Prime Medicine, Inc. (PRME) Earnings Call Transcript & Summary

All right. Great. Well, thanks for joining us. I am Terence Flynn, U.S. biopharma analyst at Morgan Stanley. And before we get started, just I'd refer you to our research disclosures website at www.morganstanley/researchdisclosures. And with that, I'm very happy to be hosting Prime Medicines today. We have Keith Gottesdiener, who is President and CEO; and Allan Reine, the company's CFO. Thank you both so much for being here. I really appreciate you taking the time. Maybe to start, we can just kick off with kind of a high-level overview of the company and the platform because, again, I think it is obviously very differentiated in terms of the platform that you're working on that you've developed and then we can go from there. But thanks again both for being here.

Thanks. First of all, it's our pleasure to be here. And we do think we have a very differentiated platform in many ways. So Prime Medicine is a gene editing company. But really, we think of it as a third-generation gene editing company. Some of the original companies, CRISPR Base can do some amazing things and then Beam came along with Base Editing, a second technique that really began to correct things as opposed to some of the things that CRISPR could generally do. Prime Editing is really all about correcting genes. So what we're able to do is to go into the genome in the endogenous locus at the gene itself, we can make corrections. They could be very, very small ones, single base payers or small insertional deletions. We can look a little bit more so what we call hotspot editing where we can look across a range of a particular gene and correct a whole area back to normal. We also can do -- deal with very large deletions from the genome if need be, for example, deleting out the repeats and repeat expansion or triplet diseases. And more recently, we've spent time talking about our PASSIGE technology, which is a way to very precisely to put in using non-viral approaches, multi-kilobase gene size pieces of DNA as well. Now we can do that without making double-strand breaks in the DNA, so our corrections are incredibly precise, very, very highly efficient, but they also come without off-target editing because we believe that one of the key differentiations for our type of gene editing is the ability to provide a different safety profile. And the fact that you can go in and you can make precise corrections that are therapeutic without, I'd like to say, mucking around elsewhere in the genome. We think it's going to be very important for both doctor and patient and probably regulatory acceptance of gene editing approaches.

Great. I appreciate the background there. The other thing, I think, that's always relevant is just it seems like the pace of innovation in this space is so rapid when you think about the industry, but also academia and all the work going on. And so how do you make sure as an organization that you're staying at the forefront of all that innovation? And again, as new to us, you may just run through the technologies, CRISPR, Base Editing, Prime Editing. It's a very short time for that innovation to occur. So as you think about kind of the next evolution, how do you make sure you're always staying at the forefront here in this field?

Well, before we start, I think you need to step back a little bit and you need to ask yourself, what is it you would want in a gene editor that isn't available today in a Prime Editing type of approach? And the answer is there's very little, if anything, we can identify. When you think about CRISPR technologies, you could sit down and you could make a list and you could say, these are the things we can't do with this or these are the problems. It doesn't take away from what the goodness that can be done, but you can make that list fairly readily. And I think the same thing is true when it looks at Base Editing. When you get to Prime Editing and you begin to think about, "Okay, what is there that's missing in this that I would really like to have?" There's a few little tweaks around the side, so we can see, many of which we've actually addressed by developing Prime Editing, but there really isn't that much. So there isn't this burning need in many ways to do something beyond Prime Editing because there's a gap in some ways that goes forward. Now having said that, there are a lot of ways to get to the same place. And I think some of the more creative things that have come out recently are people doing things that end up at exactly the same spot is what we could do with Prime Editing, but may get there by a different approach. What I would like to point out, though, is many of the new things that are coming along to do that. How do I say this sort of nicely? They're just much more complex in many cases. They require all sorts of additional machinery to make things happen. And the real question is, do they add real value over what we can do today with Prime Editing technology? Certainly, today, it appears as if the answer to us at least is no. And I think the second part is many of the new innovations in this field are very, very early, and they really haven't been demonstrated in ways that have really helped us to understand if they have the high editing efficiency, the specificity, both for on-target and off-target yet. I think we'll have to wait and see. Now of course, having said that, that doesn't negate any need for us to stay at the forefront of technology, we do that by carefully watching the literature, having very, very interactive discussions with people in the field to hear what's going on. We have an extraordinary scientific advisory board, okay, which I think is very important. And probably most important is we've dedicated a small but significant amount of our resources to innovation group. So Andrew Anzalone who's the postdoc who thought up the idea of Prime Editing and brought it to David Liu's lab where they developed it together, heads a group of incredibly talented people, many of them who came from David Liu's lab, our founder or one of our founders. And so we keep up the innovation with that. Now of course, last but not least, David Liu, who's at the Broad, who's certainly one of the innovators in gene editing approaches has a very, very close relationship with Prime. So he's helped to funnel any of the things that he's brought forth that are relevant to our type of gene editing directly into Prime as well. We're very thankful for that.

