Good afternoon, everyone. Thanks so much for joining us. Really pleased to have the Omega team here with us. We have Mahesh Karande, President, CEO, Board Director, as well as Thomas McCauley, CSO. With that, Mahesh, let's start big picture with the science here. How are epigenomic controllers or OECs, as you call them, differentiated in terms of the regulatory and target specificity that can be achieved versus other platforms, and Tom, this is for you as well? Yeah. Great. Thank you. First of all, Salveen, and thank you very much for having us here. Thanks to you and Goldman Sachs. You know, super excited. As you know, today is a very big day for us as we file our first IND in c-Myc-related hepatocellular carcinoma. Very exciting. I think your question is a really good one. I think. Look, I mean, I think it's a completely new platform. We call it epigenomic programming. Essentially, from a biology standpoint, right, we go after, you know, these conserved DNA loops that contain genes and their regulatory elements, that are wholly contained units of gene control. They're called insulated genomic domains. They're insulated because when the genes are inside them, they are free from any interaction with outside transcriptional machinery, right? They become these wholly controlled units. What we do is we very specifically target the various regulatory elements, including the CTCF sites that bind and, you know, create that insulation in that loop, right? We do that with very high specificity, and we choose those locations, and then we simply use these new class of drugs called epigenomic controllers or Omega Epigenomic Controllers, that, to put it very simply, target with high specificity, and then they tune the gene to the right level of expression, to bring it back into normal level of range of expression for the durability of the disease, right? That's really how these epigenomic controllers act. You know, these are mRNA therapeutics, so we are taking the first systematic approach to use mRNA therapeutics as programmable epigenetic medicines. The beauty is that we can program in the specificity of targeting, the tunability, you know, which is disease specific, and the durability, which is also disease specific. This is very personalized medicine, personalized to the disease, but not to the patient. How complicated is this? I guess, is this really just the convergence of two platforms in a way, like a technology and a platform? How complicated is it to get this done? Yeah. Maybe I can take it and then Tom should, you know, opine because he's really the chief scientific officer of the company. Look, it is actually pretty straightforward and elegantly simple, right? What we have is biology. This biology was delineated in 2016, and, you know, these. It's a pretty stable biology. These IGDs, there are over 15,000 of them. They're ubiquitous in every cell distributed across the 23 chromosomes. They are evolutionarily conserved in all mammalian species. Now, of course, in lower order species, you'll have sequences which are different from human sequences. But when it comes to primates and humans, they are almost intactly conserved. This is very fundamental biology. It's nature's operating system that nature uses for cellular programming and gene control. That's how nature really works. That's how nature lays epigenetic marks, and that actually expresses genes in the right cell, the right tissue, and life goes on. What we have figured out is when disease happens, it happens because of irrespective of etiology. It's because of dysregulation of, you know, gene expression. What we are really doing is co-opting nature's system by epigenomic programming and fixing it and going and restoring genes to the right level of expression. Look, it's elegantly simple. When you talk about the platform, this is the biology of the platform. The technology is what I explained earlier, which is, you know, what we did was we decided that once we know the biology, what's the best way to tackle this, right? We have de-risked the biology now in four completely different disease areas, and we are using very de-risked technology. We are using mRNA, right, that expresses a couple of proteins inside the cell, you know, at the nucleus and hones in on, you know, the sequence and lays the epigenetic mark. We are delivering it with lipid nanoparticles. mRNA and lipid nanoparticles, you know, has been probably as a modality is in more patients today than all other biotech modalities combined. Albeit we use it a little differently, and we use the ribosomal machinery. It's very simple once we figure out how to do it. Right, Tom, you're the CSO, and I, you know, I probably called it really simple. I'm, you know, an engineer, so I integrate engineering and biology. You, you're the CSO, so you might want to tell Salveen whether it's difficult or simple. Sure, I can expound on this a little bit more. You know, Mahesh is absolutely right. You know, at its core, the recognition that these insulated genomic domains are really the sort of, you know, fundamental structural and functional unit of gene control is really at the heart of what we do. You know, that is in fact how nature regulates our genes, you know, as we're sitting here in both healthy state and then, you know, we understand using a lot of computational tools. Again, you know, there is a lot of, sort of IP and also know-how, you know, in terms of computational biology and other things that go into interrogating the