All right, I guess we're going to get started. Welcome to Leerink Global Healthcare Conference 2025. This morning we are discussing with the Editas Management Team, and we have Erick Lucera and we have Gilmore O'Neill with us. Thank you again for joining us for this conversation today. A lot of exciting things in the making for Editas. Obviously, maybe we can start with the transition, right? The company has been transitioning in kind of focusing on the gene editing, but in the in vivo setting. I guess the first question would be, what are the type of indication for which you think editing can be a potential advantage over other genetic medicine per se, more traditional gene therapy or even RNA approaches?
That's a really super question because it really is at the core of our strategy to make sure that Editas chooses targets that are clearly differentiated. If you look at editing versus traditional sort of AV delivered type transgene delivery, we're really interested in going after diseases where durable effects are required. That actually is really critical in tissues where there's any kind of tissue turnover where you're going to get dilution because an edit makes a permanent change in the genome, which will be copied with every cell division and expressed in every daughter cell, unlike an AAV, for example, where you get a dilution of the effect. With regard to other types of therapies like siRNA, ASO, RNA editing, our key focus is on ensuring that we now CRISPR or use CRISPR to do things that others cannot, that those cannot do.
One approach that we're really focusing on right now is going after or targeting non-coding DNA, which actually controls the expression of a gene and essentially allows us to dial up the volume of a protein that actually is mitigating or is disease mitigating. This is something that really in the main, those other modalities cannot do or rarely could do.
All right. How should we think about specificity, specifically in the context of trying to dial up those genes by targeting non-coding elements?
I think we actually should be, obviously with the appropriate humility before nature, we should actually feel very confident about that because we actually have generated significant experience. Indeed, we have actually been in humans with precisely this strategy. Yes, we were using an ex vivo strategy with our reni-cel asset, but we learned a lot about it. We can be very confident about the specificity of the targeting of that editing. As I say, we had a super experience with reni-cel from that point of view.
Actually talking about reni-cel, before we dive a little more into what's coming in the in vivo pipeline, looking back a little bit with reni-cel, obviously at first, you know, you had some exciting data in the in vivo pipeline, kind of leading to the company trying to focus more on the in vivo in the third, fourth quarter last year. You set out to find a partner for this particular program. Toward the end of the year, the program was terminated. Can you tell us a little bit more about the journey that it was to kind of try and look for a partner for the program?
Yes.
Maybe what were the challenges there?
I might preface it a little bit of the journey of the company in that when two years ago, we announced that we were actually going to really focus our attentions and really drive towards being a leader in in vivo editing. Notwithstanding that, we had a very potent asset we believed in reni-cel. The end of last year, we had a convergence of two points. As you said quite correctly, we had some very exciting data for in vivo editing, both for an undisclosed target, liver target, as well as for in vivo editing of hematopoietic stem cells. At the same time, we had run this process. I think what we learned was in that process, as we were looking for a partner, that a lot of the target companies were very intrigued by the data.
They actually were very excited about the potency of the data with reni-cel and really wanted to see it in in vivo. I think that sort of the key takeaway was that they see and they saw, as we do, a significant opportunity to treat sickle cell and beta thalassemia. They actually think there is a, not surprisingly, these are highly prevalent diseases, and they believe there is a very robust market. However, they think that in vivo is the right approach, and that's what we are pursuing.
Great. Obviously the work you've done there, there's been a lot of both investment in terms of R&D, in terms of capital in that program. If you've seen that you're switching into in vivo, you're not starting from scratch, right? You've been working on that in vivo pipeline for a while now. What are some of the learnings from that reni-cel program that you're taking with you into this transition to in vivo?
There are a number of learnings. The first is that our editing strategy that is focusing on functionally dialing up the expression of a disease mitigating protein is a very potent therapeutic strategy. Second, we really are very confident about the particular target in the HBG1/2 promoters that we are targeting. Indeed, we're using that guide as we go forward in our in vivo program. That is a very nice piece of de-risking. We've actually used Cas12a, which is a proprietary enzyme that we actually developed at Editas, and that has been robustly validated now in humans. That actually also is another significant de-risking event. Finally, we know a lot about the disease space, both in sickle cell disease and beta thalassemia. Those are all elements which combined together will help us drive the in vivo programs.
I guess thinking more now on the capital investment side of things, how should we think about the winding down of the ex vivo program? How should we think about kind of capital investment in the infrastructure to continue to support the in vivo programs?
Yeah, I'd say with respect to the wind down, I think when we filed our Q and our K, we estimated $60 million that would go into the second quarter. We expect that that should be basically done by then. With respect to in vivo, unlike us having clean rooms with the autologous program, we're just going to do pure outsource model for that.