Okay. Great. The other area, obviously, where there's a building focus is delivery. I mean that remains one of the, I'd say, bigger hurdles for the whole editing field as we think about it. So as you think about innovating in delivery, maybe just give us kind of your current state where you are? What platforms you're employing? And then where is this going? And then how do you access that technology? Is this something that you do internally, which has been one approach? Or is it something that you look externally to kind of bring in through academia or partnerships?

Yes. I'd say the answer to all your questions is, broadly, yes. But to be a little bit more specific, we started, we paired Prime Editing with ex vivo approaches, with lipid nanoparticle, or LNP, approaches primarily to deliver as well as AAV approaches. And we're happy to say that Prime Editing works very well with each of those delivery approaches. We have programs for each of them going forward. We didn't know that, that was going to be the case when we started, but I think that's very much the case today. And we just made an extraordinary progress. In the course of doing that, we've certainly worked out all the kinks that we need for ex vivo delivery. There are certain new capabilities that we're working on like cell shielding and other approaches, which we can explore if there's time, that would make it even more exciting. Our LNP technology is something that we call proprietary. So it's really ours and including lipid. And we're very pleased with it because our approach was to make what we call a modular LNP approach, where we use the same LNT -- LNP formulation for every single one of, for example, our liver programs. And we think we're very, very close to achieving that, and that will help us to be very modular moving from one gene to another gene, one program to another very, very easily, quickly, cheaply, et cetera. And our AAV work has also been remarkably successful as well. But a little bit more of that, we've done outsourced or dealing with outside vendors than maybe some of the others as well. Now some of the work -- some of the places we'd like to work is we've worked very, very hard on targeting mechanisms for LNPs. For example, we have proprietary targeting methods for the liver that we've used as well, and we're bringing forward for some of our programs. We are doing work with AAV capsids. But the field of delivery has blossomed over the last couple of years. I joke that in 2020, when I looked for delivery companies, it was hard to find them. Now they're all over the place anyways. So I do think in a lot of ways, that ability to go out and access that technology is important. And it's pretty clear we can't do all of this ourselves. So ours is a mix of having expertise in the parts that are very unique to Prime Editing and that's a good portion of them, but much less than half. And then the rest of it is stuff where we access [ hourly ] either with partnerships or other kinds of collaborations.

Yes. What on the LNP approach? I mean you mentioned the liver. Obviously, what would be like some of the other potential near-term organ systems that you guys could address with this modular system?

Well, I -- to be honest with you, one of the places we'd most like to see that modular system work outside of the liver would probably be in the lung because we're making great progress with the gene editing part of approaching the lung, particularly for our cystic fibrosis program. So that's a place where delivery also isn't solved in many ways. But it is when we're -- it's important to point out that some of the challenges to delivery are less for Prime Editing than others. If you deliver a gene therapy to the lung, you need to get it to exactly the cells that you want, and some of the cells tolerate that and some don't, some you want high levels expression, some you want low levels or physiological levels of expression. That's very difficult to achieve with some delivery methods. In the case of Prime Editing, you can deliver and let the source sort it out because cells sort it out because what we do is we correct the endogenous gene and it stays under the endogenous control. So if that cell is supposed to produce a small amount of that protein, that's what it produces if it needs a lot. So you can use many of these delivery methods in very different ways than you might if you don't have that ability to have the endogenous control, really control the gene expression and the cell pattern expression.

Right. Yes, I remember a lot of those gene delivery companies in cystic fibrosis from, I don't know, like 5, 8 years ago. One of the other challenges, I think, was getting through the mucus in the lungs of patients. And so is that something that you feel confident with an LNP you can get enough penetration through the mucus to get to the underlying tissue?