IGDs, understanding where to place these epigenomic controllers, which EpiZips to target, and then trying to understand which epigenomic effector domains to append to those to have the appropriate modulation. When you put it all together, we are in fact co-opting nature's system for doing this. Yeah. Taking a page from nature. Inherently, we believe it'll be safer in the long run. Yeah. You know, if I can add one more point, right, to your question of simple, complicated. Look, anything that is new sounds complicated to people. Let me just point out some timelines, right, in terms of how this works. From the time we interrogate an IGD, we are going after known biology. We can go after known biology for the next 15 years and still build a phenomenal company, right? Although we can interrogate the entire genome for completely uncorrelated biology. Having said that, once we know the gene or the genes that we are going after, we know the IGD that they sit in. Typically, the way nature has organized genes is when there are multiple genes involved in the disease pathway, they usually sit in the same IGD. Again, very sensible. It's nature, how it organizes. Once we zoom into the IGD, you know, our company, you know, our AI and computational prowess is such that we are able to interrogate that IGD very rapidly. In a matter of 2-3 weeks, we are able to really delineate the exact locations and get computationally through ChIP-seq and all, you know, sort of the Hi-C technologies, right, a very clear picture of where we want to act and what level of gene modulation we can achieve. Right? That takes about 3-4 weeks. The next 3-4 weeks, maybe five weeks, we spend in designing putative controllers, right? With DNA binding domains and choosing from a library of effectors that we want to use for that particular disease. That entire process, Salveen, takes us maybe 8-10 weeks, and then we are in vitro and in vivo testing. As all goes well, you know, that entire process to get to a optimized clinical candidate, you know, takes us about 6-8 months. I just wanted to put that in context because this can sound very complicated. It's not. It's actually. We have really brought it down to a fantastic, you know, process where we can get to these things very fast. Great. Perhaps we could talk about the indications you're pursuing, why they are well suited to this platform, and then what the key milestones are that you're guiding to for the next 18 months or so. Yeah. Look, I mean, I think from an indication standpoint, you know, first of all, what we have done is we have gone after known biology, so keep the biology risk low. Then, you know, as a young company, as we set up this pipeline a few years ago, right, we wanted to make sure that we are exploring the breadth and depth of the platform and making sure that it's very robust. Now, Omega as platform pretty much can work in any disease area because we are really going after the epigenome, right? As we chose different areas to go after, right, we decided to go after a, you know, different tissue types, different gene control, oncology, master regulators, you know, regenerative medicine. Because if you think about oncology, the poster child for epigenetics. On the other end of the spectrum lies regenerative medicine, which is really controlled cellular. Oncology is uncontrolled cellular growth, right? Complex diseases, because, you know, if there are multiple genes, we know that we can regulate them with a single therapeutic because it's in the same IGD. That's how we set up the pipeline, right? As we set that broad pipeline up, we interrogated it from the other side for unmet medical need, you know, a patient need and what is actually, you know, something that we could differentiate, right? That's how we sort of brought the pipeline down to a more manageable level. Honestly, we started executing. Whatever took the lead, which c-Myc took the lead. If you see our pipeline, you know, we filed the IND today, yesterday for c-Myc, and then the rest of them are sort of moving forward. From a guidance standpoint, what we have guided to is, you know, one more IND, either towards the end of this year or early next year, right? A second IND. Remains to be seen which one. And then two development, you know, candidates sometime in the middle of this year. That's what we have guided to. And we feel very confident now on the backs of this IND that that will be achievable. You ended the first quarter with about $200 million in cash. Help us understand the cash runway here and how you get through this to this first data set, and what are your plans? Yeah. Look, I mean, I think we feel very comfortable with our cash balance, right? $200 million is very solid, and what we have guided to is, you know, it will last us over 12 months, right? Where we are is, you know, given these market conditions, obviously, I think the prudence that we have always exhibited as a management team, we are making sure that we are spending our money well. Like, look, I mean, put it in context, right? If you can, if we can take it to an IND in 26 months, you can imagine as opposed to four years or five years, right? You can imagine that it's a very efficient process that we run. We feel very good to hit all these milestones as well as get to, you know, good inflection points on our primary program, the lead program, you know, before we have to actually try to raise money. The other piece of this is also now, you know, we have always said that we are very