Okay. Thank you. I guess, as I mentioned, the transition was kind of prompted, I mean, you've set to be the leader in in vivo editing for a couple of years now, but the transition was prompted by some in vivo data. Before we dive into that, can you tell us a little more about your LNP platform and how do you see it being differentiated versus competitors?
Yeah. As we look at, first of all, one of the important things for in vivo is to have that LNP delivery technology under your roof. When it comes to a targeting LNP, we've actually made significant progress in developing our own targeting LNP, which comprises a unique combination of lipids that detarget the liver. Because we actually want to significantly reduce where we want to target tissues other than the liver, like the hematopoietic stem cell, we want to significantly reduce or eliminate the exposure to the liver, which is a source of toxicity with LNPs. The second thing we want to do is significantly enrich the targeting with specific cell type. We've done that by essentially developing a method for conjugating a targeting ligand.
Basically a molecule, it can be a peptide or something else that can be tied to or linked to the LNP or lipid nanoparticle that will then actually deliver it to a specific cell, and in this case, the hematopoietic stem cell. From a point of view of generalizability, we've talked in the past about plug and play for the genetic targeting. You change a few nucleotides on a guide RNA and you can change the gene that the editing mechanism targets. We in the same way can change the targeting ligand that we bind to the LNP in a plug 'n play method and then target a different tissue or different cell type beyond the hematopoietic stem cell.
Specifically to that, you had presented late last year some preclinical data relating to your optimized tLNP. Can you maybe give us an overview of the data and its significance?
Yes. I think the first thing that, or the key takeaway is that we are actually, in those days we presented, we were actually already approaching a threshold that is going to be clinically meaningful for editing in HBG or HBG1/2 in hematopoietic stem cells. What we essentially have shown is the transition as we've moved from and evolved our LNPs, so-called LNP1, 2, and 3. When we had our second key iteration LNP where we had actually done some tweaking of the lipid nanoparticle chemistry and put on a targeting, a novel targeting ligand to go to HSCs, we saw already in mice a 10% editing in HBG1/2. We were so excited about that that we actually took that into monkey. I'll return to that in a second.
With our LNP3, where we had further optimized and significantly detargeted the liver, so-called LNP3, we actually were achieving 30% editing of HBG1/2, which is nicely above a threshold. We think the threshold is about 25% editing required. That is moving into monkeys. Indeed, when we took LNP2 into monkeys, the data we shared in January on that was that that 10% already translated in monkeys or non-human primates into a 17% editing. That was just at seven days follow-up. The nice thing about non-human primates is that you can continue to follow them after each assay, unlike poor mice. We are really looking forward to sharing more of those data in the future because we are very excited about the data that continue to generate both for LNP2, but actually also for LNP3, which we believe is threefold more potent than LNP2.
To that effect, when should we expect additional data for LNP2, so second generation in monkeys, so longer follow-up? When should we expect initial monkey data for LNP3?
Yeah. What we've guided to is that we are actually looking to, we're targeting getting to two DCs, our drug candidate selections, one for in vivo HSC and the other for a liver target. We are planning to do that in the middle of the year. In the middle of the year, we plan to share more data. Obviously, we will be disclosing more data at scientific meetings going through the year.
You mentioned obviously that we will see more data throughout the year. Are there any tissues that you've seen the platform being applied to that are easier to target than others? We've talked about the targeting of the liver, but in terms of the other tissue that you're going after, are there some that are easier to target than others?
I can step back for a second and say that in addition to our own proprietary targeted LNP, we actually have a wonderful collaboration with Genevant, who have a liver targeting LNP. Obviously, the liver is very easy, well, very easy. That is standing on the shoulders of 30 years of research. Today, it is a relatively easy tissue to target. Indeed, we continue to see really exciting data on in vivo editing coming out, not just from us preclinically, but others clinically in the field. This is all wonderful for us all and for the patients that we look forward to treating. As I say, the liver is a relatively easy one. That is why we have a program or a lead program that we hope to DC in the middle of the year.
Now, we haven't shared the target yet, but we look forward to sharing that very soon. The key thing again is it's differentiated. Going back to your original question about how are we using CRISPR to differentiate from other technologies. Again, this is about potent, high efficiency dialing up of the dose of the disease mitigating protein. We did actually present some what I would sort of anonymized data earlier this year for that liver target, where we again showed very high levels of editing. We basically had nearly maxed out editing in the liver at around 70%, where hepatocytes represent about 70% of the liver cells. We actually saw again a fourfold increase in the target of interest with substantial, like a 60% reduction in a critical biomarker, which is actually meaningful in human disease. Overall, we're very excited about that.
