Q3 2023 OmniAb Inc Earnings Call

Epic time, 11 am eastern time, so we'll kick it off good morning, everyone.

I'm, Matt for CEO of Omni App and I want to thank you all for joining our first research and technology event, we're presenting today.

From Nasdaq's entrepreneurial center.

In downtown San Francisco, which is just a short drive across the Bay bridge.

From our headquarters in our labs over in Emeryville.

It's been just over a year.

Since <unk> became an independent publicly traded company listed on the NASDAQ exchange and I want to thank the NASDAQ team here in San Francisco and back in New York, but especially the team here in San Francisco for hosting us today and furnishing this great space for our event this morning.

But before I begin I'd like to remind you that we'll be making forward looking statements during our presentation. These forward.

Looking statements of course carry risks and uncertainties and actual results may be different from those that are projected so I'd urge investors to please consult todays earnings release.

As well as our SEC filings for more information on these risks so again welcome.

I'm going to provide some opening remarks. This morning, some updates on the business and also give a bit of a road map.

Two today's presentation, but before I do.

I wanted to introduce you to our presenters.

We've got a wider cross section of management I'm excited that investors and analysts get the chance to meet more of our management and leadership team here.

So youll see presentations from <unk>.

Todd Pettingill.

Our VP of business development and strategy towards bid with the Omnia business really since the beginning of forming the foundation of what has now become on Yahoo can play a critical role.

All six of the acquisition of the company and technology acquisitions that we did in a less than a six year period to form what is now the foundation.

The business of Omnia Bill Herman heads our antibody discovery Bill was a founder of Crystal Bioscience, which was the innovator and inventor of omni chicken Bill has had a really illustrious career in antibody discovery space is also the inventor of the gem assay, which is part of our <unk>.

<unk>.

And Bill has the honors of doing the army Dab watch today, and you'll hear more about that as that run through the agenda, Bob Chen runs our discovery system.

Bob joined US when we acquired <unk> Biosciences, Bob was the cofounder of <unk>. He co founded it along with Doctor Jennifer Cochrane.

He also sits on our board of directors.

The <unk> business was spun out of the Stanford School of Engineering and Bob is an inventor of our exploration technology, which has become a key part of our business as well and you will also get to meet them craft, Doug is a well known individual in the scientific circles around ion channels and transport.

<unk> set a long history of first scientific first round, the ion channel and transport space and heads our ion channel and transporter team based out in Durham.

And then you'll also get to meet Curt obviously many of the <unk>.

Investors on the line and analysts know Curt very well.

Curt joined us not long before the split when we split the business often became an independently publicly independent publicly traded company with a long career in biotech and technology longest of which that Amgen for many years heading there European finance operations. So excited that you will get a chance to meet all of these calls.

Leagues, who I'm honored to work with today.

Today's agenda again I'll provide some opening remarks, Todd is going to give an update on <unk>.

Creating value for partners, that's something obviously is very important to us.

And bill will be launching the omni DAP technology today, we'll talk a lot about that get into the science get into where it fits in the industry and why its important Bob will highlight how we enhance discovery with omni beat which is our suite of silicone tools that are woven throughout our technology stack and <unk>.

We'll provide details there and provide some case studies and other <unk>.

Details that we think will be interesting to the investment community and then and then Doug will talk about the ion channel opportunity. Some high value partnerships that we have there and why we see our unlocking the antibody potential in iron channels as an important.

Part of the future and that Kurt will review our financials, obviously, we reported our Q3 financials earlier. This morning, who will review those and also provide some other financial insights into our portfolio of partnerships and our business.

I'm going to start with our mission. We are a mission driven organization. This is what guides us. This is what keeps us focused.

And our mission is to enable the rapid development of innovative therapeutics by pushing the frontiers of drug discovery technologies. We are highly focused on this we're highly committed to this and I think that clarity of mission is one of the things that attracts new partners and also causes a number of our existing partners to expand.

Their use of our platform.

Our business in many ways, it's quite simple, it's a licensing business. So we license our technologies to the industry to allow them to more quickly and efficiently discover antibody based therapeutics.

Our technology offering.

Addresses some of the most critical needs in discovery today.

And we're operating one of the largest greenfields in the pharma industry I will talk more about that in a couple of slides, but the antibody element of an antibody related therapy elements of the industry continue to grow we have a leading and proven technology now with a growing number of partners and a growing number of.

<unk> programs.

And we are committed to continued innovation in what we call intelligent expansion of our technology because of where we sit in the industry. We have a bit of a unique position, where we can have deep technical dialogue with our partners not only understanding where they are today, but where they are headed and that informs how we invest.

In.

And how we innovate around our platform.

So a little bit on an omni app today.

We as I said at the outset, we just passed the one year mark of being an independent publicly traded company.

And we really do feel like all of the pieces in the business are beginning to become a life as we look forward into 2024 and beyond we do feel like we really have a business that is positioned to see if you will going forward that the pieces have come into place and we really do now feel like we have a business that's positioned to saying our work is centered on.

On driving the business on accelerating innovation around the platform and consistently staying ahead of our partners discovery needs were 112 employees across three primary U S sites, our headquarters here in the San Francisco Bay area over in Emeryville.

We have a channel and transporter team in Durham, North Carolina as I mentioned, and then also and in silica team. That's based in Tucson, Arizona and then we've also built up our business development team more broadly and recently established ex U S business development presence as well.

We see the need for only minimal future headcount growth to support substantial growth in our portfolio and our partnerships. There is a lot of leverage in this business a lot of efficiency that's been built in over time.

And we feel like we're really well positioned to take advantage of that leverage.

Spite of macro landscape in the form of tools and technology space that has obviously been widely reported and has been.

Has had a number of headwinds associated with it our business metrics in our business continue to demonstrate the value that our platform brings to the industry. We've had nice growth in new partners nice growth in new programs over the last 24 months, while the industry has been facing substantial headwinds.

We've also seen nice partner program Advancement and announced this morning that we now have five new clinical entrants in this calendar year 2023.

Our work and our technologies are really having an important impact not only on our partners R&D pipelines, but also on patients' lives and this is something that really motivates us and motivates the rigor that we put into the science, how we challenge ourselves to stay ahead of partners' needs, but we're quite proud of the fact.

Where we sit in the industry and it's and it's quite rewarding to see the impacts were starting to have on patients' lives. There are over 170 active or completed clinical trials that are testing on the app derived therapeutics.

That's a testament not only to our partners' commitment and conviction around the antibodies that have been discovered out of our technology, but it also speaks a lot about the impact that we can potentially have on patients' lives and are over 30000 subjects either enrolled or to be enrolled in those trials. We are through three approved.

<unk> derived drugs all of those are in cancer currently and a growing portfolio of clinical programs that I'll touch on a little bit later in this section our business is really designed and funded for continued innovation and intelligent technology expansion, where obviously launching an exciting new technology today.

Omni Dab heavy chain only chicken.

And importantly.

Our innovation engine for either producing new transgenic animals are new elements of our technology is becoming more and more efficient we're able to do it faster we're able to do it more cost effectively and that's something that we I think we will feed well.

Feed the business well into the future.

Our novel or we will watch other novel technologies next year as well.

And we also expect to rollout other new partner experience enhancements as we call them in 2024 and beyond.

So I'm going to step back for a moment and talk a little bit about the antibody market. This is a growing market for a variety of reasons.

Antibodies are projected to have sales of $279 billion by 2025 up from 238 billion last year there were 51.

