Bullfrog AI Holdings, Inc. (BFRG) Earnings Call Transcript & Summary

Good day, and welcome to the iAccess Alpha Virtual Best Ideas Fall Investment Conference 2026. Our next presenting company is BullFrog AI Holdings. [Operator Instructions] I would now like to turn the floor over to today's host, Vininder Singh, Founder, Chairman and CEO of BullFrog AI Holdings. Please.

Thank you. Good afternoon, everybody. Great to be with you today. We are BullFrog AI. We are an AI machine learning for drug discovery and development company, really exciting space. I'll let you take a few seconds here to read our forward-looking statements. Okay. So the reason BullFrog AI exists is because there are big problems in the pharmaceutical industry. And you may or may not know that a lot of money is spent. The success rates are incredibly low. The timelines are incredibly long. And what ends up happening is all of this leads to very high health care costs that we all face as we age. And there is an urgent need really for custom solutions for drug discovery and development. I think the world and then especially our market is getting much smarter about AI, and we're realizing that there's no one-size-fits-all solution, okay? You have to have the right tools for the right problem. And that's exactly what we are designed to do for the pharmaceutical industry. So everybody wants to know why should we invest in BullFrog? Well, here are some highlights. We have a proprietary tech stack. The core of it comes from Johns Hopkins University Applied Physics Lab, which is a world-renowned research institution. We have strategic partnerships that are enabling us to get access to one-of-a-kind data sets so that we can make discoveries. As we all know, in AI, it's not just the technology. The data is as important, if not more important. We are and have been actively engaging big pharma to secure commercial deals. And by doing that, that's validation for our company. Several months back, we did announce our first top 5 pharma deal in the neuropsychiatric space. Very excited about it, and I'll talk more in the future slides. And after that announcement, we were able to raise quite a bit of money to take us well into next year. And that event also led to some other great things for the company from an operational perspective. But relative to others in our sector, we're incredibly lean, and we have been for a long time, very, very disciplined with our resources, just waiting for the right moment and that moment has come. So at the end of the day, we are a life sciences intelligence company. What we are doing is probably the most difficult and complex application of AI. We are dealing with biological systems and biological systems are complicated. There are lots of variables, millions of variables, and there are still things we don't know about biological systems. So this is a very big challenge, but our tools are designed for this challenge. And as I mentioned earlier, a big part of our solution comes from the Johns Hopkins Applied Physics Lab. So our technology that came from there is an award-winning technology that they spent many years developing. So as I mentioned, data is critical in this industry. And the amount of data is growing pretty rapidly, and that's good because with more data, higher quality data, insights and discoveries can be made. And the key here is the quality of the data, the type of data. The data that we generally work with is incredibly rich, and it's the type of data that you really need if you want to make a difference and make a dent in these long-life cycles and high failure rates. And the other thing is, especially when it comes to multi-omics data, the cost to generate that data has come down substantially, like orders of magnitude. And that's, I think, what's opening the door to amazing discoveries that are happening now and will continue to happen, and we think that will accelerate. And BullFrog is right in the middle of all of that. So we have a proprietary tech stack. There are 3 components to it. There's data preparation, which we can do with any type of data set, big or small, shallow, wide, complex, clinical data, early-stage discovery data. And within hours or days, we can clean, harmonize and structure that data where it would ordinarily take many months for a whole team to do it. Then we have our proprietary analytics engine called bfLEAP, and that's where we make all the discoveries. And finally, earlier this year, we launched bfARENAS. This is our AI decision support tool. So with AI, you get predictions and recommendations, which is great. But with what we do, it's explainable. But then the question is, well, what do you do with all those recommendations and predictions? How do you know what to move forward with? And that's what our bfARENAS tool does. So this proprietary tech stack is now being further developed into what we're calling the BullFrog operating system. And our goal is to make this an enterprise-grade solution that any companies in the biotech or pharma world to plug into their existing enterprise solutions and extract incredible value. I mentioned earlier about our first big pharma agreement. This was a feasibility study for major depressive disorder, which is a very big market. At the end of the day, we are going to deliver a target to them that they will then bring in-house and advance through their drug discovery process. So this project started approximately mid- to late April, I believe. And we've executed extremely well. We've had [Technical Difficulty]. Sorry about that loss of connection. So with the Eleison Pharmaceuticals, we were able to discover a biomarker associated with threefold increase in survival for pancreatic cancer patients. So that was a huge discovery, not only for us, but for Eleison and for patients. So they effectively now have a formula for being successful. And I think patients have hope that they could have a solution to a horrible, horrible disease. I mentioned earlier that we have a relationship, which provides us access to the world's largest neuropsychiatric brain tissue repository. We had exclusive access for a 