It's a nice example of how we are going after an additional tissue to metabolic stem cells. Apropos targeting and the plug n' play, in many ways, changing the ligand is going to be the key thing. Identifying the ligand for the cell that you want is going to be a critical element for those targeting LNPs as we move beyond HSCs.
You mentioned partnerships. If you see those partnerships kind of based on the value that you bring with your LNP platform, can you tell us a little more about the IP portfolio that surrounds the platform?
Sure. We actually have built a robust IP portfolio around both our targeting LNP. We're building that. Obviously, around our editing technology, indeed, we have foundational IP that is relevant not just to us, but to others in the space as they move their programs forward. Obviously, that latter part was emphasized, validated, and indeed valued by the agreement we made with Vertex just a year ago to enable the launch of CASGEVY. Since that time, we actually further monetized that deal with, you know, monetized the downstream payments with DRI.
Can you tell us, you mentioned the different portion of that IP portfolio. Can you tell us a little more in terms of your licensing monetization strategy, the existing collaboration, and where you see potential for growth?
Yeah. We are very fortunate to have the foundational Cas9, Cas12 license from Harvard, MIT, Broad. It's a traditional university royalty rate that we think that we can out-license to everyone that's pursuing a target in that area. As you know, those are sort of low single digit type royalties. We have the deal with Vertex on one hand, but we also did deals with Vor and Bristol Myers and several others. We are really looking to just create a bespoke agreement with any company that looks to use the technology to advance the field.
How should we think about existing collaborations? The cadence of potential development milestones in the short to midterm?
I would say with respect to some of the IP licenses, each one is different. Obviously, I think the most advanced one beyond the CASGEVY license is the deal we have with Bristol Myers. If you go back on their R&D day from a couple of years ago, there are several programs that they are progressing. We would expect incremental payments along the way. For some of the earlier deals, those are more back-end loaded based on the fact that they are just smaller companies. It really is a case-by-case basis with each one of them.
I guess kind of walking back to my original question, where do you see greatest potential for growth? What would be an ideal partner for where the pipeline or where the platform is at this stage?
I think when you think about partnering the pipeline of IP, it's really on a case-by-case basis. I think the Intellia assets are the ones closest to market. Those are the ones that are most interesting to us.
All right. Great. I guess, maybe just kind of zooming back on the corporate side of things. We’ve talked about the transition from ex vivo to in vivo. We talked about the winding down. How should we think about the cash runway as of now, what it covers, and kind of the next key catalyst for the company?
As we stated on the last time we reported earnings, we ended the year with cash of about $270 million, which gets our runway into the second quarter of 2027. Included in that runway are not only the two DCs that we expect in the middle of the year, as Gilmore mentioned, but also human proof of concept by the end of 2026. In sum, our cash runway allows us to get that first set of human data.
Can you talk a little more about how to think about OpEx moving forward? There's been investment made in the ex vivo side of things transitioning into in vivo. How should we think about OpEx?
Yeah, I would say it's a little bit muddied by the fact that we're going through the transition of the wind down of reni-cel. As I mentioned, we expect that to be concluded by the second quarter of this year, at which point you'll see a more normal level of OpEx. We haven't given specific quarterly guidance, but if you sort of look at where we're beginning with $270 million and getting into second quarter of 2027, you can look at the runway of OpEx for this quarter and say we do that for another quarter as we wind reni-cel down, and then just take the remaining cash and then divide it over the couple of quarters. That should get you close to what the run rate OpEx will be.
All right. I just want to check if we have any questions from the audience. Great. I guess this will be a good day to dive a little bit more into maybe the sickle cell disease space and where do you see an advantage of editing over other modality. Then within editing itself, how can in vivo be differentiated from all of the ex vivo approaches that we've seen?
Yeah. That is a great place to go. The truth is that by going to in vivo, you massively simplify the therapy. You significantly reduce the risks. Frankly, you reduce the burden on patients, their families, and healthcare systems. Those altogether come forward and actually create the ability for a therapy to be used across a much larger proportion of patients with sickle cell disease and with beta thalassemia. The reasons for that are that you do not have to, first of all, you eliminate busulfan. The conditioning is a substantial risk for patients. The second, and basically because of that, really forces patients with the most severe forms of refractory forms of the disease in the case of sickle cell and beta thalassemia, to really consider transplant. Most others do not, even though the diseases are still dreadful.
I think it's worth reminding everybody that where you don't have supportive care or the access to supportive care is much more limited, in sub-Saharan Africa, the mortality for sickle cell disease is of the order of 60%-80% by the age of five. 80% of babies born are most likely not to see their fifth birthday. It's absolutely diabolical disease. With significant supportive therapy, where it's accessible in the U.S. and other much richer countries, you can actually get that the median survive is around 50. It really is a terrible disease. Expanding beyond that most narrow sector to actually the vast majority of patients creates a huge opportunity within all the health systems. I think this is really where we see a huge opportunity.