Blockbuster antibodies. So these are antibodies with sales of over $1 billion in 2022, and the five best selling antibodies had approximately 75 billion of sales last year.

V. The importance of discovery technology focused on antibodies.

Is is is continues to increase for a variety of reasons there've been decades of foundational and basic biology research and scientific advancements that are helping create what what I see is a continuing need.

For cutting edge antibody related discovery technologies, a lot of foundational investment that is driving that present day and future demand really starting all the way back with Nixon's war on cancer back in the 19 seventies and then a number of other scientific advancements that contributed to antibodies.

Becoming a more and more important modality for treating disease. Those include hybridoma cloning, obviously, the human genome project and the advent of proteomics as well as other advancements in immunology and a deeper understanding of immunology, and molecular biology, and higher and higher speed computing all of which drive.

That demand for discovery technology in addition to that.

The industry success rates the success rates that our industry. The pharmaceutical industry has enjoyed over recent years have been far higher for antibodies than traditional small molecule pills that you may put in your mouth. Overall are the historical success rates for antibodies have been roughly double that.

For small molecules when you compare it over the fullness of time. There are also other factors that are driving interest in antibodies the inflation reduction act, which is shifting.

R&D spending of large pharma partners away from small molecules is also driving interest antibodies and then the data on the right hand side in the Blue of this slide is actually very new data. This was just presented a couple of weeks ago.

By the antibody society, who do a very meticulous tracking.

Of antibody success rates for antibodies that are being pursued.

In a therapeutic way by commercial.

Sponsors.

So we find this data one extremely relevant and also very interesting given what it's showing and if you look at it very closely the way the antibody society does this that they're tracking these on an individual basis and you see in the bar charts, moving left to right and there are overlapping periods here because of the way in which they report the data in the.

And which they track the data, but you can see over time that it appears that the industry is also getting better at developing antibody based therapeutics. So not only have the historical success rates have been better than small molecules other macro factors driving investment away from small molecules to antibodies antibody based modalities, but the industry.

Is also getting better at developing antibody based medicines.

Yeah.

So I'm going to talk a little bit about some recent metrics in the business. We've signed eight new license agreements. So far this year, we announced new platform agreements with gig immune and Polaris Therapeutics that we're both signed in Q3 and more recently entered into a new platform license agreement with a global pharma company, a well established global pharma company.

That was also signed recently so our active partner count has grown to 76 as of the end of the quarter and as you can see in the Bar chart. We've continued to grow the number of active partners net of attrition over a number of cycles in the biotech space. We also think theres strength and diversity in the <unk>.

<unk> partners.

And that we are that we are attracting and bringing in and that creates multiple paths to potential value creation.

<unk> stream.

We've also seen nice nice growth and advancement of active programs. We started this year with 291 active programs and.

And we ended Q3 with 314 active programs net of attrition. So you can see that growth reflected on the left hand side in the Bar chart and then in the Pie chart in the right you see that we've had nice growth and diversity as well as our graduation and advancement if you will of programs. So.

We've had a number of programs.

Moved from discovery to preclinical.

We've had five programs move from preclinical to phase one clinical trials and one program moved from a phase III to its first.

International filing I want to note here as well that our definition of preclinical.

Something of a high hurdle, we don't put something in that preclinical slice of the Pie chart.

Unless it is in pre IND studies and the partner is moving towards filing an IND and entering into clinical trials. So that's quite a high bar.

Bar that we use in defining preclinical, but as you see there are 14 programs in that slice.

We've also had growth in active clinical programs, we started off 2023, indicating our expectation publicly that we expected three to five new clinical starts this year and.

And at the end of Q3, we are at thoughts. So we've had five new clinical programs from of Omnia derived antibodies entered the clinic. This year <unk> added by specific immune event.

Entered the clinic with <unk>.

$14, two which is a next generation CRM antagonist. They've also already reported out positive data for that program and indicated this morning. They expect more data for that program before the end of this month.

Gloria entered into its first clinical trial for an anti lag three and then in the third quarter, our Roche entered into the clinic with a bi specific antibody and cessation therapeutics.

Entered into clinical trials with an antibody with a very interesting and important medical use as an anti Sentinel, obviously sentinel a lot of reporting of the medical tragedy and growth in medical need.

Around <unk>.

Preventing a fentanyl overdose and this is a really interesting use of an antibody and thats an issue not only here in the United States is as has been widely reported but also now becoming more of an issue in other countries as well I do want to note here on the Roche program, which entered the clinic in Q3.

That is a program that is subject of a fully paid license that was essentially a grandfathered license that we inherited from a company that we acquired so there are no economics to that program. So I want to be clear about that.

It is further validation of the importance of our technology in in a in a variety of disease spaces. We continue to monitor the progress of the 14 preclinical stage programs as those approach phase one clinical trials as I mentioned on the prior slide.

We have a very high hurdle for what we call preclinical. These are programs that are in pre IND studies that are approaching the clinic.

This next slide is becoming a bit of an eye chart as more and more things enter the clinic.

We are now at 31.

Programs that are either in clinical trials in registration or approved this is becoming harder and harder to read on this slide we are considering other ways.

To reflect our pipeline to investors and the outside World Bull's eye charts, and the like which may be more amenable to showing not only the diversity of partners the growing diversity of.

Therapy areas as we get deeper into the pipeline, but also the progression as well.

And importantly, now as I as I kind of wrap up my section here. We're announcing today that we are launching army that are in and in fact, we've already launched it we have partners now that are already leveraging this newest technology of ours and active programs omni DAP, but simply as a is the first and only.

Transgenic chicken that is producing single domain antibodies and this is a growing important class.

And one that creates a lot of interesting opportunities not only medically and scientifically but for the business as well and bill is going to talk more about that and Todd will also talk about partner perspective around omni depth as well.

And as I wrap up here I, just wanted to talk a little bit about our key areas of focus going forward.

We believe we are well positioned for future growth and we believe we are making an enduring an insignificant impact on human health.

And on the the industry as a whole we feel like as we enter 2024 as I said the business. The pieces are aligning for the business and we feel like its positioned to thing and we're leveraging our highly scalable business where investments in technology and innovation really are informed by deep discovery really.

<unk> with our partners, we have quite all use a nonscientific word and say quite intimate relationships with our partners around not only the challenges that they're facing today and the types of antibodies and antibody based modalities that they they want to pursue but also the challenges that they're facing tomorrow, we're focused on partner pipeline development.

And expansion continued.

Continued what we call workflow versatility initiatives initiatives.

Expanding the reach of our platform.

As well as new technology development and launch it.

At our foundation is a focus on stakeholders, that's a really important part of our foundation.

Proud of the team that we have a fantastic colleagues to work with we have a strong culture, we really do focus on developing hiring and motivating the best employees. We focus all the time on our partners, making sure. We're focused on customer service, we're focused on future needs and that deep collaborative scientific.

Dialog that theyre looking for and of course, you investors as well.

Obviously superior business execution is extremely important to us and we will continue to be committed to that going forward and then we're also committed to leading with integrity and responsibility in the communities in which we operate.

So with that I'm going to introduce Todd who just.

Little bit ago got back from bio Europe, looking fresh and ready to go so Todd welcome.

Good morning, everybody, it's great to be here with you.

I get to speak about a good topic be.

The value that we're creating with our for our partners and what's driving that.

I mentioned, we've had a really.

Good a good run over the past several years of increasing our partner base and especially in the last 24 months, which is especially encouraging due to the in light of the recent market headwinds.