Well, you have an underlying assumption there that this would be an inhaled approach, okay? I think that, that's certainly something that we very much want to think about, but the other part of it is, do you want to come from the blood side of it? And part of the reason is, keep in mind, what we're talking about is a ones-and-done therapy and then with the ones-and-done therapy, you want to get to the stem or progenitor cells. We know we've shown in our own hands, I don't know if we've actually presented it yet publicly in a conference that we can edit those cells with high levels of efficiency. But it is entirely clear what the best way to get to them one day.

Okay, great. And then is there anything as we think about milestones on the delivery side, just anything that is coming up later this year or next year that we should think about from a clinical or preclinical basis to like from a milestone side?

Yes, I think probably the most important thing is for us to declare victory in a modular LNP and to show, for example, non-human primate data using a modular LNP, if this gets very high-level editing efficiency and such. But there are other parts of it as well. Of course, we want to show a very clear safety margin, particularly in light of some of the difficulties people have had with LNPs. Preclinically, we like what we've seen so far, but we want to fill out that story. And we also have very exciting data about redosing these LNPs as well. Most of our studies are done in non-naive, non-human primates. So these are ones where we edit Gene A and we take a liver biopsy, we wait a couple of months and then we do Gene B and C and D. And what we found is, no matter how many times you go back, it seems to be that the animals respond well. There doesn't seem any immunogenicity issues. I'm hoping we don't have to re-dose, but wouldn't it be a great thing to be able to do that if and when the time came. So I'm hoping we'll share a little bit more of that data later in the year and those sort of are probably the most important things that I could think of.

Okay, great. I guess just moving on to the lead asset, PM359 for chronic granulomatous disease, I can never pronounce, it's a mouthful CGD. You're doing a Phase I, II trial here. Maybe any updates on enrollment and then as you think about the key endpoints and the data we're going to see next year. Maybe just remind us what you're going to be looking for there to say, "Okay, this has been a successful trial, and we're going to take it to the next step?"

Yes. Thank you. We're not going to be giving enrollment updates along the way. I think the only milestone we've said is that we'll share data next year. We have provided some relatively general advice on this. It's about just so people who get a mental image of it. What we've told people is that we're working with academic centers, many of which wouldn't become activated until our IND was open, which is on or about May 1, that we expected it would take for the first patient about 6 months, give or take, to get potentially to a dosing, just thinking about a Gantt chart as one does it between activating the site, recruiting the first patient, mobilizing all of the individual parts, doing the editing, doing QC, which is obviously an incredibly important part for the first patient and then getting it into folks. And then you have to keep into mind that they have to block a month or so of their time to spend in hospital for autologous bone marrow transplant, which starts to become a problem towards the end of the year. So, I think that's about the best guidance that we could actually give on that. Keep in mind also that we've told people that we have to demonstrate the safety in the first patient before we could go to the second. And safety generally means that we have shown that engraftment returned. That's typically a 1 to 1.5, maybe even a 2-month process. We can safely say that when we put back into patients, in fact, it has resulted in engraftment. Now if you ask what a data package would look like, we haven't been very specific about it, but I can tell you, there are probably 3 categories of data we'd like to present to clear victory. The first is rapid and full engraftment. That's a place where, for example, Graphite a year or 2 ago started. The second is to show high percentage editing of the individual stem cells, which come from bone marrow, a bone marrow aspirate or something like that as well or even from peripheral cells. And third is reconstitution of the enzymatic activity, which is missing in these patients that prevent them from fighting off infections, which is the defect for this particular case. So hopefully, we can present all of that data as well and we'd like it to be a robust data set. We're a pretty conservative company. We don't kind of just shoot things out a little bit from the hip. So I would look for a good-sized data -- not a good size, but a good, robust data set, whatever that would be to help people to believe, yes, this really has been nailed.

Yes. Will you guys issue -- I know you're not going to give enrollment updates, but is the materiality around the safety in that first patient and dosing of the second patient, does that rise to the materiality threshold such that you would provide some kind of like disclosure around that event?

I probably can't answer that question today.

Okay.

Allan, can you answer that one?

No. I mean, look, if we look at most Phase I studies that are open label, you can typically enroll and most of the time, it's not a material event where you have to disclose right away.

Right. Okay. Fair enough. And then when you think about the data, is this something that's a press release or is it more like a conference? Like you said, it sounds like you're conservative, so conferences of...

