You hear me okay? Okay. Welcome everybody to the Leerink Global Healthcare Conference. My name is Roanna Ruiz. I'm one of the senior biotech analysts here at Leerink, and it is my pleasure to introduce iBio. We have Martin Brenner, CEO and CSO, and Felipe Duran, CFO. Thanks for coming.
Thank you.
Thank you.
Great to have you guys. I'll start with some big picture questions before I drill down into more detailed questions as we get into the details. Maybe to kick it off, for investors that are newer to the iBio story, could you just recap your longer term vision for the company and how you're thinking about it evolving both in the obesity and the cardiometabolic-
Yeah.
-space, what are you focusing on these days?
Yeah. Good question. Two years ago, we pivoted into the cardiometabolic space as a company, and our goal at the time was really to look at what comes after the GLP-1s. It was pretty clear that this space would be very highly occupied, but it also was very clear that GLP-1s will become a cornerstone of obesity treatment. They do leave important areas of patient care open. That's what we focused on. If you will, we're a ambitious company. We're very small, but at the same time, we do have a portfolio approach to treating obesity. We're not an incretin company. We're not a TGF-beta company. We really are focused on cardiometabolic disease.
Different mechanisms, different approaches, which is quite de-risking to a degree in the company because we all know this is a very high attrition space we're in. We wanted to make sure that, you know, a few of our programs really are successful in going through all the way. You mentioned cardiometabolic. I think with recent data, the announcement of 35Pharma being acquired, we have a different spin on potentially treating PH-HFpEF, so heart failure with preserved ejection fraction. I think the TGF-beta family is making a real difference in the pathology of this disease, so that's something we definitely wanna tackle as well. We're considering ourselves as a therapeutics company.
Okay. Great. That sounds good. Just to lay the groundwork here, what do you see as the most important value inflection points for iBio, let's say in the next 12 to 18 months?
I'll hand this over to Felipe because-
Sure.
-he can speak with a lot more authority to that.
Obviously, the Wave and Arrowhead data that's going to be reading out externally is a big inflection point for us. Internally, we are going to be filing our Activin E by the end of this year, which puts us at first patient dose first half of next year. If we're able to enroll the patients fast enough, we could have interim data by the end of next year. That to us is extremely exciting. On top of that, as Martin mentioned, our bispecific, which is our myostatin activin A, that's about six months behind our Activin E program, so we can be in the clinic by second half of next year. Lastly, we just filed our myostatin program, and we are hoping to have acceptance in Australia, and that could have first patient dosed as early as third quarter.
Those are major inflection points. That doesn't even mention our Amylin program, which...
Which to me is extremely exciting given the space.
Yeah, you've got a lot going on.
Yes.
which is great. I'll start with the lead program.
Yeah.
IBIO-610, where I get the most questions from investors-
Yeah.
-we'll dig in further. That's your Activin E antibody.
Correct.
From a mechanistic standpoint, where do you believe the antibody approach going after Activin E differentiates itself versus some of your competitors who have RNAs, et cetera, and in terms of, you know, different components, efficacy, durability, safety, et cetera?
Yeah. Really good question. The Activin E pathway, you can interfere with this in three different places, right? One is what the siRNA companies, Wave and Arrowhead, have shown on the gene level in the liver. Validated approach, you know, early clinical data from both companies are very, very promising and validating. What we're pursuing is not going after the gene in the liver, we're going after the protein in blood. That's a near perfect target for an antibody. The last, you know, point of interference could be on the receptor level, which can be very beneficial, but can also actually add safety signals. We're basically watching the entire field. What we believe by targeting the protein in blood, with an antibody, what we can achieve is a near complete inhibition of the pathway.
This is important because it has been shown by competitors of ours and ourselves that if you start blocking the Activin E pathway, before you see efficacy, before you see an effect, you need to block at least 70% of the pathway. For whatever reason, it's still unclear why siRNA that is liver targeted is leveling out at about 85% inhibition. This is, by the way, true not only for Activin E, but for other targets as well. It seems to be kind of what the siRNA can achieve. It's highly unlikely that if all the action happens between 70% and 100% inhibition, that you suddenly max out your efficacy at 85%. What we believe is this near complete inhibition of the pathway might actually show better efficacy down the road.