What is driving that.

There are several factors that jumped out at us, but really we have had a good run to improve and increase the platform visibility both through our business development efforts, but also through our partners.

Antibodies into the clinic and also gotten them approved.

We've also.

As Matt mentioned, we put a lot of investment into our business development and marketing presence both increasing the size of the team, but also spending a lot more time at Congresses.

That's really been helpful. As we've been being able to have cutting edge science that we've been back.

Backed us up and made the made the message clear.

Finally, we are able to be creative in how we license we don't take a one size fits all approach with our partners.

Have a range of different contract types and different things that we can work with to make.

To find a deal that works for all of our partners.

With that we're able to attract a diverse set of partners.

Where we're now starting to define our partner base.

A different area because each one has a unique.

Characteristic.

First we have our discovery technology access partners. These are partners, who have full access to the platform for both current and potential program, but also they can develop and commercialize antibody our <unk> derived antibodies.

And that's the majority of our of our partner base next we have the commercial the commercial partners and these are the these are the partners, who have geographic or therapy area rights to commercial and development stage Omnia derived antibody.

They're developing in their commercialized finally, we have our academic partner licensing. These are these are working with academic institutes.

These licenses are designed for revenue share.

We provide the discovery technology platform and the understanding is that theyre going to use this to do proprietary research and spin it out.

Assets for development in commercial lines.

But what's driving the interest from our partners and are using the platform. This is our platform.

This is our tech stack, we like to create it.

Two defined into three separate separate.

Yes, if you will.

Create recruit we help people create a large diverse set of a repertoire of high quality antibodies for select stores.

We have a wide range of transmission and other animals that are that we are considered biological intelligence.

Drive how we create antibodies for our partners next we screen, we have we help our partners screen through millions of potentially.

Potential antibodies to find the right therapeutic we have a high throughput automated version and then we also have Emmanuel version, but also dig deep into the into the repertoire.

Finally, we delivered we help people characterize and select an optimized threat anybody would do that through traditional wet lab work and we also.

Recently incorporated in silicone tools to to expand and build upon the <unk>.

The assets that we provide to our partners.

Well go back to the grid section.

Driven by biological intelligence, what is biological adults, we define biological intelligence says.

Using using mother nature to do what it does best to generate antibodies in vivo. So.

We believe that in vivo generated antibodies are superior because they are generated through an iterative process.

<unk> antibodies and then increases the specificity in.

Select for those with superior develop ability profile.

On top of that our suite of transgenic animals allows us to provide anybody with fully human variable region. So these are not only are these.

Strong antibody candidates, but they don't need to be humanized, they're ready they are.

They've already pass back to you Scott.

That's what we call a biological intelligence and with that we view that this increases the efficiency and the probability of success for our partners to <unk>.

Bring them a lot of different options to potentially go to the clinic.

Now, let's talk about our platform what makes us different.

So we have a.

Multiple technologies that are that make us unique I'll go through them a high level on the first of all we have our chicken.

Our chickens consists of three different technologies, our omni chicken, which is the chicken that makes.

Fully human antibodies.

With that our standards are antibodies.

We have a chicken called omni click that makes human antibodies that have a fixed license that's useful in making by specific than we'd have omni depth, which I won't be too much right now because that's what bill is gonna be speaking about in just a few minutes.

But why is the chicken important really it's an evolutionary just what our last common ancestor with eroded was call. It 90 million years ago, but with the chicken. It was closer to 300 million years ago. So a chicken is that much more different from a from a human and therefore that much more likely to identify an antigen or or targeted non film.

So what that allows is our partners can you use these chickens do identify antibodies that have a broad a broad range of episodes coverage and a wide range of targets.

Next we have a rep. We have two technologies with our we have our omni rat, which is fully full standard.

Bodies, and then we have Ami flick, which are big fly chain.

Body again useful provide specifics.

So why would you use a rep.

Look similar to a mouth, but it actually is different and so it can react to an antigen in a different different wave in the mouth. So you can get a different response, but it has a similar ease of use as well as amounts.

Also our rats bigger so you can get a higher bcl quantity, which can potentially lead to broader diversity.

We are on the right. It was our first technology that was put into operation and we have.

We have multiple approved antibodies from you on me right both in the U S or in the U S and European Union and in Asia.

Next we have our Cal technology, So army tour.

Mixed antibodies that are.

Have you you meet characteristics. They have these ultra long C D R.

Debt.

That almost that stick out from the variable region of an antibody and look almost like a finger that can reach out and accessories best episodes, such as interior of ion channels or different parts of the GPC yards that are normally not acceptable to a standard full length IGT anybody.

So really the omni tour anybody.

Opens up potential new new broad new class of potential targets on the antibody or on the discovery side.

So these ultra long C D ours can be cleavable into a very small fully functioning protein that's about a third the size of an antibody we call. It a pico bot and there you can put a lot of different different functions.

Finally, we have our exploration.

Technology. This is a high throughput be felt screening platform, which.

Which is large has a large amount of throughput over one and a half million you felt was at a time that can screen.

It also uses integrated artificial intelligence and sequencing maximize repertoire minded for.

So these technologies not only are they driving new partners to us, but theyre keeping partners within our ecosystem as they continue to use the innovation that we have.

Do you find new antibody.

This is a quick break down of how our partners are.

Our partners are using the different technologies as you can see on my right. It is leading the pack at the moment, that's largely based on the fact that it was put into operation prior to all the other technologies, but as you can also see the other technologies are becoming a bigger presence and we're moving to be more and more diverse.

From our from our technology usage standpoint.

As far as potential uses for our Omnia have antibodies, there, they're useful or anything that is that could be used.

Anybody can be used for it. So this is the breakdown of what our partners are doing so a lot of mono specific antibodies on their own but also multi specific by specific.

Or more tri specifics.

We also have antibody drug conjugates in our pipeline.

Wide range, but also there is still useful for other technologies car T TCR mimetic things like that.

Anybody's can be useful in a wide range of applications. A bill is going to talk to talk today about omni that and that really opens up a lot.

In a way it blow the roof off of other potential.

Other potential formats that can be used.

With our technology.

So the last slide just as before Bill talks about omni data I'll just talk about why is it important to why it why is it important to a partner or partners are interested because you know.

These are quotes from our partners because they can generate a panel.

Multiple multi specific antibodies.

Using tethered single domain antibody.

Can also rapidly generate high affinity human sequencing from the army on these out.

These molecules can be used to penetrate deeply into solid tumor tumors. They can potentially cross the blood brain barrier and they can also be used as linker to guide other molecules to various parts of the human body.

So after you know will present today, but there are several upcoming presentations, but if you happen to be at I would recommend you joined.

Next week, we'll be in Lisbon at pegs Europe in.

In December we will be in San Diego with it a T conference and then in January 2024 will be presenting a oh.

Our webinar series that deal specifically with all these out.

That's it for me I will now turn it over to Bill.

Thanks, Doug.

So I'm going to take you a bit deeper into the technology behind omni Deb and single domain antibodies.

Let me start first with conventional antibodies in IGT molecule. This is the predominant antibody form and most vertebrate species.

And it consists of two heavy chains into light chains.

Held together by first of all if I bridge.

Pop of the molecule. There's two binding domains that are comprised of a V. H D L.

And then at the bottom the base of the Y. If you will is the FC domain. This is important for serum stability.

Effector function. So that's a conventional antibody no.

