity you're seeing. Would you wanna invest to push it forward just broadly across both of those verticals yourselves, or would you seek to partner? I guess which indications?
Yeah. When you look at Let's just take the broad category of B cell depletion. It's hugely competitive, right?
You have almost every large company's got several mechanisms. They've got pills, they've got antibodies, they've got antibody-drug conjugates, they've got T-cell engagers, they've got CAR T cells, they've got in vivo CAR T cells. They've got all these different ways to go about this. Therefore, you know, being really a little bit broader in our clinical development and getting rapidly finding the place where our technology is the best answer for the patient is really important.
It's likely gonna happen, you know, more rapidly and more broadly with a partner than it will alone, right? Particularly when we think, assuming success, that this, Type 1 diabetes is kind of a generational opportunity. Would we partner that? I think that, you know, in most scenarios if we can find a good partner, it will be partnered.
It will end up being that the pie is so much larger with a partner that you can divide some of the economics, right? It's when you don't grow the pie that it's hard to partner. In some partnerships you shrink the pie, right? Because you just make decision-making so complicated. I think that's when the pie grows.
It seems like the CAR T assets broadly will be things that over time, again, like we can't control when we get to the right arrangement, but over time we'll be better off, you know, in partnership than trying to do them ourselves. Whereas Type 1 diabetes, I don't know the answer to that. I think of like it's very simple. Does it work? Like drugs that we made, kinda the cat's out of the bag, right?
Can you scale it? If it works, can you scale it? It's a totally different technology. Unclear others can help us. If you can scale it, can you commercialize a curative therapy in a truly broad market? Again, something that's gonna take some real novel creativity, right? The fourth is how do you pay for all that? Very clearly pharma can help us with the latter. We have to think through the first three and if we feel like it's enough of it and they help with number four, we may end up with a partnership. If not, I think it would be really valuable to hold onto for ourselves for a while.
Yeah, yeah. Kind of champagne problems once you see the activity.
Yeah.
Yeah.
First you gotta say, "Does it work?
Yeah. Exactly. All right. Well, with that, I think we'll leave it there since we're out of time. Steve, thank you so much for the great conversation, and thanks everyone for attending. Thank you.
Yeah, thanks everybody for their time and attention, and thank you Alec Stranahan.
Thank you.