Please welcome to the stage CFO of OmniAb, Kurt Gustafson. Excuse me, Kurt Gustafson.
Thank you very much. I guess I will be doing an advertisement for Coca-Cola here. You, me, all of us in this room, we all have immune systems. Our immune systems have evolved over hundreds of millions of years, and our immune systems are designed to keep us safe from foreign things that come into our body. Think about a virus, cancer cell, even a piece of pollen. Some sort of foreign substance that comes into your body. Our immune systems are designed to go fight off that foreign substance, kill it or get rid of it, and remove it out of the body. At OmniAb, we have designed transgenic animals where we have swapped out the genes of those animals so that our animals actually have a human immune system.
In response to some sort of foreign threat, that cancer cell or virus or whatever, our animals will produce antibodies to go fight that threat. But the antibodies they produce aren't mouse or rat antibodies, they're actually fully human antibodies because of the way that we've adjusted out the genes of these animals. Big biotech companies and pharmaceutical companies come to us to get access to our technology to go discover drugs. Our business model is we let them use our technology and we take a piece of the action. They'll take a license from us to get access to our technology, and in return, they'll pay us milestones and royalties to the extent they identify something that they move forward. That's the essence of what OmniAb is, and let me now go into a few details here.
Before I begin, just a reminder, I'll make certain forward-looking statements. Those are outlined in our SEC documents. As I mentioned, what we have are these transgenic animals that produce fully human antibodies. We pair that with novel screening technology because once these animals produce these antibodies, we have to screen them. We have something that we call the power of BI and AI. BI is the iological intelligence that's built into our animals. The immune systems of these animals that actually can go figure out what's foreign and develop antibodies to go create that's the biological intelligence of our engine. Then we pair that with some proprietary screening technology that uses artificial intelligence to find the antibodies that those animals produce that go after the antibodies of interest.
We have what we feel is the best of both worlds, the power of BI and AI put together. We've got 110 partners using this technology. We're working with some of the major pharmaceutical companies in the world. Those companies have developed 425 different programs that are currently under active development. That's a net number we'll talk a little bit more about. If you add up all the milestones of those 425 programs, they add up to more than $3 billion with an average royalty rate of 3.4%. I'll talk a little bit more about the xPloration. xPloration is an instrument that we designed to go screen all of these antibodies, and we've had some partners recently come to us and say, "Hey, we might be interested in buying one of those." That's a new business opportunity that we've just launched.
At the end of the day, this is a licensing model. We do not develop drugs. We help partners find drugs. They come to us to take a license to our technology. In return, we will get paid an upfront fee. They may hire us to do research work for them. But the real sort of meat of the economics are as they take a molecule and move it into the clinic, they will pay us milestones, and hopefully eventually royalties if that drug is commercialized. Here is kind of a snapshot of the technology that we have. On the far left here, we have sort of the creation of the antibody. Here are all of our different transgenic animals that we have. We've got mice, rats, and chickens, you see that up on the top, that create fully human antibodies.
We actually have animals that can produce bispecific antibodies, so these are antibodies that can connect to two different things. That is OmniClic and OmniFlic. This will sound a little bit out of science fiction, but we have actually developed animals that can produce very unique shaped antibodies. OmniDab and OmniUltra are examples of some of those. Just as an example, OmniDab comes from a llama where llamas actually make really unique antibodies. They are single-domain antibodies, thus the dAb name, but they are much smaller than regular antibodies. We have actually designed a chicken that will produce a llama-like antibody with a fully human sequence. We have a bunch of rockstar geneticists at our company that have designed all of these animals, and these antibodies are used for very specific reasons.
OmniDab, for example, because the dAb is so much smaller than a regular antibody, think about diseases that are in your brain where a regular antibody would not cross the blood-brain barrier. OmniDab, given its small size, these dAbs can cross the blood-brain barrier. We have had renewed interest in sort of the technology platform from a number of neuro players once we launch this technology. I thought I would put together this diagram of just sort of how this technology kind of works from a workflow standpoint.