It has to be proven. We're preclinical, so I wanna be very clear about this, but that might give us a little bit of a leg up.
Yeah.
That's on the efficacy side. Safety, it's really hard. It's molecule to molecule difference, but obviously, antibodies are a highly validated modality. There's more than 200 approved antibodies, so we know a lot more about antibody safety than we know about siRNA. It's not saying that the siRNA is not safe, but I think the burden of proof is a lot higher on these novel modalities. We've been there with antibodies 25 years ago, and this is what siRNA goes through as well.
Last but not least, what is a little easier is, if you think about the scalability, we have a nonlinear scalability of antibody production. So considering the massive population we're targeting, going from a 200 L batch that allows us to cover phase I versus going to a 20,000 L batch that gets us probably in the commercial scale is a nonlinear, very easy, you know, scale. Whereas siRNA is a synthetic product that at least at the moment still scales linearly. So you double the output, you not have to double the number of synthesizers you're using, and that will be built over time. But as we've seen with peptide shortages recently on the GLP-1 side, it's just something that needs to be built over time.
We hope we can grab a little bit more market share in the beginning. I think there's a clear space in this massive population for siRNA patients that will specifically benefit from siRNA. There will be other patients that specifically benefit from antibodies.
Yep. I hear you. How confident are you with IBIO-610 potentially achieving less frequent dosing? You know, that's something that, you know, everybody's looking forward to see in the obesity space, how are you thinking about it?
All of our antibodies have been really from the start, been designed as subcutaneous molecules and as long-acting molecules, because like you mentioned, complex chronic diseases, we do not wanna add pill burden. The less frequent we can dose, the better it'll be. We have measured the half-life of the activin A antibody of 33.2 days in non-human primates. If we compare this to other half-life extended antibodies, that would suggest a half-life of around 100 days in humans. That gets us into a really, really good position with other antibodies that are dosed twice- a- year. The twice-a-year dosing starts somewhere between 38.5 days human half-life and 50 days human half-life.
I think we're safe, but there's one component we have to first measure in humans before we can make that assessment. This is the reoccurrence of activin A. We know from our rodent studies we can block the pathway 99.6%. The question is if the occurrence rate in humans should be higher, which is unlikely, but there it's a chance that we might have to dose more frequently to get full inhibition. We would still maintain the benefit of deeper inhibition, but it would then be probably quarterly. The molecule, at least what the modeling shows, could be potentially dosed twice- a- year.
Yep. I hear you. Okay. Super interesting. Thinking about some competitor data, you know, they've highlighted meaningful visceral fat reductions and liver fat reductions. I was curious, how do you think that reads through to IBIO-610 and how that platform could evolve?
I think we have just this morning announced our non-human primate data. We started this study before actually human data was there. We knew that the translation from a mouse biology, specifically when it comes to fat tissue to humans, is at best shaky. We wanted to do this non-human primate study to see what actually happens in physiology that's closer to humans. It's a little anticlimactic because now the human data is out and the monkey data shows exactly what we've seen now in humans. I think that even strengthens the read-through that we see from Arrowhead and Wave.
These are really important studies that they're doing, and we're in a, if you will, lucky position because we're learning a lot about where to use activin A, what subpopulations of obesity, but also how to smartly design trials with longer-acting molecules. We believe by knowing and seeing, all the efforts, we might actually be able to catch up. It could just puts us in a good position. We can use part of their basically book, playbook that they used and optimize that for us.
Yep. I hear you. On the topic of your update this morning, what are some of the other main takeaways from the non-human primate data? I noticed you also called out they were on a high caloric diet as well.
Correct.
Anything that we should think about the implications there in terms of extrapolating to human data later on?