1-year period to the data, and we've made a number of really important discoveries in major depressive disorder, schizophrenia and bipolar disorder. And obviously, that has led to our first commercial engagement with big pharma around major depressive disorder. And this is really exciting because we've discovered a number of targets that we believe are the drivers of those diseases. So this relationship with this top 5 pharma is just one of many opportunities we have, okay? We want to repeat everything we're doing with this particular pharma, but in a bigger way for schizophrenia and bipolar. So we think we can do several deals here. And so anyway, that's really important. Getting the first one done, the first deals, they're always going to be these feasibility studies, pilot studies. And that's effectively big pharma's way of doing their due diligence. And like I said earlier, we're performing really well. So this is going to really help get us on the map, okay? We're going to get on everybody's radar now. That said, we have other big pharmas in our pipeline, okay? So things are really starting to move. So as I just said, I mean, there's multiple opportunities for us to partner. We have this tech stack. We can provide that tech stack to companies in the industry, either one or more components of that tech stack. And like I said, that's going to move into the BullFrog operating system enterprise solution, and that's coming relatively soon. And that's really going to be our ARR side of the business, okay? Our goal is to build that up, and there's a substantial pipeline already for that, build that up and that we will make BullFrog profitable on its own. And then we have these strategic partnership opportunities around the discoveries we've made. So you would layer that on top of our BullFrog operating system revenue, and you got a really exciting combination. I want to add that earlier in the year, when we got the pharma deal secured, we brought in a bunch of cash. I was able to hire a leadership team, and I'll introduce them on a slide here in a minute. And we were also able to hire about 10 people, okay? So we now -- we have a win, a big win, and we're going to go in that direction hard, okay? And these 10 people are equally split between commercial people and technical people. So now we have a full commercial team building a pipeline, marketing our solutions. And in a short period of time, we're seeing the effects and it's all very positive and very exciting, and that's what's going to drive us to become a profitable company, hopefully, next year. Now we have plans to further expand the team. We're going to do it in a stepwise fashion. This first group has to get the results we need. We've got to get to our BullFrog operating system and other solutions. We got to build that pipeline and then convert and close deals and start ramping the revenue, expand the pharma relationship and get more of those and expand those. Land and expand is a big strategy for us. We think we can build a very substantial business inside any one big pharma because they have huge R&D portfolios. And anecdotally -- well, not anecdotally, even from this one pharma partner, we're being told they can't do what we can do. They don't have our technology. And we're not sitting still. We're continuing to innovate, continuously innovating, okay? We are in the AI machine learning innovator category, okay? We're not simply an applications company. So we're really, really excited. We're driving. We have momentum. I expect things to hit in Q4 and then building into Q1 and beyond. I mentioned earlier, we have a very, very experienced leadership team. Everybody on this slide has at least 30 years of experience and have accomplished great things in their careers. And what this gives me and the team, the company is a leadership team with a very deep toolbox, okay, that knows how to navigate things and take advantage of opportunities and address risks. And these are things you got to think about early, and we're doing that. So we are in very good hands, and I'm really excited because it took us some time to get to this point. And these guys are driving things right now, and it's -- we're seeing the results. The AI pharma relationship model has had multiple versions, I'll say, over the past 10 or so years. First, they were doing lots of deals. Big pharma is doing all kinds of deals with AI companies left and right, and we were all reading and hearing about them. Then pharma started building their own teams. That had mixed results, in some cases, bad results. Then pharma -- now more recently, pharma started to make some acquisitions, and they're trying to link up with big tech. So we'll see what happens there. And then you have the big, large language model companies. And they are getting aggressive. They're looking to make acquisitions. Of note is Anthropic's acquisition of Coefficient AI, which is a small company, no products, no technology, just about 10 people, and they were acquired for $400 million. So interesting times. This is not something we're focused on. My focus is continue to execute and build the company, and we'll let the rest take care of itself. So again, just to reinforce the point here, when you're looking at a company like BullFrog AI, a bunch of things are going to jump out. But I think the most important things are, number one, we're in a very hot space, okay? AI, life sciences, white hot. Two, we have proprietary technology, and we don't think anybody can do what we can do in some cases. Three, we are a lean company. We continue to be lean. There are many companies in our sector that burn hundreds of millions of dollars a year, and we've taken a different approach, and we are driving toward hopefully becoming a profitable company. This is an inflection point for sure for the company. There's no question. You got the pharma deal. You -- we're building the team. We've more than doubled the size of the team, but we're still relatively lean. Pipeline is growing. So all the arrows are pointing in the right direction. And that's it. Thank you very much. I guess we'll move over to questions now.