much interested in expanding the pipeline and doing partnerships because we would be remiss with a platform like this, which can be used in so many different therapeutic areas. We cannot possibly prosecute everything ourselves, right? We are open to partnerships. We're having discussions with big pharma, you know, to really partner these out. I think those things obviously add then, you know, to the ability to expand pipelines and deliver on inflection points. That's really how we are thinking about it. What we have guided to is about more than 12 months. You know, at some point, if we change the guidance, we can get into more discussions on that. Your lead asset here, OTX-2002, is a MYC-targeted OEC in hepatocellular carcinoma. Can you describe or just discuss your confidence, given this has historically been an undruggable target? When we might receive first data now that your IND is filed? Go ahead, Tom, you wanna take this one? Sure. I mean, you know, MYC is implicated in more than 50% of cancers, essentially all metastatic cancer. It's a, you know, clearly a target of great interest. You know, many different attempts over the years, you know, to drug it have failed, you know, in the first instance, because it's sort of a disordered protein, so there's not really an easy hydrophobic pocket for it to select a small molecule binder against. It's also because it's pan-essential to the cell in so many different functions, it's very tightly autoregulated, you know, at both the mRNA and the protein level. You know, any attempts to degrade it at the protein level or to antagonize it or to, you know, knock it down at the mRNA level tends to be overcome by the sort of transcriptional driver, you know, at the sort of top of the central dogma of driving that cascade of expression. You know, in our case, our approach explicitly here is direct, unlike some of the other attempts to drug MYC in the past, which have been indirect. You know, by directly targeting it pre-transcriptionally, we believe we'll be able to overcome that autoregulation. You know, certainly our preclinical data, I think, bears out, you know, our confidence in that. There was preclinical data that we've seen, I think, looking at one IV treatment every five days in the xenograft mouse model compared to standard of care for tumor control. How does that translate to patients, especially as you think about what the timing of infusions would look like? Mm-hmm. How are you thinking about durability in managing MYC levels? Well, yeah, happy to take that. In our data that we published in both at AACR and ASGCT for the HCC program, AACR in particular, you know, we showed that in vitro the durability of effect, both for the epigenetic modulation and then the change in expression and viability, lasted over two weeks. That's consistent with what we see in vivo as well. From a sort of allometric scaling perspective and a dose and regimen perspective in the clinic, we expect to be well below a milligram per kilogram in terms of an active dose, and to dose once every two weeks. It'd be a short infusion once every two weeks is our current thinking on that. Okay. You're also going after non-small cell lung cancer. Could you just talk about it? Is this now a different asset, and how does it differ? Mm-hmm. Yeah. Maybe I can take this one. Yeah. Look, I mean, I think, you know, the interesting thing about MYC is, you know, MYC as a gene sits in a large, you know, IGD by itself. It's a monogenic, you know, IGD. What MYC does is it recruits different elements from outside in different types of solid tumors. That's where the dysregulation happens. Maybe super-enhancers in, and actually those interact with the promoter, and that's where the gene gets, you know, tuned up, or cranked up completely, right? The way we are approaching this is in two ways. One way is to be very specific for each disease area, right? Right now, our NSCLC asset takes that approach, where, you know, in NSCLC, the IGD is slightly differently dysregulated than in hepatocellular carcinoma. That's really what we are doing with that asset, right? Slightly different EpiZips to target because, you know, we can actually bring the expression into more control. That's the beauty of our approach, that we don't have to go after just one location. We can figure out which one, which combinations are the best, right? That's one approach. Having said that, right, we look at MYC as a franchise, right? Because, look, it's 40%-50% of solid tumors, 100% of metastatic cancers, right? We know that we can eventually hit all of those. We will, as we progress, try to figure out which direction we go in, right? Both paths are open, but right now the asset that we have is differentiated. Can you walk us through as well the combination data that you showed in non-small cell lung cancer and the rationale for this? Would you be moving forward with a combination program? Yeah. Go ahead. You wanna go over it? Yeah, sure. I mean, it certainly, I think the sort of prevailing paradigm in terms of oncology treatment is moving, you know, ever more towards combination therapy, right? Certainly in the case of non-small cell, the prevailing therapies are given in combination. What the data that we showed at ASGCT, for example, was showing that with EGFR and MYC inhibitors, that we saw additivity in vitro. We've also seen, I should say, in the context of MYC inhibition for the HCC program that we see strong additivity with kinase inhibitors, for example. As