The one really big difference this model has to humans is that first of all, they were relatively old non-human primates, and their obesity has been driven and has been kept driving by a very high caloric intake diet. That actually works against the activin A efficacy. In humans, you don't have this extreme overfeeding. Given the fact that we extremely overfed these animals and still saw similar results actually is a quite positive outcome of that study. That was a very complex study. It had multiple arms. It had a rebound study, it had a semaglutide and semaglutide combo arm. All of these data are coming out over the next nine months.
It has been quite complicated to analyze all of that, and we just got the plasma samples shipped back from China to the U.S., now we're starting to do the biomarker work. We have some biopsies, which is interesting. We're very interested in the reduction of inflammation by activin A. That could be an angle that is leading towards protection against cardiovascular disease. All of these biomarkers will help inform our phase IIa studies.
Oh, interesting. If you're able to share, any other biomarkers that you're particularly interested in looking at?
As I mentioned, inflammation. Adipose tissue inflammation has been well established in obese people. We also know if we reduce this in mice, it's a dramatic effect on insulin sensitivity, which could lead towards the Type 2 diabetes field. But we have so far not had a mechanism that would translate from mice to humans because everything we found in a mouse that would be working was either toxic or did not develop in humans. This could be the first mechanism that helps us actually to explore what low-grade inflammation does to our visceral fat.
Yep. I know, I still gonna stay on the competitive landscape for a second, but then we can dig in more. One last question that I think is interesting from investors that I've gotten is just thinking about additional data from competitors looking at higher doses, longer follow-up, et cetera. I mean, is anything that you're watching from these readouts that could have implications to IBIO-610 or may not have implications? Like, help us parse through, like, what should we think about in terms of extrapolating a bit? 'Cause it is, it's not exactly apples to apples.
Yeah. Absolutely correct. What we would love to see as a, as a whole for the field later going on is. What do we see as pathway inhibition at the low dose, at the medium dose, and at the high dose? If we get somewhere between 70% and 85% and can compare this with the efficacy levels, we can then extrapolate what we might be seeing at 100% inhibition. That's going to help us setting the dose for us. That's very interesting. Then, of course, everybody's waiting for weight loss data. I just wanna caution everybody, at the moment, the regulatory path assumes weight loss is the goal. You could lose muscle and lose weight, which would be very unhealthy.
Moving away from just looking at pounds lost towards the tissue that actually makes us sick and reduce that's something we're watching out very carefully. We have to make that case. At the moment, that's not a regulatory path, but the science is about 10 years ahead of the regulatory, you know, developments. That's going to be very important, shaping the future, shaping experiments that help us then define these endpoints and negotiate these endpoints for ultimately different approval.
Yep. On the regulatory front, do you think the FDA and other regulatory agencies could get there, or there could be an evolution of what they're looking for for approval?
I think if we can show that there's real benefit not only for patients but for the entire healthcare system, that will be something that's interesting. Just take the case of Type 2 diabetes for a second. We're spending about $1,000 a day per person in the U.S. on Type 2 diabetes care and treatments. These patients live a relatively long and healthy life considering. In India, you spend about $1 per day in person, and patients die very, very early of Type 2 diabetes and complications. If we can reduce that cost burden by adding an Activin E and, you know, prolonging the onset or kind of pushing out the onset of a Type 2 diabetes, this would be a very easy way to negotiate an endpoint.
Yep. I hear you. Okay. Super interesting. Thinking about, let's say everything works out, you're starting to push forward IBIO-610 into, you know, potentially getting commercialized, et cetera, where do you see that program fitting into the treatment paradigm for obesity, with GLP-1s adjunct or maybe as total monotherapy? Like, what are the possibilities here?
Yeah. let's assume for a second we only have one regulatory pathway, so the 5% weight loss at the end of one year is an approval path. Nobody would take an antibody for 5% weight loss. I think where it would play first and most importantly is a combination with a GLP-1 or an amylin, right? You could reduce the doses of these drugs to a level where patients actually can tolerate them. We know in the real world, GLP-1 weight loss is about 10%, not 20+ like in clinical development. The reason is because patients reduce the dose because they just cannot tolerate that high dose.