With the recent advancements in your bfLEAP platform, what is the current timeline or strategy for announcing major commercial biopharma or clinical co-development partnerships this year? Well, I mentioned earlier, my goal is to expand the current relationship in Q4 with additional expansion in Q1 and bring in a couple more deals in Q4 and build from there. How are you seeing internal validation metrics improve as you integrate larger multi-omics data sets into the AI analytics? Well, look, the better-quality data that we have coming in, the richer the data, the better the insights. I mean that's the relationship that's always existed. What is your current cash runway outlook given the recent scaling of operations? So we think we're in good shape until probably at least the middle of next year. It was originally late next year, but we've obviously hired a bunch of people. But look, our goal is to be a self-sustaining company. We don't want to go back to the capital markets. We have some existing vehicles in place. As you may or may not know, we have an ATM, ELOC. We have warrants -- clean warrants at $2 and $4. So there are some existing vehicles there. We'll see what happens. In timing, when do you expect the next AI selected candidate to enter IND-enabling or clinical development? Well, remember, that's really not what we are focused on. We partner with companies currently. So that's not for the immediate future for us. Can you update investors on active discussions with pharma and what milestones would trigger a formal partnership announcement? Well, as I mentioned, you have to perform in these feasibility studies, and we are performing. So we're -- I mean, they're happy, we're happy, but that's really the key here. I also think being able to reveal the name of this company is going to lead to a whole host of other opportunities for us because I think the market is going to say, look, this big pharma -- I mean, this is effectively their diligence process. And especially if we go to an expansion, that's a big check mark, and everybody will be paying attention to that. Okay. Another question is, which revenue path do you see as the most realistic near-term: platform licensing, joint development or internal drug advancement? Internal drug advancement, I will put that last. We are already effectively in joint development, right? We're discovering a target for this top 5 pharma, and they're going to bring it in-house. And related to that, I don't think any big pharma is going to be interested in just one target. So I think that's another big opportunity for us. They're going to probably want several targets. That's typically how these deals are done. And once you get through the feasibility stage, you move to standard deal terms. And those are the types of deal terms that will transform big way. This platform licensing, what we'll call BullFrog OS, like I said, we do have a bunch of those opportunities in our pipeline. And we're going to convert on those. They take a little bit of time. And then we'll move to BullFrog operating system, enterprise, and then we're going to be able to really scale the business in a big way. So that's -- those -- that's coming soon. That's -- you're looking at 1 to 2 quarters away for the first version of it. And I think that's all the questions we have. Okay. We have some more. We have a few more minutes here. What would represent a successful outcome from the current top 5 pharma? Well, I think we are already showing some success. But like I said, the end result, what they want is a single target for major depressive disorder that they can then bring in-house and advance through their discovery process, okay? And that's -- that will be the conclusion of this project, but that's still a few months away. But the fact that we can talk now about expanding this relationship says something. What are you seeing in terms of interest from other large pharmaceutical companies? We do have other large pharma in our pipeline. And I think, look, success leads to more success. So again, this ability to announce an expansion, more are going to come in. But we're also very active on the marketing side. We are going to be exhibiting and sponsoring some conferences, giving presentations, panels, very, very active in the fall around all of that. Which parts of the platform generating the strongest commercial interest today? Well, obviously, this combination of our tech with this proprietary one-of-a-kind data is attracting a lot of interest because that's a very powerful combination and neuropsychiatric drug discovery and development has always been a very challenging space. What differentiates bfLEAP from other AI platforms? I get asked this a lot. I mean, look, what we have is not what the big tech companies are offering. It comes from Johns Hopkins Applied Physics Lab. But the real answer is our ability to be successful is what's going to separate us. That will speak for itself. Then you know our technology is better. And I think we're at the end of our time. Okay. Thank you. Bye.

That concludes BullFrog AI Holdings presentation. You may now disconnect.