So, let's say you are a pharmaceutical company, you have interest in treating prostate cancer and your idea is , if I can hit this prostate cancer cell in this specific way, this specific receptor, but not this part, but kind of a little bit over here, we will work with you to design an antigen or the thing that we are going to give to our animal that sort of mimics that target that you are after. Usually it is a strand of RNA or a protein, and we will give that to one of our animals. Our animals will produce millions and millions and millions of antibodies, right? Some of them will be against that target that you want, but the animal is going to be producing millions of antibodies to all kinds of things.
We then use our proprietary screening technology, which is this xPloration machine that you see on the lower right-hand side. This instrument, in the span of an afternoon, can sort through millions of cells and figure out which of those antibodies are directed against the target that you want using a number of our artificial intelligence algorithms. You end up with all of these antibodies that are then targeted against your specific target. Eventually, you'll sort of decide which of those antibodies becomes the one that I want to take into the clinic and hopefully become a drug. That is kind of the workflow that we have. As I mentioned, we've been at this a while, so we've got 110 partners using this technology. These numbers continue to grow. These numbers are also net of attrition.
Sometimes these companies fail or whatever, and so these numbers can kind of grow and come down a little bit. But we're working with eight of the top 10 pharma companies, and you see the list of names here, kind of the who's who on the big pharma and biotech list. We've got 425 active programs. Once again, this is a net number, right. This business is a business where most stuff actually fails, and so we're constantly adding new programs. Certain things are failing and coming out, and so we always track our numbers net in terms of what is actually being currently developed, and that's 425 as of the end of June 30th. The other metric that we track is the number of programs in clinical development.
This is an important metric for us because as I mentioned, our licensing model, where we really start getting some more bigger economics is when things move into the clinic, right. So, they start triggering milestones. We currently have 34 drugs that are in the clinic. If you were to kind of add up the milestones or the remaining milestones associated with those 34 drugs, it would add up to about $340 million. So, there's a lot of money just in this later stage of development. Here's a snapshot of our pipeline, or I should say our partner pipeline. I want to highlight maybe just a couple of drugs on this that I think are exciting and our partners are clearly excited about. The first one is kind of there in the purple color there, called IMVT-1402. This is an asset being developed by Immunovant.
It's an FcRn, and they're going after five or six different indications. They've had some good data this year in difficult-to-treat RA. Next year, they will have the readout of their pivotal programs in myasthenia gravis and Graves' disease. Assuming those are successful, people think they will file next year. Most analysts have this drug launching in 2028. If I were to pull up the analyst reports for Immunovant and look at the consensus revenue estimate, the consensus view is this drug will be a $3 billion drug at peak sales. So, this is a big drug going after a big market and pivotal data not too far away. So, we'll see that data at some point next year. The other one I'll highlight just because they've had some really nice data this year, which is in phase II, the top one there, TEV-408.
They're going after the disease of celiac disease as well as vitiligo. They've reported out data from both of those indications earlier this year, and this drug looks amazing. It's an IL-15. The initial results look amazing. Teva said that they think this is a $2.5 billion drug. We'll see more data from these programs next year. Based on the results that they saw in these first two indications, they're actually now going to be going after certain types of dermatitis as well as alopecia. So, almost a pipeline and a product for that one as well. Obviously a lot of other drugs. We had a few of these this year. The ramantamig at J&J went straight from a phase I to a phase III this year. We've been seeing some very nice progress from our partners in recent months.
We've got a lot more data coming. These are the clinical data readouts over the next 15 months from those various partner programs. There will be a steady drumbeat of clinical data that's coming out over the next coming months on products that are part of this pipeline. I mentioned a little bit about xPloration, which is our screening platform that can screen millions and millions of cells in the span of a very short period of time. We use this for our own workflow to go screen the antibodies that come out of our animals. A few of our partners came to us and said, "Hey, could we get one of those?" We did some additional development on the instrument, and last year we started making it available to partners.