If you now add an Activin E and get to the same level of weight loss then compared with a high dose, that would be a huge win, right? We see this as a perfect molecule for combination with GLP-1, specifically given the Arrowhead data, that seems to indicate that fat is being burned, so it's not being pushed from one organ into another. It's really disappearing from the body. Combining a mechanism like this with a mechanism that reduces food intake is complementary and is definitely going to be helpful. Long term, what we believe and if the rodent data holds true, is the biggest unmet medical need we have in obesity right now is weight maintenance. We can go on a diet, we can take a GLP-1 and amylin, we can lose weight.
Problem is you cannot do that for the rest of your life. If it's true and if it holds true what we see in rodents that, you know, twice-a-year dosing could actually prevent weight regain, although there is no approval path for that right now, but that's probably the best value and best use case for a drug like an Activin E if that holds true in humans.
Yep. I hear you. extrapolating a little bit, are there any specific patient populations that you think would be best suited to IBIO-610? Your vision for its profile down the road as you clinically develop it. Let's put it that way.
This is a very great case for me as a scientist. It's a very bad case for my Chief Financial Officer because I keep asking for more and more money. At the moment, what we've learned from Arrowhead, from Wave, and from our monkey study is that, we need to really, you know, strongly consider a MASH population, right? This goes beyond just liver fat. This goes into the fibrosis space. I think Arrowhead has opened that door very wide with a, you know, 40% reduction in liver fat. We can also not ignore the Type 2 diabetic patients. This could be a very dramatic improvement for Type 2 diabetes treatment, on top of GLP-1. If that sensitization, takes care, Type 2 diabetics are resistant to weight loss, are resistant to exercise.
If we can turn that clock back or flip the switch back, if you will, that would be a dramatic change. For 100 years we researched Type 2 diabetes and have not found a disease-modifying drug. That could be the first.
You know, there's other indications like, you know, obviously cardiovascular disease where the genetics of the target point towards. That's why we did the monkey study. We wanna assess some of the cardiovascular biomarkers to maybe pinpoint which indication or comorbidity on top of obesity might be the right population. Last but not least, there is just a tiny or smaller population with obstructive sleep apnea that could benefit actually from fat-specific weight loss because this is actually what's, you know, leading to a large degree to the, to the obstruction. That could be very easily measured and done as a phase IIa study. Of course, now we're talking about five cohorts in phase IIa. At one point it becomes cost prohibitive.
Again, the biomarker work, what we're seeing from Arrowhead and Wave will guide us in that direction. We're hoping not to go down unproductive pathways and unproductive diseases, but also at the same time expand the indication profile for Activin E as well.
Yep. preempted a little bit of my next question. Thinking ahead, so let's say you move into phase I, start to plan for phase II or phase IIa, how would you interrogate these different patient populations? Any sort of design features that you're thinking about in phase II and beyond?
I would definitely say that Arrowhead has provided a blueprint for how to do this well. We would be following that blueprint probably closely, but again, there's always things we can add and that might be important, right? I mean, adding liver fibrosis to the mix is probably not a bad idea. It can be measured non-invasively. Is it an approvable endpoint at this point?
We probably wanna do a liver biopsy at one point, but to just get to a point where we know which indications for phase IIb, which will be long and will be costly, if we can narrow this down with multiple phase IIa studies that can be done quicker, can be done more cost efficiently, I think that's the whole goal, to kind of narrow it down before we actually go and do a year-long phase II study.
Yep. I hear you. Wanted to spend some time asking about the other pipeline programs as well. I know you have myostatin and activin A bispecific. Talk a bit about this bispecific and how does it address these, you know, different pathways and what are some of the intrinsic advantages that you're excited about for this program?
Yeah. Obviously, we have followed very closely what Merck is doing on with Sotatercept, first on pulmonary arterial hypertension, which is a rare disease, but now in a much broader indication, PH-HFpEF, so heart failure with preserved ejection fraction. I think we finally came to the conclusion that this is a multi-organ disease, right? It cannot be treated with just offloading the heart. The SGLT2 inhibitors are doing a great job in reducing mortality, but not attacking the underlying pathology. I think what Sotatercept did is it actually opened very wide that tissue remodeling is what we need to address in these patients. These ligand traps come with difficulties.