Mahesh mentioned, I mean, just from the biology of MYC, it's known to directly regulate a number of checkpoint factors in particular. You know, because while it's also regulating sort of tumor cell intrinsic mechanisms like apoptosis and proliferation, it's also doing MYC and under the cascade of genes regulated by MYC, controls the programming of the tumor microenvironment. Which allows, you know, by reducing MYC, you allow the sort of, you know, reignition of the host immune response within the tumor microenvironment. You can take a cold tumor and turn it hot by downregulating MYC. Some of the additional data we showed in terms of the potentiation of some of these combination approaches by targeting MYC as a natural byproduct of targeting MYC, is that you see increased PD-L1 expression in tumor cells just by inhibition of MYC. You know, it's not hard to imagine that you know, in combination with an anti-PD-1 or PD-L1 agent, you might see, you know, significant additivity clinically. All of that plays into our thinking in terms of the clinical rationale. We've yet to give details on the clinical plans. Look, I mean, I think, you know, it makes sense, right? I think if you think about what we are doing is, and I've worked in oncology for a long time with Novartis, right? I can tell you that this is such an orthogonal approach, right? Obviously, we're gonna look at monotherapy, and we're gonna prove that out, right? In oncology, combination therapy makes a lot of sense, and especially if you actually get synergistic combination therapy, which is what we would love to prove out, right? It remains to be seen, but at least our initial forays and initial data, you know, solidify the hypothesis that is possible. You know, it's orthogonal enough that and the other thing about, you know, our approach is that, you know, Tom talked a little bit about autoregulation earlier, right? The other piece is that we also believe that what happens in oncology, because we are targeting everything at the IGD level, right? If you have any specific, you know, or mutations that happen, they usually happen within the IGD, and we are controlling the IGD. We believe that, you know, and that our drug also, by the way, is not resident in the system because it lays the epigenetic marks, right? The mRNA, LNP, and those proteins that are expressed degrade within a matter of hours to a couple of days, but what stays behind is that effect that we engineered in, right? Given that, right, we believe that we won't hit resistance mechanisms. I think it could potentially be a very powerful armamentarium, you know, either in monotherapy or in combination therapy. That's really how we are thinking about this. Makes sense. Could you walk us through progress in your candidate targeting, liver regeneration and when we might, you know, expect an IND there? Yeah. On that, obviously, you know, our work is continuing, right? And we are, you know, HNF4 alpha is a near and dear program to our heart because it really is about liver regeneration, and we have shown some incredible data in mice. We are working through that. You know, as a small company, we are obviously making sure that we are focused and, you know, the work in HNF4 alpha continues. We haven't guided on the IND data and, you know, at some point in the future, we will guide on that. Right now, that's all I can say. The alopecia program. Yeah. I think we just had the first drug approved in alopecia areata. Yeah. Which was great. Yeah. No, I mean, look, that is incredible, to be honest with you. It's such a serious disease for people. We, you know, all know, and I personally know people who actually are suffering from all forms of alopecia areata, and obviously androgen, you know, male pattern androgen, right? What we are targeting is all forms of alopecia. We are preclinical. We are very orthogonal, like we talked about in MYC, right? We're very happy that JAK inhibitors, you know, have shown those tremendous data. Look, we do believe that, you know, without really specifically commenting on sort of, you know, those particular products that we don't really know very closely, there is a lot of space to come up with products that are potentially very safe, you know, very tolerable, right? You know, that give. We are seeing some incredible preclinical data that we have, some of it which we have shared. Yeah, I mean, our confidence in the program is very high. Along the same lines, you know, at some point, we will guide it. You know, we are looking at, like in HNF4 alpha, we are optimizing it, because there's an optimization of the OEC, there's optimization of the delivery, so we're working through all of that, and we'll be able to guide on that as well, like in HNF4 alpha. Any questions from the audience? At the gene level, you're really changing the structure of the chromosome. I'm just wondering how changing that gene would? Sorry. Can you repeat that question please? At the gene level, you're changing the structure of the chromosome when you are altering the IGDs. Do you think you would potentially unspecifically change the overall chromosome structure? What kind of unspecific effects you might get with your process? Yeah. You might want to explain that. I don't think we're exactly doing that. Yeah, no. I mean, we're not looking to sort of overtly perturb chromosomal structure at all. I mean, in fact, we're taking advantage of the fact that these IGDs, that what the interventions we're, you know, the modulations we're