This year we did some market research on this area and realized that this B-cell screening area is about a $500 million market. We've just started selling these instruments. They're expensive instruments. They sell for $500,000 a piece. In addition to selling the instrument, there are also single-use consumables that get used every time that the instrument is run. You see on the right-hand side, there's these chips that the cells go into and plates where they recover them. Those have to be used every time you run the instrument, so it becomes a little bit of the razor blade model, where not only do we make a nice margin on the instrument, we make some really nice margins on the consumables that they continue to have to go buy. The instrument is pretty amazing.
In that chip, they can put about 1.5 million cells. We put all of the antibodies that come from our animals in that. They'll also put the antigen or the target that you're looking for. What happens is if the antibody is the right antibody and it binds to that target cell, it glows, and a camera will take pictures of this, and our AI systems analyze which of these cells are actually glowing the way that we want them to, and then a laser automatically goes up, and it hits and releases the surface tension and drops that antibody into a plate. A person doesn't even touch this. They load the plate. They stick it in, and the instrument actually does all of the work. What they end up is a plate full of these antibodies that they might want to go do.
When we do a campaign for folks, we go from millions of antibodies to what we commit to providing to a partner, which is, say, 100- 200 hits, which are antibodies that have the sequences that bind to the target that they want. We do that in terms of just the screening part, we do that in about a day. Just a quick snapshot of our financials, and I will focus on the column that is second from the far right, just our year-to-date financials. The type of revenue that we are bringing in today, just given the evolution of the company, it is mostly milestone-based. You see there the milestones being the biggest part of our revenue. We also earn service revenue to the extent that the partner asks us to go do some work for them. You see that in that next line.
xPloration, this is that instrument I talked about. We just started selling those, but sales are ramping, and I think this could be a meaningful part of our revenue story here in the next few years. We had an Analyst Day a couple of weeks ago, and we said we expect that we would, sales for this program would be about $2 million-$3 million this year and would double in 2027 and then double again in 2028. It is still early days, but things are looking really promising for selling that instrument. Finally, the line item that we hope will be growing here pretty soon, which is the royalty revenue. Right now, we have got these couple of drugs that are approved. They are only selling in China, so they are only kicking off about $1 million a year.
That is the line item that I think will be growing pretty dramatically once we have some of these next products hit. It is a highly scalable business model. If you think about our operating expenses, our R&D expense is really focused on keeping our animal colonies alive and developing some of these new technologies. It is almost rather fixed in nature. I am not saying it is not going to go up. It will go up with inflation and those types of things, but we do not have to grow this business or our operating expense as the business grows. We can add another 30 partners, we can add another 50, 100 programs, and we do not have to grow our operating expense to do that.
I like to say our animals do all of the hard work, but we spend a certain amount of money to keep that infrastructure alive, and then we leverage that going forward. As revenues will grow, you will not see that corresponding increase on the operating expense side. On the balance sheet, we started the year $54 million in cash. We were at $52 million as of June 30th. Let me just move to our guidance. This year, we expect revenue to be somewhere between $32 million and $36 million. We give guidance on both a GAAP operating expense standpoint as well as cash. OmniAb was formed from a series of acquisitions, so we have a lot of amortization of intangibles, and so we find it helpful to provide people what our cash operating expense is. That just removes that amortization of intangibles and stock comp.
Our cash use this year, we are getting pretty close to break even. As I said, we started the year $54 million. We are at $52 million at the end of June 30th. That's about where we would expect to end the year. The company is well-capitalized from that standpoint. I am going to maybe just say one other thing around the business thesis of this. I have been in biotech for about 30 years, and a lot of biotech companies are focused on developing a therapeutic. If you are at a small biotech company, you maybe have funding to discover and develop one or two drugs. If those drugs work, it is amazing. It is going to be great. The challenge with this industry is most things fail. Our business model is a little bit different. We play the odds here in terms of it is shots on goal.
I like to say I would rather own 3.4%, our average royalty rate, I would rather own 3.4% of 400 things than 100% of one or two things that probably do not work. We have a very diversified business model in terms of the play in the antibody discovery area. We are working with the largest pharma and biotech companies that know how to develop drugs. Folks like Pfizer and Amgen and J&J. Those are the people that are moving our programs forward. This is a really nice way to play, get exposure to the biotech industry and the life science industry without taking that binary risk that you typically do with a biotech company. I am going to pause right there and see if there are any questions from the audience. Yes, sir.