Different species will have ultimate forms and in particular are relevant here is.

Kemalist. So this includes camels lamas Packers.

The ultimate form of antibody called the heavy chain only antibody. So just as it sounds this form of antibody is devoid of light chains. It just has a V H domain as its binding entity.

And this is interesting actually because a typical antibody does need a V H N a deal and so the the Lama <unk> had to evolve.

Certain.

Changes in the V H to support stability as a standalone binding element.

And that's actually a really important because that allows a very stable, but small binding entity to exists and in fact.

Researchers have have taken this entity by itself is just this 15 kilovolt sized binding unit.

This compact size just opens up a lot of potential in terms of what kinds of binding molecules you can create with it.

So just to give you a flavor for what can be done here.

You can take these these individual antigen binding scaffold and put them onto a variety of different types of molecules. So on the left hand side of this slide I'm showing where it's been.

FC scaffold so in the Lama.

Obviously, a llama FC domain, but you can actually put a human FC domain or putting your single domain antibodies on the human FC and there you get the benefits of having a human Nazi against a longer serum half life and the effector function.

What's the main benefit of having the single domain antibody there well you can actually control the.

The valence so how many interactions.

Essentially you're able to have with your target antigen and so you could stack. These single domains together to create a.

A variety of most of the other molecules you can actually also put the.

The single domains of different ends of the S C.

Lot of Optionality that you have there to create molecules that have certain performance attributes.

Biological systems.

You can also take two different single domain antibody, so raises different specificities and put them together. So you have a path towards bi specifics of multi specifics. These can be the scaffold, but also.

I see.

But they can also exists sort of on their own as well. So if you look at the middle portion of the slide.

Here we're.

Thinking about taking advantage of the smallness, if you will.

Ultra small sized binding units and this this allows you to create something with activity that you can deliver drugs that can conjugate in single domain antibodies.

<unk>.

A variety of different types of molecules, including radionuclides.

These are very small therapeutic agents or imaging agents that you can the can penetrate deep into tissues and have a variety of uses so you can use as well as modest specifics of single domain units, but you can also tether. These together.

Great attain.

Multi specifics.

Molecules and you can also tell it is to other types of antibodies that single chain antibody and fast.

The point is there's a lot of flexibility just on the on the therapeutic protein side.

And in addition.

These have been found single domain antibodies have been found to be useful for car T where you can actually use the single domain unit as the specifier.

Towards the target and that's linked to T cell signaling.

So theres a lot of a lot of potential there and medicines.

And up a lot of new doors, so to speak.

Alternate routes of administration is an important one so I should mentioned that single domain antibodies are very stable.

Relatively.

Protease resistant so it can be delivered orally or.

Or nasally, so they can actually depending on where.

Where the target is you can deliver these molecules directly to the park.

So that's an advantage in particular this type of compact cameras.

And also related to that is tumor penetration tissue penetration.

And the potential for getting the cross blood brain barrier to live to deliver a therapeutic molecules.

Across that.

For imaging quite quite useful.

Fast clearance rate. So if you don't have an FC we haven't done anything to extend the half life is.

Molecules are cleared very quickly out of the serum so for imaging applications, that's really important because molecules, which are bound to the target can bind there quickly, but then everything else is not bad very quickly creates a very high contrast for me some very ideal molecules without kind of situations.

So overall, there's a lot of broad therapeutic application single domain antibodies to the medicine and its growth.

So let's talk about how as of today. The single domain antibodies have been made whats the process or at least maybe the ones that are in the clinic now or approved drugs, where they may.

And again the single domain antibodies come from from Wamus, So need to immunize alone.

And when you're in Venezuela, you get antibodies.

That's fine, but more ideally for therapeutic use in humans you'd like to have a human based framework.

So a lot of the molecules are in the clinic now.

And then originally from Lama immunization, but they've been humanized humanized really means is you take the frameworks within the V region Theres framework regions in the Ctr reached city or regions are really are the variable sequences, which are determined the specificity of the antibodies to the target.

You can't generally.

Change those too much without operating blind so those usually stay but the framework itself is an important thing that you can change the humans.

However, if you just simply change the Lama frameworks to human.

That particular molecule is not that stable.

And not that.

Developable in a way because it's not really evolved human gene the frameworks are not resolved.

To be expressed on their own they're always paired with <unk>.

So that requires you need to sort of introduce some of these lama sequences back into the human frameworks Gotta reenter the engineer those back in order to have a good developable molecule.

All of this is just a lot of engineering a lot of process and after that initial discovery of the antibody.

And this is where omni down and really streamline the entire process.

So my dad was a transient chicken.

That has.

That's where the human framework, but not.

100% human framework, because we've introduced stabilizing mutations into certain regions that are important that are known to support.

Solubility.

The stability.

The single domain antibody.

And this slide here it is rather busy but we havent pipeline is actual fully human sequence and then just below that where you see the peripheral arrow you can see the positions where we put these stabilizing mutations.

And then below that or all of the clinical molecules, including some that are FDA approved.

And what you can see collectively as those positions, where we've introduced a stabilized mutations are consistent with how these clinical molecules that have actually turned out how they've been engineered after all this effort to come at those sequences of course, the CD ours are highly variable because theyre all different parts of the different antibodies.

But the point is that the <unk>.

Basic scaffold that you want to have in the end.

That's engineered already into the chicken so that means that when you immunize omni Deb chickens, you'll come up with a panel of antibodies.

Have these engineered attributes to them.

So this allows you to get much closer to your final molecule directly from the animals, which basically saves time and decreased risk of things went wrong during the engineering process.

So that's one key benefits pre engineered aspect.

The transition is a key benefit of army deal.

But also.

As Todd mentioned.

And the chicken.

But that's a different animal too.

And one way to understand the advantage here is.

Basically all mammals genetically are more related or closer to each other.

Then they are two birds, let's say.

So if you're talking about reason antibodies.

You really.

Any animal who is responding to a foreign Amazon the degree of foreign degree of difference is important and so within the realm of mammals. There are different because you can make antibodies.

In a mouse to a human.

Rosemary.

Various species, you can get antibodies out but.

They they are not they don't tend to be recognized as foreign within that group of mammals. As if you were to immunize any of those proteins into a bird.

Another way to think about that if you. If you indulge me in a metaphor here, let's say your target of interest as a greenhouse.

And that's different than what the mouse version of this protein is let's say the valves.

Red Oak.

You know you inject the human protein in the mouse the mouse will say, yes, that's different and I'll make some antibodies.

We expect that this happens.

Lots of lots of but assured progress based on that okay. So I'm not saying that doesn't happen. However, you take that same.

Human protein you put it in the chicken.

Yeah right. That's the chicken sees this as a very different protein I mean, there's places all over this this target that the chicken recognizes as different.

And those places on the protein.

Or call it epitopes.

You can talk about epitope diversity, and I'll talk about that some more too, but but that's one of the key things that you can brings is a.

Mission of all these different epitopes and their diverse they are all over the part of interest and this is sort of fundamentally.

The advantage that the chicken brings it and in fact all of our chicken based platforms bring this they're all in a chicken host so it doesn't matter if the omni chicken with a V. H B L antibody as a matter of if it's on the clinic with a common light chain antibody and here and on the debt.

So these are really kind of summarized the two benefits here the chicken host recognition clusters pre engineered engineered ne ne.

Sure of the transient, particularly for single domain antibody.

And just to give you a little data on this this is highlight.