So we haven't really decided that as well. And there are many factors that could go into it. In general, we have presented data at conferences, but we've made plenty of exceptions.

Okay. And then maybe just remind us the editing threshold. I mean you mentioned that a high percentage of editing in the stem cell is an important endpoint. But what do you think is that necessary threshold based on your preclinical models that you need to reach?

So we don't have to use the preclinical models because there's actually a great human data. These patients get allogeneic transplants and when you do an allogeneic transplant, in the end you often get a mixture of the new donor cells, which are curative and the old patient cells, which are worthless for the patient from a disease point of view. What they've been able to show is in clear human examples, quite a number of them that if you get 15% or 20% of the new donor cells, you seem to have ameliorated the risk for infection from these historical papers. So we would put a fairly strong 15% to 20% now for that overall. And I think that's fine. On the other hand, I would just point out that when we do our animal studies, remember, we take human HSC cells, edit them just like we would do in a regular clinical trial, the clinical trial we're doing. The only difference instead of putting it back in the people, we put it back into immunodeficient mice. So in the process, we've been getting 85%, 90%, sometimes 95% precise correction. So I would certainly, we know what that threshold is that's probably clinically relevant, but if the animal models are at all predictive, I hope we can certainly beat that threshold handily.

What -- obviously, safety is important. You mentioned engraftment and then this high percentage of editing. Is that the kind of totality of data that you then need to make a decision on go/no-go for a pivotal trial? Like is that going to be that initial data set that we see whenever we get it, is that going to be enough or do you need some duration of follow-up or again longer...

So, we haven't had the discussion with the agency. I will tell you, it's certainly our intention that when we have clear and convincing data, okay, which I'm being a little vague about. But when we have that, we're going to go and speak to the FDA about how to convert this Phase I, II trial into a pivotal trial that's designed to make that conversion. So we hope we can do that relatively early, and we certainly have plans to do so. We'll see if the FDA and the other regulatory agencies we're working with will agree with those plans.

Okay. And remind us this is global, not just U.S. sites?

That's correct.

Have you talked about the total number of sites you're targeting?

We haven't. We haven't given any data. The only thing I would point out is we do our processing here in the U.S., and there's a time limit to how far you can transport these things once you've done the editing. So for example, we know we can't do studies at this point in Australia or New Zealand, places like that because we just don't have that window to do the flight transportation back to patients.

Okay. Because these aren't frozen, right?

So sometimes -- well, it's a little complicated some parts are, but the point is that it is just as feasible. Now having said that, for a pivotal trial, we would take a different approach and develop sites that can do the processing in more than one place. But for Phase I, we're keeping it very simple in processing.

So more limited number of sites?

Correct.

Okay. Okay. Understood. The -- I guess, just remind us kind of the commercial opportunity, like what drove the decision here for CGD is kind of the first indication? And how do you think about the commercial opportunity?

Let me answer the second question first. The commercial opportunity is probably hundreds of patients here in the U.S. is what it seems. Remember, there's a fraction, probably 1/3 or 1/4 of this total CGD patients, which number in the thousands. So we would anticipate many hundreds of patients potentially would be eligible for this overall. We didn't pick this specifically to be our first indication. It kind of happened. I don't mean that in a bad sense. It wasn't like we just threw things up in the air and so we landed face up. We started a bunch of programs together, which were programs where we felt we understood how to deliver them into the clinic, some were AAV, some were LNP, some were ex vivo. This is a program where everything worked perfectly. The first time we tried it, this is an exaggeration, of course. But essentially, every approach we stepped along the way worked. We had a great team. We solved problems very rapidly. It just moved ahead of the others. But it is a great choice in many ways because the only alternative therapy is an allogeneic bone marrow transplant, and that comes with much greater risk from the transplant, a strong risk of graft-versus-host-disease, lifelong immunosuppression. We're a ones-and-done therapy. They have to go through a month of the risk of an autologous versus an allogeneic bone marrow transplant. But when they're done with that, they're cured. So if they make it out of the hospital with the kind of curative data that we're hoping to see. At that point, their life is essentially, hopefully, back to normal. So there's a lot of interest from patients and doctors.