These are very hard to engineer molecules. What we see with Sotatercept is it's working, it's almost a miracle drug, but it has the bleeding risk because it actually hits BMP9 and BMP10. There were other companies that set out to improve upon the design and failed. It just shows how complicated it is to do an umbrella approach and then try to engineer certain things out. We take the opposite direction. We actually have identified the components that actually contribute to the disease, and we're building a multispecific antibody against those components, which is myostatin, GDF11, and activin A, which allows us to be way more precise. We believe at least the bleeding risk is taken care of. Again, we have to think about these cohort or Group 2 patients are very sick.
I think one part that we also have to carefully consider is how and who we're gonna enroll in that trial. These are very sick patients. We believe at least on the bleeding side, we can actually eliminate this risk with a bispecific.
Yep. Tagging onto that, you know, what are you thinking about potential future indications? Like, there could be multiple paths you go forward, it could be sarcopenia, obesity, you mentioned PH-HFpEF.
Yeah
... other muscle wasting conditions. Like, how would you make that decision down the road and prioritize different indications?
We are not a rare disease company, and I think this is very, very important because it takes a lot of experience to become a rare disease company. We're a cardiometabolic company. We're happy to partner these programs, one or more, with companies that wanna put them in rare diseases. We believe there's a good use case. It's just, for us, very complicated to add rare diseases to our portfolio. We believe that as obesity will be maturing, we will have subpopulations specifically, you know, in the sarcopenic obesity space. That's 10 million people already where these drugs actually might play a major role. As the market matures, I think there will be alleyways for these drugs to go into certain subpopulations.
Yep, that makes sense. Thinking about IBIO-610. Could you just recap, you know, how are you thinking about that program? What's interesting there that investors need to know as it moves forward?
We're very proud that we're the only company in the world, to our knowledge, that has an antibody against the target. That sets us very nicely apart. The antibody has been developed for high developability, so it expresses really well. It's based on a human. It came from a human naive library, so we've actually engineered high developability and safety in the molecule right from the start. I think that's what really sets it apart given the large population we're targeting. The antibody is, if you will. We know exactly where it binds, so we know a lot about the mechanism, so we have de-risked this as much as we could. We're not gonna share that information publicly because we don't wanna have somebody, you know, reverse engineer the molecule.
I think we have gained a lot of knowledge in that space with that molecule. We have also shown we can advance this really rapidly. We have now completed dose range-finding studies to a very, very high dose in non-human primates without any issues. Not safety studies, just dose range-finding studies. We believe this is a relatively safe path, pathway to inhibit even all the way to 100% from the knowledge we have so far.
Yep. That's super interesting. I know, Martin, you've alluded to this, but maybe to zoom out a little bit, thinking about your drug discovery platform and the AI sort of enabled design that you're thinking about. Could you just, for investors that are newer to the story, just highlight, you know, so how is that backing some of the programs we just talked about?
Yeah. That's a very good question. There's, at the moment, we see a rift or a disconnect between what we consider traditional antibody discovery. These are molecules that are highly polished, highly developable. These are molecules that you would expect to see in clinical development. There's great companies out there, I don't wanna name them, they're all familiar, fantastic antibody companies. There's the newcomers, the in silico companies, and they have, you know, basically opened new target spaces with in silico design. The problem these companies tend to run into, they find binders to the target, but if you need to activate or block the target, that's where they usually fall short. Even if they achieve that, these antibodies are really hard to manufacture, and they don't really look like drugs.
What we've achieved with our AI platform is we actually have connected these two, you know, disrupted ends. We have a part of the platform that really develops novel things. We do have an in silico approach, but we actually cross over the in silico approach with traditional efforts, which actually informs the in silico approach to make more human-looking antibodies, and also we find different antibodies in our existing library that we didn't think would actually be productive. That's on the antibody side. On the antigen side, so you're presenting your target so that you can make an antibody, we've come now, thanks to AI and to, you know, system that is called partial diffusion, we've come to a point where we can make a full receptors, transmembrane receptors, including the transmembrane domain, fully soluble and in an active state.