Highlighting both of those things so on the left side, we're looking at process called Epitope. Vinnie. This is looking at the panel of antibodies from from one campaign versus the panel of antibodies from another in this case. The first campaign was performed and omni dad.

In other cases, the campaign performed an omni flip which is a rapid time in my tenure at <unk>.

This process of epitope Binney. It allows it to see where are these antibodies binding and are they different from each other and you can see here, there's a clear delineation towards this target model antigen potent KC 46 that there are some common epitopes to both species it but theres a lot of different ones and the army Dow chicken actually brings a lot of new stuff.

In terms of epitope recognition now.

This can be driven.

But in this case by the chicken evolutionary distance, but then also just the nature of the binding element itself, which is a single domain. It's a smaller territory. That's the parts of bonds epitope.

Other than a conventional ph by V. L antibody, so anyway a lot of it.

The results we've seen so far with army dad, what you can get the sort of unique episodes.

Finally on the develop ability side.

Is pre engineered.

Oh single domain antibodies appear to be very very stable and robust and systems that we use to measure.

This is an important feature for actually making drugs out of some of these molecules.

The types of things you look at our thermal stability as a whole.

Most of things, but one of the very important metric that's looked at his cell.

<unk> interaction.

They call it <unk>.

It's looking at when you take the protein and you put it very high concentration what's a tendency for the aggregate does that that's a problem for manufacturing down the road.

The panel on the right here shows you. Just this is just randomly selected positive binders from omni Dab in showing you the range in this case the low scores better so you're seeing the sin score being quite low for those and as you can compare it to some other molecules on the right are.

They're very high scores those are actually clinical failures.

<unk> had a problem in this area.

But then further to the right you'll see a couple of other approved currently approved.

Antibody drugs, including one which is an engineered.

Emma basically antibody and this metric that those don't score as well as just.

A collection of of antibodies from Omni channel.

So to summarize I'm adaption transiting chickens.

Express an optimized single domain human framework.

Again pre engineered.

Since being a chicken it targets a distinct episodes.

A robust animals, you get a bit tighter as part of the organization.

And you get high quality kind of just specific antibodies.

The developer's ability profile.

Good expression level.

So we think this is a very strong platform for a therapeutic antibody discovery going forward.

A lot of options for partners, especially when you think of this in the context of all the other platforms that we have.

This is a good segue sneak it on that kind of the more.

In silica and screening side of things I'll turn it over to Bob Chen who will tell you about how we've really developed and push the technology on that had to get the very most we can out of the rep towards we generate from our transit attributes.

Yeah.

Hi, everyone I'm excited to be here to talk about how we're enhancing discovery with the army.

In May we launched.

The highlight for our partners with Sweden, physical tools that we have for therapeutic discovery and optimization.

These tools are woven through our technology stack to help us create diverse repertoire to help us screen billions of cells and they help us deliver the right antibody.

Our goal is to use this and silica tools to streamline and assist drug discovery.

We want to make our capabilities ever more efficient and effective for our partners.

On the deepest built on four fundamental pillars.

Based on deep repertoires, Barbara animals, it's based on each screening with proprietary hardware and software.

Based on deep sequencing, which collects in depth information.

And then based on deep learning tools that help us understand this information and make insightful to say.

I wanted to emphasize that the input data Amit.

The deep repertoires that we get from our animals.

These brokered horse are generated by biological intelligence. This is the interplay between rational genetic design and powerful in vivo processes.

For example on this.

Image here. This is an illustration of what revpar. It may look like in three different animal.

They're immunized with different variance of the same target two protein variance of when the generic mutation with either mrna or <unk>.

And you can see that the repertoires book different between this animal and so biological intelligence allows us to create vast and diverse antibody reports within an animal and across animals.

This is a large space that we need to bring unique tools to be able to understand that tap into what we create and here. We can bring the exploration platform. This is our AI driven deep functional screening platform and this platform is built around the strip show up here. So this shift was.

But aside from a palm has $1 $5 million 40 Micron features.

This is a unique through whole formats and in each one of these microcap alerts to perform as they have some thoughts.

Very often we performed binding interactions with fluorescent antibodies.

And then we bring in a suite of various machine learning hit detection models that allow us to automatically look at every single one of b cells and label the targets.

It's of interest.

Once we have a list of cells, we want wanted to recover we use a precise and proprietary laser recovery methods.

Recover themselves very quickly, which our finfet to a single cell bar coding workflows.

Sequencing workflow.

So what we're doing is integrating biological intelligence with AI, we see biological intelligence into these deep screening and sequencing tools, which enable us to have large scale data collection.

All of this information is dumped into proprietary databases, which then feeds into deep learning models, which we stack on top structure based design tools really.

The quality system.

These tools.

Too often this ecosystem will allow us to better mine the diverse workforce that we have.

The biological intelligence of exploration greatest synergy, which generate a large amount of data and only deep is the key to navigate this data and to empower will be called large scale antibody discovery.

To illustrate what I mean is we're going to talk to a case, but in this case that he we immunized re omni slipped animals.

So we screened over 27 million cells that led to over 3000 positive finding events and over 1300 unique sequences and.

Over 124 lineage.

We'd like to visualize Revpar space with this plant here in this part of the top 30 vintages across the <unk>.

What I just mentioned.

And you can see that every one of these spots represents a unique antibody sequences.

Illustrates the scale I wish we deliver to our partners.

Now to go from a large pool of sequences to therapeutic tenants, we need to have a strategy, but we need to make some decisions along the way.

Traditionally you may look at.

Perhaps the linenger's that our box in the squares here there.

Their box because they are likely to be both protein and cell biology.

But now with I mean, if we can apply some in silicon tools intelligently prioritize and select candidates from this large pool.

So how does that work.

Well first we can take the high quality input data exploration hits and perhaps ask.

Hey data affinity value from since the close and we can put in all of the NGF data from the humanized animal.

So we can put in real sequences that exist in the animals and also very high confidence data on a few select close.

We could feed that into deep learning.

Gary also we use the type of model called the variational Otto quoted.

And the goal here is to extend the insight on the phone.

It's to be able to infer the function of untested close.

Essence, the deep learning gives us new suggests a quote to go ask.

For example in this park here in the Middle you can see a green box and highlighted in light Blue are closed our suggested to further test the character.

Before we do so we've we established.

Established one last quality filter, we use a structure based in silicone developer abilities.

This filter and set of tools allow us homology models on any given sequence and that allows us to use a three D and homology models to calculate some developer will be offered.

And therefore, we can use these two very efficiently and cost and time filter out of focus on the most promising candidates.

And so it gives us additional high affinity and highly developed antibody sequence.

So looking back on the spot we can go from the lineages that our box.

Year to feed that into AI and air suggest to focus on maybe some additional quota.

Which are highlighted in the box lineages.

Now we have a systematic way to continue to select antibodies and what they are but it tells us perhaps focus on some rare variance down to the bottom. These are various perhaps we would not have noted look or we have prioritized I guess because of resource, but now we have a way to explore the space and a guide of it Matt.

And so army deep provides new insights specifically these non obvious insights on our immune repertoire for our projects.

So I mean deepest where the power of biological intelligence with AI, we are studying a bed biological intelligence into machine learning, helping us assist in discovery and optimization.

We're offering access to our partners new workflows for examples of large scale discover workflow and also the various optimization tool.

For their existing portfolio.

We are trying to offer and all the best of our in vivo and in Silicon.

And actual results.

Thanks, Bob.