Okay. Okay. Great. I mean you've touched on this a little bit in your opening remarks, Keith, but just this whole question of off-target editing. And so again, recognize that it's a lot lower with Prime Editing here. But what's the current framework at FDA? And what's their comfort level here with this question? Again, recognize it differs probably by the delivery and the cell type and there's many nuances here. But just high level, where is FDA on this question from the field perspective?

Yes. So first of all, we've had very extensive discussions, both this part of our IND and outside of that, about off-target editing. And I will give the FDA credit when I listen to the advisory committee meeting for [indiscernible]. I felt like both the company and the FDA were having trouble getting their ideas across to some degree. The team that we've been working with the FDA and it's been different teams, potentially for different programs, they're extraordinarily up to date with this. They understand it well. They've asked great questions. They know exactly what they want from us in many cases. They don't prescribe things necessarily. FDA has often said to us, tell us what you think you need to do and we'll comment on it. Most of the time, they have not asked us for additional information and part of that is just to put it into context, when Vertex and CRISPR described their off-target, they talked about 3 assays, one of which was a karyotype. We're currently doing 11 different assays, some of them that are based on sequence specificity, some that are sequenced independent. There are rearrangements and translocation assays. Some are very pertinent to Prime itself, some are more pertinent. For example, we do all the double-strand break type activities, even though we can't find any double-strand breaks, just to nail that shut and say those things are not happening with our work. In our program so far, we have not found a single off-target edit when we've done it with quality reagents. And that's an important point to make because the quality of the agents can have an important part on it. But there were none, for example, in our CGD and we haven't found any so far though it's a little more preliminary in each of our 3 or 4 advanced programs. That doesn't mean we're never going to find one. But it does mean that whatever it is, it seems to be remarkably rare and essentially, just not there. So, we've been able to convince the FDA of that. Whether that gives us any bragging rights on the next one, bragging rights, of course, isn't the right word, but some -- a little more freedom there. I don't think we've seen any evidence of that, but we certainly hope someday to get to the point where the FDA is going to feel Prime Editing is a different technology in terms of its off-target. And we've worked hard to do more than anything they've asked. Let me just give you a good example of that. When you look at most companies that have talked about the sequence-specific predictions for what could be off-target activities, companies pick 100, 200, 300 closely aligned target sites in the genome related to the individual target site. We did, I think, 8,000 to 10,000 predicted sites, just to really nail this down, so you could think of that as somewhere between 10 and 20 more sites that we evaluated in order to show those no off-target. So it's just an example of a place where we really feel like there's a major advantage of ours, where we're going to do everything we can to really do it. And so far, the FDA seems to be like our approach, at least from every bit of feedback we can get is answering their needs.

Right. And that was specifically for 359, right, the 8,000 to 10,000 sites?

Yes.

Yes. Okay. And the 11 assays same context?

Yes. I suspect, though, probably one thing I should add is those assays are applicable to any kind of Prime Editing approach. So whether we do LNP or in vivo, those assays are there. There may be some specialized more around the outside that we may have to do, but these are the core of everything and they're pretty big core of things.

Yes. Okay. And so you basically look to kind of replicate that for any additional pipeline product. It would be the same kind of robust approach that you take across any of your...

Correct. And maybe if I could just add one point there. Our whole approach is modular, okay? This is just an incredibly modular approach to gene editing. The guides change when you do editing, but almost everything else stays the same. That's why we talked about a modular LNP. But in every stage, what we're trying to do is to make it so that as many things are uncommon from program to program because that just makes it faster, cheaper, easier, easier on the regulators to do that kind of work because you're really saying we've already shown you this kind of data 8x, 10x. You don't have to comment on the assay. You don't have to comment. You know how to interpret the results. We've dealt with some problems. You've told us what format you wanted in, think -- little things like that. You got it.

Okay. What -- so as we think about kind of the next set of pipeline assets, maybe just level set us in terms of expectations for what we should be focused on next and how you're thinking about prioritizing which asset comes next through the pipeline?

Well, I want Allan to have a chance to answer a question. So we save that one for him.