We have now the tools to screen for the right antibodies. Before that, we didn't even have these tools. We're one of the few companies that actually do both, optimizing antibody and optimizing the antigen. Last but not least, to make this all developable, we have the optimization tool, a mammalian display platform. That platform allows us to, at the same time, optimize several dimensions of the antibody at the same time. Several of them is always developability, expression, aggregation, you know. If they bind to anything else, we can engineer this all out in a single shot. This integration of AI with wet lab biology, I think that sets us apart.
Yep. Super interesting. Maybe I'll give you a little bit of a break, Martin.
Thank you.
I'll ask Felipe a question. Like a big picture question, how are you thinking about the company's cash runway now and how you're prioritizing development here? What do investors need to know about, you know, where you think stand, market cap, things like that?
Thanks for the question. We have cash into first quarter of 2028 calendar year. We are prioritizing Activin E, the bispecific, as well as our myostatin program. With the $26 million that we just raised in January under the PIPE, we are also taking Amylin through CMC in talks, right? That's our goal. In terms of market cap, we have roughly 34.5 million shares outstanding. Our market cap that you see out there is not really accurate because of the raise that we did in August, right? It was very heavily pre-funded warrants. If you include the pre-funded warrants and the outstanding share count, we're around $350 million market cap. Fully diluted, we're closer to $500 million. You know, that's how investors should be viewing iBio.
Yep. I hear you. Thinking about possible partnerships as everything progresses in the preclinical to clinical sort of phase and keep advancing, what are you thinking about either out-licensing, partnering, potentially moving forward as far as you can? Like, what are the options here?
Yeah. I think we have multiple options going forward, right? As Felipe mentioned, we're well capitalized right now, we actually have the chance to move three programs in the clinic. Obviously, we wanna see that clinical development. We believe for our shareholders, the best inflection point is for us to move them in the clinic and partner at one point. If we're considering large indications like obesity, we're looking at phase III trials in the range of $300 million-$800 million. That's a tall order for a small company like us. We're not saying this is impossible, the company would have to grow significantly in market cap to actually get there.
This is why we believe we've created a pipeline that attracts a lot of interest from potential strategic partners that do either have an obesity franchise or wanna get into the obesity space. Hopefully, that'll allow us to partner some of the programs. We never wanna exclude that we can develop these programs ourselves. They're smaller indications. Like I mentioned, if it's an obstructive sleep apnea trial, we can get the drug to approval very likely doing this ourselves. If you consider, you know, the massive obesity population, you know, we're definitely looking for some strategics. Ultimately, it could be a combination. We could partner one program and then, you know, create enough revenue to actually move one of our other programs into the clinic.
I know Felipe has a favorite program, and I hope we can actually keep this and move this forward as far. You can say what it is. But that could be a hybrid way of doing this. Partnerships, we're definitely looking for this. To be honest with you, we're very selective right now because we don't want to partner a program with somebody that doesn't have a track record in the space and doesn't have a track record of actually creating value through partner programs. It can be a little bit tricky. Again, it's all in view of we wanna maximize the benefit for our shareholders here.
Yep. Makes sense. I know we have a couple of minutes left, so last question. What do you see as the most underappreciated part of the iBio story, and why is that?
I'll let Felipe answer that.
When you sent me that question, I was very intrigued, and I thought about it long and hard. I think it's three words. It's people, platform, persistence. They all go hand in hand. From our AP person to our most senior scientist, we have an A+ team. That feeds the platform, and the platform, to me, and Martin and I have said this, we'll put it up against anyone's platform. Lastly, it's the persistence, right? In a scientific field, you should have some attrition, and these guys just do not give up, right? Activin E was a perfect example. Our Amylin molecule is a perfect example. They find ways to uncover the very difficult targets and figure out how to make them work. I think that's what really sets us apart in this space.
Yeah. That's great. Looking forward to more updates. With that, we're basically at time. Just thank you again for coming, and really great discussion. Looking forward.