So Bob and Bill just did a great job introducing with some of the innovations that we have in our technology platform, what I'd like to do now is move onto the IHL opportunity that's coming out of the development of those innovations are some really interesting things that we have ongoing.

So for those of you not familiar with the space I'm still walk if you wouldn't know that channel is.

Everyone. I think is familiar with ion Cesar atoms or molecules that are charged sodium potassium what we'd go there are physicians who either.

Chemistries that we measure all these things every cell needs to manage the composition and the concentration of the volumes across the membrane maintain health and they have a normal status and avoid disease and it does that by expressing IHL proteins, primarily on what these proteins are there as shown on the cartoon on the right hand.

The part of the slide that you see.

The Green is the protein and the little Orange circle spirits are the items going through the pieces to go through and you can see on the right hand side I have to go through that one channel and.

It's a big hole and that's channel through the membrane thats, hence the name ion channel proteins for this path.

One when those iron flow through they can they can translate signals that can change a lot of the properties themselves. So the results are very small Curtis and that's what's shown in the animation on the thought on the bottom there you can see that.

Downward blip the flexion, our one protein one on until the opening of the time very very small electrical forthcoming from that.

And we with sophisticated technologies, we can record these skirts and do things.

A lab with them so.

When you look at single proteins, and that's all a function of it's really cool you up here. The science, that's a fun thing to do but why should anybody else care right.

They should care because channel is a really important in both health and disease and they are involved in everything we do everything.

Every function of the body, we pick some examples here to show you on the left.

I can tell is regularly the heartbeat, they regulate movement muscle and nerve function all of our senses vision smell touch gearing.

They are a strong with the eminent biophysicist a researcher in the field are made the statement. When he was received when the Albert Lasker Award. They said I think the iron shovel.

Are the most important single class of proteins that because this doesn't seem to bother anybody for that matter.

Clay, Australia, obviously biased because we worked a lot of channels, but it really is true they're there they're everywhere.

You can always get a lot of physiology of biology and disease by studying these proteins.

And then one of the largest drug classes as a result of that because I don't work.

A lot of things go awry.

We've spent many many years developing what we believe is one of the industry's most experienced several teams of drug discovery expert.

With decades of experience has primarily been apply the small molecule, but now we're leveraging that in the antibody space.

And there is a rich heritage from our staff and our R. R.

Terrific.

Leadership in first in the field as an example, we are we were the first.

To discover.

Selective blockers of a protein called NAV, one eight southern Cal or protein and that's about for those of you are interested in pain therapeutics looking at that space.

There's a lot of buzz about potential opportunities for new drugs coming out about that space targeting this protein there, but other examples where we've actually looked.

Developed technology platforms with our pharma partners are using to enable.

Targeting.

Unique a variance of artichokes in driving our say our program.

We're continuously expanding the platform as well this isn't static.

We are developing custom technologies for cell was high throughput electrophysiology applications like X Ray fluorescence, we use a lot of structural biology, no cryo EM I'll show you a little bit of data from that the molecular dynamics.

So there's a continuous evolution of yard until platform to improve them.

Drive that technology forward.

Validated is in many ways by our pharma partners I love to hear a GSK and Roche, where we have programs in neurological disease and Neurodevelopmental together pieces. So I've got your targets with you.

Global partners.

So.

Where is the opportunity here and is there enough well there really is I wouldn't be standing here.

One of you if there wasn't there a validated IHS targets across the genome, whether they're sodium channel personal travel have been the rich history of neurological disease drugs for the vessel with broad metabolic disease drugs that come out of this space.

But to be fair, it's been challenging it's been difficult often to obtain small molecules that actually will have all of the right properties.

We're making drugs against this target plus.

We've been successful certainly that's supposed to small molecules, but it's been challenging I think for the industry as a whole we believe antibodies to solve this problem.

And I'll tell you why in a moment.

We believe we have some solutions in the space that can really help advance this particular area.

Specifically.

Amit abnormally tour, which both bill and Todd mentioned.

We feel are very unique.

From from our company, our position and coupling through our platform essentially to provide solutions for targeting our children's but.

Now this figure.

I wanted to just go back referenced the first slide I had there was this related to that remember where that should be the cartoon of.

Beyond a shadow of what you see on the left is basically a real structure for a large chunk of it where it is today.

The other way the cryo EM structures run molecular dynamic simulations in the computer and.

<unk>.

Got structural David to help drive our program that's what the read is left slide.

That's a natural protein and the green is the membrane with Barrington. There. If you look in you can see a hole through the middle that support and so that's what if you want to modulate up or down you want to get things into that there's almost for cloverleaf kind of thing around the upside where you can see domains that they control the opening and closing of the <unk> and so that's where we want to get we want to do.

Drive down into those regions due to develop antibody therapeutics for targeting Archibald historically, though vegetable formats for Ala bodies don't do that it's in the by the flat surfaces. So if you need to get down on the membrane and access. These key domain, we need something else, that's where the smaller sizes.

Bill had mentioned in the.

Bob had mentioned about different domains in under Durban Amendment or give us a leg up we feel and allow us to push forward.

And innovate in this space.

So we've been working on this this platform approach in the oilfield area.

Now since the company.

That's about all.

And we've integrated all of these pieces, we have the animal supports business platform that <unk> talked about the proprietary screening technologies those alluded to a number of different platforms and built a Bob showed you that chip, which allows us to screen them at very high capacity.

And we have very sophisticated high throughput technology expert personnel for drug discovery in this space to look at structural functional readouts.

We feel we can apply this platform now in a very meaningful way for ourselves and our partners to drive artichokes drug discovery Biologics and that's exactly what we're doing.

My final slide here is just the tee this up for the Rd community really this is geared towards the scientific folks, but we have a webinar at the end of the month, describing some of our strategies and approaches in this area that could be because of it. So please join the other if you're interested in going deeper into the science of learning a bit more so thank you very much and I'll turn it over to Curt now too.

<unk> finished the formal presentation.

Thanks, Doug.

So today I'm going to start off by talking a little bit about our third quarter financial results.

And then I'll kind of switch gears and talk about some metrics for the broader portfolio.

So let's start with the third quarter results. So.

Total revenue for the third quarter was $5 $5 million compared to $6 9 million in the prior year quarter. We saw an increase in the license and milestone revenue. This quarter that's related to a milestone that we received from <unk> as well as the <unk> program that was partnered with Pfizer.

That increase in the milestone revenue was offset by a decrease on service revenue as a result of our completion of work on certain programs.

The royalty revenue was $500000 this quarter, which was comparable to the prior year period.

But actually showed an uptick relative to where we've been the first couple of quarters of the year.

On the operating expense side, our R&D expense for the third quarter was $13 9 million compared to $13 2 million in the prior year quarter.

The increase was primarily due to higher personnel costs.

And on the G&A side, we also saw an increase in costs up to $8 $5 million that increase was due to head count that we've hired as we become a public company as well as those public company costs. As you go back to Q3 last year, we were not a public company at that point.

The net loss for the quarter was $15 $7 million or <unk> 16 per share.

Moving to our year to date results.

On a year to date basis our.

License and milestone revenue was significantly up from last year. You'll recall. This is primarily due to the recognition of a $10 million milestone that we got from Janssen for the launch of Tech Bali in Europe.

The increases in operating expense for the nine month period ended September 30th are.

Basically the same reasons that I stated for the quarter, we've had head count hiring as we become a public company as well as the public company costs.

<unk> drove that increase.