You're not talking about 10,000 or 20,000 patients in a handful of countries, but you're talking about potentially reaching hundreds of thousands and millions of patients.
There are a few companies that are working on non-genotoxic conditioning for sickle cell disease specifically. How do you think, if successful, those approaches would change the market opportunity for in vivo editing?
I think in the end, what I left out as I was talking about the differentiation beyond just the toxicity of conditioning is the journey. We look at an in vivo therapy as a single infusion. Again, the simplicity and the burden of therapy, it's massively simplified. I think obviously pursuing non-toxic or less toxic conditioning is a wonderful approach. It still, however, requires patients to have their cells mobilized, collected, edited, and then go through what is obviously one hopes is a much simpler transplant process. They still have to go through that. There is a complexity and a burden for the patients, which in vivo could essentially bypass completely.
Now looking into circling back to what you've seen with LNP1, LNP2, LNP3 in terms of hematopoietic stem cell editing, where do you see, so are you confident with the level you've reached with LNP3 that it would translate to human? Would you want to continue the optimization before you go inhuman with this program? Where do you see the in vivo data translating?
We actually feel very confident about the threshold. We believe so. We're setting a threshold, a targeting threshold for editing about 25%, 20%-30%. And that's based on the allogeneic transplant experience, which has shown that once you've actually achieved that kind of level, and we're basically doing an equivalence of chimerism. Basically, post-transplant patients may have 30% of the cells are from the donor and 70% are their own cells still. Once you get to about that 30% or 25%-30%, you basically damp down or control the complications, the vaso-occlusive events, and the other complications of sickle cell disease based on that published experience. That is very good. As I say, we are feeling very good about the potency that we've seen to date and where it is. We're actually already in mice have exceeded that with LNP3.
It is important to emphasize that those mice are not just, there are not mouse hematopoietic stem cells. I should have said that. Forgive me. Those mice are engrafted with human stem cells. That is very compelling. As I say, we've already exceeded that threshold in the mice. We are looking forward to sharing more data in non-human primates in the future and expect and hope to see that.
I guess maybe one last question. When we think about, we've talked about the limitation in terms of non-genotoxic conditioning. We've talked about kind of the potential for in vivo to simplify the journey. Now that we're talking about in vivo, can you maybe contrast and compare the editing specifically approach versus a gene therapy approach?
I think this goes back to your question of what we've learned from reni-cel. We're actually simply using the same targeting strategy. We're using the same enzyme. We're using the same guide. The only difference is that we are putting that editing machinery into a lipid nanoparticle so we can do a single or possibly two infusions, but we're targeting a single infusion or injection. Overall, we have substantially de-risked the targeting in the human with the use of that editing mechanism that we've already validated.
You mentioned one infusion, two infusions. If you see using LNP, how should we think about the need for potential redosing?
It is something that we obviously are making sure that we can do. We are obviously actively looking at that. In an ideal world, we would go to a, we would try and get to a single infusion that would actually be much simpler and easier for patients to deal with. Prudence says that you can actually look, and we should look to ensure that we could actually possibly do a repeat infusion. Even then, that would still be a much, much simpler journey for a patient in the healthcare system than autologous ex vivo.
So far, I guess in the future from now, looking at what a label could look like, how long of a follow-up do you think you would need in a pivotal study to demonstrate durability and potentially have a label that's kind of a one and done?
That's a great question. I think obviously I have a view. Regulators might have a different view and obviously be a matter of degree. What I can tell you is that one of the things that's really good about where we are today is that we have substantial experience now across a number of different platforms when it actually comes to making permanent editors or genome changes using both CRISPR as well as other mechanisms. There's a lot of regulatory and frankly clinical experience. What would be required for the duration of follow-up for an approval or what endpoints you would use, I think actually there's a lot more opportunity to actually use a more aggressive strategy and potentially focusing on fetal hemoglobin alone rather than actually having to follow patients for a prolonged period of time. We would do that anyway.
I obviously think that there's been obviously substantial cross-platform experience with using fetal hemoglobin, for example, as I would say now a robustly validated biomarker to predict efficacy. Again, obviously, because we can actually monitor, calculate, or quantify the edits. Once an edit is in the genome, it's in the genome. It's not going anywhere.
All right. I guess we might have one more minute for maybe one question from the audience if anybody has a question. All right. I think we are set here. Thank you again for your time. I very appreciate the time and the conversation.
Thank you very much. Lovely talking to you.
Likewise. Thank you, everyone.