Yes. So as we think about -- I'll start with sort of prioritization first. I joined the company back in January of this year and have worked with Keith and the team to really think about what is the right way. I call it kind of spending to value, right, ensuring that it's the right allocation of dollars that we're getting some return on that investment and what is going to be realized in terms of getting us excited, investors excited, the stakeholders excited about the ultimate opportunity of what we're doing. The company is only 4-ish years old now, right? I already have an IND ongoing. And beyond that, have this pipeline of assets because there are so many exciting places really to deploy this technology. And I think as you look at the pipeline today, some of those assets will be partnered. And I think that will be an important part of our sort of capital formation strategy, but also the strategy of getting what I think is going to be these important medicines out to more patients. And part of it is we're not going to be able to work on all of these things as well. And so I think you'll hear a little bit more from us as we go through the rest of the year on sort of what are the things that we will plan to focus on. I won't talk about that necessarily in specifics today, but you did ask about kind of what are sort of some of the other exciting programs within the pipeline? I think Keith talked a lot about our modular LNP to the liver where we think we really have solved that problem and have a really good construct there. I think within liver disease, I think Wilson's disease is sort of a prime area for something like pun intended Prime Medicine to work very well. And that is one exciting program out of -- within our pipeline today, whether it's cystic fibrosis or other things that we're working in. I think there's a lot of still very exciting programs within the pipeline. And again, I think we'll talk more about that as we get through the rest of the year.

What would be like the earliest you could have an IND or CTA for like Wilson's disease, for example? Is that like a '25 event?

I think more likely a 2026 event.

Okay. Okay. Got it. And is that -- that would be an in vivo approach?

That's correct.

Yes, that would be the liver. Yes. Okay. Got it. Okay. And then what -- on the other one, I think you guys talked about like ocular before. Is that still in the mix?

Yes, it's still in the mix.

Okay. All right. But just further behind these other ones or...

No, I think we've talked about potentially getting to IND, enabling studies this year. So that also could be a late '25 or early '26 IND.

Okay. And then what's any -- you've mentioned you can't move all these forward, you need potentially a partner. What's the landscape like right now? It seems like when I look at the larger cap companies, some of them have leaned in on genetic medicines broadly. Others have maybe leaned in and then pulled back. Others aren't there. But as you look broadly like on an aggregated basis, what do you think the larger cap companies are? How are they thinking about potential partnership opportunities?

Yes, maybe I'll let Keith answer that. He's been in a lot of those conversations.

All right. That sounds good. I think there's quite a bit of interest. I think companies are still trying to -- larger-cap pharma companies or big biotechs are still trying to figure out where gene editing fits into their portfolio. A couple of years ago, when we talked to them, it was very hard to gauge their interest. Some of them kind of were interested because it was the newest, hottest thing. But I don't think they had really done a tremendous amount of strategic thinking about where it would fit into their pipeline stuff, and some have retreated from that. I think today, over the last year, it's been very different. I think companies, first of all, are a little past that this is the shiny new toy approach, which is kind of bad for valuations, but probably good for seriousness. I think second of all, they've gotten past there, how do I get through to 2030 concerns in many cases. So they're starting to think a little bit more long term of what their pipelines look just a little bit farther out. Third is, I think companies like particularly Prime, so I can't talk for the others, that we needed to build up a level of credibility. So we had to show them that we could interact with the FDA, that we knew how to manufacture what we're doing that we can get in vivo data. I think over the last year, we've just been in a totally different spot having conversations with pharma. So that's not the environment. It's more about us. And I have to say those talks have been incredibly positive with a very large proportion of the biggest pharmas, for example, who have really dug in quite deeply in what we're doing. Some of them have come to us. Some of them, we've talked to in terms of licensing certain parts of our programs like CAR-T or hearing or even potentially ocular, which we're trying to decide how much we can do ourselves or with a partner. It's just been very, very exciting to talk to those folks. We've talked about BD a lot over the last couple of years. I'm hopeful that we'll be able to be a little more specific in the not-too-distant future.

Okay. And how does that all fit into kind of cash runway, maybe Allan, for you in terms of thinking about where you're at right now? And then as you prioritize the pipeline, like how to think about the cash runway?

Yes. I mean as we think about cash runway, we've talked about having cash until around midyear next year. So obviously, we're thinking about non-equity ways to fund the company and that gets back to what Keith was talking about where, again, we never sort of promise on BD and we never would. But I think there are a lot of, I think, opportunities to think about collaborations as an important source of funding. And I think it will likely be a very healthy mix of BD and equity as we think about funding the company in the future.

Great. Well, Keith and Allan, thank you very much. Really appreciate the time and insights today.

Thank you for having us.

Thank you. Bye-bye.