doing inside the IGDs are actually, you know, confined to those so that we're not affecting genes outside. I mean, so for example, in all of our programs, we look for, you know, genomic off-target effects, right? The DNA binding domains that we design are incredibly specific, and we test that using, as Mahesh said, we look for chromatin interaction, you know, assay touch points. We, you know, we look at sort of the, you know, quantitatively and qualitatively at off-target and on-target binding. We look at the specificity of on-target epigenetic state change. We, you know, we also look transcriptomically, you know, genome-wide at the, you know, transcriptomic changes, both expected and unexpected from, you know, from these interventions. In general, we see very, very high specificity of targeting in terms of, you know, if we're trying to disrupt loop, a loop structure or, you know, change the binding of, you know, certain factor to an enhancer element, for example. A lot of the looping and the interventions we're doing happen within a loop. It's inside. They're sort of internal to the loop, so there's really no perturbation outside. Mm-hmm. Yeah. I think, you know, to think of it simplistically, right? I think, you know, if you think about gene dysregulation, it happens because of, you know, simply speaking, the structural and functional changes in IGD. It's almost like going from a pristine state to a disease state. What we are doing really through all of these things that Tom just talked about is, you know, again, simplistically speaking, we are restoring that IGD as close to the pristine state as possible. Really, whatever changes we are making are, you know, very specific, and they're contained within that IGD to bring it back to the right structural or functional orientation that first got dysregulated. I think from that standpoint, there is very little risk to sort of, you know, perturb overall chromosomal structures and have off-target safety issues. We test that very extensively. In fact, the data that we have put, you know, we have a corporate presentation on website, and we've shared it with you guys as well. You will see exquisite specificity. I mean, we have targeted, you know, a CTCF site on a single chromosome and hit only that. And, you know, you'll see a threshold beyond which, you know, you would see off target and everything else, chromosome, like genome wide screen, everything is, you know, miles away from sort of that dotted line. I think, you know, we. We take this very, very seriously, and we have taken through our MYC program, and you'll see in a poster we have actually shown some of those data. Yeah. Yeah, we look at that at every level from the sort of genome, epigenome, genomic level, and then at the cell and tissue and macro level from a safety assessment perspective too. Great. Maybe one last question for me. How, what do you think about the overall safety profile of this platform? Yeah. I mean, I think, you know, we just sort of talked a little bit about safety, right? I think, look, the beauty of this platform is, and Tom, I'm sure I'll forget a few things, so you should add. That's it. The beauty of this platform is it's highly specific in terms of how we target, right? What we are really doing is laying an epigenetic mark, right, that tunes the gene to the right level, right? Then the drug, the medicine, right? If you think about, you know, what's happening there is the mRNA gets degraded very rapidly, right? The epigenetic mark gets laid. The gene gets, you know, sort of it does its work, gets to the right level of expression for the durability. The proteins that were expressed also degraded within a matter of 2-4 days. If you've seen some of our data, you'll see that with one treatment, we have been able to engineer a durability for a few weeks to actually even over two months. Right? That's with a single treatment. Some of these changes are heritable, as daughter cells, you know, parent cells divide into, you know, mother cells divide into daughter cells, but they are all transient, and they are for the duration that we actually engineer. I think that's one piece which is very, keeps it very safe. Because, look, I think, you know, if you think about epigenetics, right, there have been drug development in epigenetics for the last 20 years. You know, I'm really happy that drugs have been approved, that patients have choices. Those drugs have taken the approach of small molecules, et cetera, where the drug needs to be resident in the system ubiquitously, non-specifically, right, for days. You know, 400 mg BID, 800 mg a day, two weeks at a time. Our thinking is to dose 0.5 mg per kg every two weeks, and the drug is gone. What stays behind it? I think that's one piece, right? On top of that, as we develop this, right, we have enough information and data that the specificity is proven out. We feel very good about the overall safety profile of our drug. Remember, another thing is, although we are genomic medicine, we are not making any nucleic acid sequence changes. Right? We are not changing underlying DNA sequences at all because we don't know what the safety profile of those drugs can be, right? Our conversations with the FDA, they understand this. There is no additional safety follow-up. They get this, right? We feel very good about the safety of our platform. Great. Well, with that, thank you so much, Mahesh. Thank you, Tom. Really appreciate it. Thank you. Thank you. Thank you very much, Salveen.