Net loss for this nine month period was $36 6 million or <unk> 37 per share.

I wanted to drill a little bit deeper into the cost structure and if I move to this next slide and just take a look at our year to date results.

I wanted to highlight.

Something here and that is that a significant portion of our operating expenses are noncash.

So if you look at the nine months ended September 32023, you'll see total operating expenses of $77 6 million.

If you look at the Callout box here on the right, you'll see that between stock based compensation depreciation amortization.

Over $33 million of noncash charge.

Charges. So if you exclude those numbers actually our cash operating expense is closer to $44 million.

When youre doing your evaluation of our metrics.

It's important to understand that net income is not a good proxy for our cash burn based on all of these noncash items that exist in our P&L.

Okay.

Turning to the balance sheet, we ended the quarter with a total of $96 6 million.

This is down $6 $5 million relative to where we were at the end of the second quarter, which was a cash balance of $103 1 million, but still above our prior year end balance.

There really aren't any other changes to speak of for the quarter on the balance sheet.

But as I turnover to the cash guidance.

Matt talked about the fundamental drivers of the business right. So signing new partners that that metric looks good we continue to see it grow in our active programs.

But obviously the industry is facing some headwinds and those headwinds are also affecting various elements of our business.

Earlier in the year, we saw some attrition in clinical programs for the very first time and later in the year, we're starting to see some delays in some of our partner programs.

And as a result, we now expect to end the year with slightly less cash in the balance that we had as of 12 31 2022.

That being said, we still continue to expect that our cash will provide sufficient runway to fund our operations for the foreseeable future.

Okay.

So that that's sort of it for the third quarter I want to kind of transition and talk a little bit about some longer term metrics and maybe drill in a little bit on revenue.

So historically, our total revenue for lack of a better word has been lumpy.

And most of that Lumpiness. If you will has come from milestone and license revenue.

Which is unpredictable based on the timing of our partners achieving various milestones.

Royalty revenue on the other hand, it's been a little bit more consistent but it represents a very small portion of our revenue.

If you take a look at this chart.

It's the part of the Bar chart, that's in Purple and you can almost barely see it.

Now I expect that number to grow but I wouldn't expect it to be meaningful.

Until we see some additional product launches.

From some of our partners.

Service revenue on this line is shown in Blue and that comes from both the ion channel side of the business as well as the work that we do with chicken on the antibody side of the business.

And that work is somewhat more predictable in the short term based on work orders that we've signed.

But it will fluctuate based on the number of programs that we're working on and the types of programs.

That our partners have access to work.

In recent.

History that number has been averaging about $3 million per quarter.

But what I want to what I really want to sort of get into is the milestone revenue here.

So we kind of fast forwarded or take a take a deeper dive on just the milestone and.

License revenue.

That is where we're sort of seeing the lumpiness, if you will and.

And over the last 11 quarters, you've seen the milestone revenue range anywhere from $1 million a quarter, all the way up to $31 million per quarter.

So as you look ahead and think about.

What this revenue could look like going forward I think it's helpful to take a step back and look at where these numbers have been historically.

And the first thing.

I understand is that these tech valley milestones that are shown here in Orange Hashed line.

Are unusual in both their size and frequency.

It's not to say that we wouldn't get milestones like this in the future.

We have a number of janssen programs that are in our clinical pipeline that had the exact same structure right. So those could those could happen again, but this economic structure is a bit rare in our portfolio.

So I think you need to view these payments as more onetime in nature.

So if I exclude <unk> from the calculation and draw regression line on the remaining milestone revenue you'll get this blue line.

It starts at $3 $2 million and has an upward slope that grows up to about $3 $6 million year in this current period.

If you were to include the Tech Bally milestones in this regression line youre going to get a much much steeper line and it wouldn't be consistent with the base level of our business.

So as you think about our license and milestone revenue going forward I think it would be more appropriate to base. Your estimates on something that excludes these technology myself.

So I also wanted to show you some metrics for our total active programs, but before I do that I think it would be helpful to understand a breakdown of our active programs by license type.

The first thing I want to say the most important thing is that 98% of our programs have downstream economics.

There are only five programs out of the 314 programs that are active programs that have what I'm, calling either a grandfathered or a prepaid license right. So only five in all five of those are in clinical development, so they're highly visible programs.

Just to be clear those those are the only five.

The other one that I think is worth mentioning just kind of calling out is the.

Slice of the pie that's shown here in Green, which is the revenue share.

Licensing.

These are mostly from our academic institutions.

Where there is usually not an intent for that academic institutions to take that molecule all the way to commercialization.

So the way. These agreements work is that we will receive a portion or a revenue share of whatever that institution that discovers that molecule gets when they do a sublicense of licenses out to somebody.

So while our percentage of that revenue share as defined upfront in our agreement with them.

Many cases, we don't know what the final economics will be until they do a license with someone else and then we'll be able to understand what our share will be.

So what I'm going to show you in the next couple of slides are the metrics for the vast majority of our our portfolio, which is the standard license shown here in purple and I also have another slide for the ion channels.

So if I.

Take a look at that that purple section of that Pie chart, and we're talking about.

294 of our programs.

And we exclude so this does not include those grandfathered license. It doesn't include the ion channels and I've excluded the revenue share agreements, where the economics are not yet known so that that's the 294 programs that we're talking about and we add up all of the remaining milestones for those programs.

That number is greater than $3 billion.

No. Obviously, we don't expect every single one of those programs to be successful, but I think you'll agree theres a significant opportunity available to us here.

In addition, if you take a look in those 294 programs and take a look at what is the average royalty rate for all of those programs.

Ends up being three 2%.

Yeah.

So if we look at the ion channel programs.

The economics are even higher on a per program basis.

So as Doug mentioned, we have programs ongoing with GSK and Roche.

And the remaining milestones on those programs are approximately $1 billion.

Due to the confidentiality of those agreements I can't give you a sort of the same number that I did for the other programs.

On royalties, but I can tell you that.

There are they are tiered royalties that are higher than the standard antibody platform license that we have.

Okay.

So I hope this provides you a little bit of additional insight.

The economics of our programs.

I hear from you and understand that it can sometimes be difficult to model our business given the lack of information about these early stage programs, but hopefully this information today provides a bit more insight into the value of this pipeline.

That actually will conclude our prepared remarks.

And so we're going to have some time for to answer your questions and I'm going to ask my colleagues to come up here on stage.

Yeah.

Yeah.

And the way this is going to work is that.

If you take a look at your.

Zoom Scream, you should have a place down at the bottom where you can raise your hand.

So if you want to ask a question go ahead and click on that a little button to raise your hand.

And.

That will let us know that you have a question we will try to do our best to take your questions in the order that they come in.

And.

We'll let you know when all sort of announced when you have your line is up there is going to open your line one other thing just to remember.

We're gonna on mute your line, but if you have muted your line on yearend Youll have to mute your line there as well so.

Let's go ahead and will.

Try to get our first question lined up here.

Alright. So the first question is going to come in from Joe Penn genus.

Joe go ahead on mute your line and.

We will be able to hear your question great guys can you hear me.

We can hear you Joe.

Great to see all of you I Hope you had a great trip.

So a couple of topics I'd like to discuss first on the underlying business first Matt you mentioned about looking at minimal head count growth I was just curious if you could provide any more color with that since you have continued to grow your technology bases, so how those sort of reconcile.

Yeah sure. Thanks, Thanks for the question.

Really.

We've come off a year now in this last year or so with with pretty substantial head count grows.