I am trying to understand when you are negotiating royalties with pharma, how do they look at this from a. Is there a lot of variability or is it very homogenous in the royalty space generally? What do those negotiations look like?
Yeah, so the question is if when we are doing the negotiation for one of these licenses, what does that look like? How do you guys agree to the royalty rate and whatever? I would say this, when somebody approaches us and we send a term sheet out, that term sheet is the same every time we send it out. So, the starting point is the same, and it gets negotiated from there. I am going to generalize this, but this is kind of typically what I see. Pharmaceutical companies are very focused on keeping the royalty rate down. They are willing to pay some more money up front, but they want that royalty rate down. When we are talking to a small biotech company, it is completely the opposite dynamic. Like, "We do not want to pay anything now.
We're willing to give you a big number on the back end, but we don't want to pay anything now." We have a risk-adjusted NPV that we're trying to get to, and so we can play around with that front end and back end, if you will, and adjust it if we can get back to that risk-adjusted NPV. Somebody wants that royalty rate down, well, guess what? Your phase I, phase II, phase III milestones are going to be higher. That's how that negotiation works, and so every deal is different. It doesn't vary a lot. We talk about our average royalty being 3.4%. It's not like some are 15% and some are 0.1%. It's a couple of percentage points is sort of where you get 95% of these deals are in that zone.
But yeah, it's a negotiation, and we can be flexible on that, and it's just a function of what are their pain points and what are they trying to solve for, and it gets negotiated from there.
[audio distortion]
Yeah.
How do you look at the world of Royalty Pharma and the people that buy those royalties and what they're paying for them? I haven't kept up to date with it, but what's your view of that space, and would that [audio distortion]
Yeah, the question is how do we look at Royalty Pharma and what they're doing, and maybe would we consider. Is the question if we would consider selling a royalty to one of these guys?
Yeah.
In some ways, we're kind of similar in terms of our business model. We're a royalty company trying to generate royalties. The difference is we invest in this core technology, and we'll spend, like I said, maybe $30 million in R&D a year, and that spins out 60, 70, 80 new programs or potential royalty-bearing assets every year. That's kind of our investment. These other royalty companies, they end up having to go out and they want to buy a royalty, they go out and spend $200 million to go buy that royalty. It's the same sort at the end of the day in terms of us trying to get royalties, but sort of the approach in terms of how we get them is different.
In terms of whether or not we would consider selling a royalty, that's not part of how we're thinking about the business today. As we go out and speak to our investors, the royalties are really what I think a lot of the investors are sort of looking for. That's why they're investing in OmniAb. Like, what are those royalties going to be? I think if we were to sell that, it's like kind of getting rid of the goose that's laying the golden egg. We want to be able to retain that. Now, that being said, there could be a price for anything. If somebody approaches us, we listen. Meetings like this, we'll have royalty players come and sit at the table and talk to us about wanting to buy a royalty. We're not really interested in that.
We even actually have partners come to us and say, "Hey, we'd like to buy the royalty back from you for this program." When we hear that, it actually makes us want to hold onto the royalty even more because they have way better information than I do in terms of where they think this program is going to be. So, in those types of situations, the information arbitrage or asymmetry is really big, and so we want to hold onto that. The company is well-capitalized. We don't need to go after capital, and so we'd rather kind of sit and wait and harvest those royalties when they come in. That's the strategy, if you will, for now.
[audio distortion]
The question is how do I feel about the marketplace here, and are people overpaying or underpaying for that? I would rather not comment on those. I am sure some they are getting cheap, and some are expensive, and it all depends. I would say my one comment is this space is becoming more and more crowded with the number of players that are doing this, and the cost of capital for these guys in some cases is pretty low. I have seen over the last few years these players get more and more aggressive in terms of how they are bidding for royalties, so I would probably just leave my comments there. All right, I think we are almost at time, so I want to thank you for your time. Thanks for coming and your interest in OmniAb, and please feel free to reach out if any of you have further questions. Thank you.