It's been one year since we split off to become an independent publicly traded company and as a result of that.

We added our administrative functions Curt build out his finance team, we added in an internal HR people team and.

And we've leaned into other areas of new science, we've added a new new team members in our screening platform.

As well as on our engineering platforms also have continued to as we have for many years lean into the AI and ml elements of Big data management and other things that Bob highlighted so we've come off a year, where we've added a significant.

<unk> number of fantastic new colleagues, but as we look forward I do see some head count growth, but it's fairly minimal.

In many ways largely because.

The business is highly leverage able right theres an efficiency built into the business around how we work with our partners how they leverage work that we do for them, but we are also the beneficiaries of the fact that our partners.

Have some of their own work streams as well.

So really what is meant by that statement.

Is that we see substantial growth coming.

In terms of new partnerships.

And new programs being added to the portfolio, but expect those can grow at a higher clip than we need to grow our infrastructure and I think that really.

Something about the leverage that we have in the business I don't know Kurt maybe you want to add anything that's absolutely right great. Thanks, and then the second part of the business question is obviously Curt you talked about.

Headwinds in the markets and what have you and you see attrition.

Clients or partners. So obviously, the main reason, which no one should be surprised or clinical trials or strategic needs by your partners I'm curious has any attrition.

The lack or companies that space.

Financing headwinds that are not able to commit the capital that they want to let the design to be able to partner with you.

Let me take that one yeah.

I can add as well.

I'll make a comment and then Kirk and children anything I missed but I you know it.

The first point I'd make Joe is as you look at our metrics over the recent years everything. We report is net of attrition rate. So we report our partners' net of attrition our programs net of attrition and those are all continued to grow even in this I'll say last 24 months period of headwinds in the in the pharmaceutical.

Industry. So we've continued to grow both our partner count and are or are new programs net of attrition.

But we have had some partners who I have I'll say gone away I mean, one that was disclosed was a secret biologics, everyone really interesting science and.

VC funded a few years ago.

But early in the year this year I announced that they were closing closing down actually some of the programs are those those assets actually returns to us and those are ones that could be potential for future partnering events in the future, but I think that's one example, when.

When you talk about bigger partners it's.

It's a little harder to define sometimes we have Kurt referenced.

Our clinical nutrition that.

That we saw early in the year this year.

<unk> clinical attrition was driven by a global Big pharma partner, who was realigning therapy areas decided to get out of inflammation.

As a specific example.

I can't talk about the specific partner, but but that is one of those situations are very hard to define if that is that macro or is that driven internally I think and even even with perfect information and dialogue with our partners. Our best information we can get.

It is a bit hard to to know exactly if something like that is driven by macro factors or simply our business refocusing. So I mean, that's kind of the full answer.

I left anything out.

I mean, I think that's right when somebody says they're going to do a re prioritization is that truly re prioritization or is that a funding issue.

I'm not sure we will know but.

In some ways I'm not sure it really matters to us it's a program that maybe is being delayed or.

Not going to get the economics for us so in some ways it doesn't necessarily matter no absolutely fair and then.

Other topic is and thank you for indulging me, obviously I'm very happy to see the launch of gap today.

I'll keep all the pictures of people getting out of my notes.

Yeah.

So two parts there. So the first part is you know seeing.

Seeing the multi block or building block potential of this it makes me think of other companies say like an anti calin space or what have you where you could come up with a lot of unique structures.

Do you have any early information about the ease or difficulty.

Future manufacturing of these sort of multifaceted.

Structures.

Looking to shrink.

James any experimental data from the DAP program publicly and then lastly can.

Can you talk a little more with regard to debs and their differentiation or more specific epitopes specificity compared to traditional antibody does it change the calculus on clinical applications.

Yeah, Great Great question, Joe I'll, I'll, let I'll, let bill comment on those I will say that the early feedback from partners.

<unk> has been fantastic Todd highlighted some of that in his section, but in terms of them understanding.

The part of the industry the need that that this technology can fill that that that initial feedback has been great. As I mentioned, we already have a couple of partners who have programs that are in progress.

Already in progress of those started here in the in the fourth quarter.

But those are already moving in part, but bill can talk about our.

Disclosure plans, we have a couple of big presentations coming up.

From a scientific conferences and can address your other questions.

Yes, we have.

A few presentations, we're going to go into more depth about the <unk>.

It is with antibodies coming out from the army.

So that'll be next week and pigs, Europe and also in a T in San Diego in December.

And we'll be continuing to talk about this as more data comes out.

We have plans to publish a couple of papers on the topic and.

To ask <unk> to answer your question a bit more specific on the bell mobility, that's something that we've looked at it pretty hard because obviously if you invest as much as we have an engineering of the Trans gene you want to make sure that you've got a good one.

So we've got a lot of good data and its growing.

Which will I think.

Really I would say.

Specify how the how it developed a little these single domain antibodies to come out of our platform are now when it comes to <unk>.

Linking multiple single domain antibodies together as a multi specifics I'll give them to different types of more it is some of that slide that I presented with all the different variations, obviously, we havent checked all of those.

That's too much to do with just for us, but we will be working with our partners on that aspect, but I think at the core of it if you can have.

Very high quality human single domain units, you're in a pretty good position to develop all of these kinds of molecules.

Yeah.

Thank you gentlemen.

Thanks, Joe.

Okay.

Alright, so it looks like the next question is coming in from Puneet go ahead.

Who need and it looks like you've the annuity <unk> go ahead and ask your question.

Yeah. Thanks, guys. Thanks for hosting this hopefully you can hear me well Yep Yep, Okay, great. So you.

First one maybe.

High level on the partner side, and then I won't get into technology question, but.

Bill and Bob.

The team on that so maybe just.

How do you expect the partner mix to sort of change given the funding situation.

It's sort of finally caught up with antibody discovery.

Part of the sector too I mean, you might recall I was asking pretty much every quarter about that but finally, we're here. So now going forward do you expect more collaborations that mean more partnerships with larger pharma.

And maybe just.

Talk to us about that how do you see the evolution in 2024 and I hear comments on the on the revenue side, but I just want to make sure I am.

Conceptualized hearing it correctly.

Yeah Puneet. Thanks for the question and then I'll I'll comment on the partnering landscape and Todd can can can fill in as well.

Sure.

Interesting the last two quarters.

We've disclosed new partnerships with global Big pharma companies.

And and that I think is really a testament to <unk>.

The innovation work.

This team and the team back in our labs are doing.

And also the visibility of the platform at the level of validation around the platform.

It is definitely attracting the big pharma players who understand not only the technologies, we have now and the level of validation work, we put in and into them, but also our intellectual and business and scientific.

Scientific medical commitment to continued innovation I think that that's what's attracting some of those bigger partners, but we are still signing up a smaller partners as well we announced.

Our deal with with gig immune from paying players therapeutics. This last quarter. So we are still seeing some of that.

Which is good that's counterbalanced by some of the examples I gave earlier.

Seeker, and and I'll say, our business development team has been as busy as ever we have a substantially.

We substantially expanded the team has done a great job of bringing in a topnotch I'll say a science.

Ah scientifically trained and and and and our BD team that really leads into the science, because that's something that our partners find a value, but Todd maybe you can offer more color around migration and other things that go in effect.

That sounds good.

There's been a lot of growth in it.

As things.

Evolved it might be helpful to talk to you the sourcing of where these partner leads come in a lot of legs.

That said we do.

We've expanded our business development team significantly and we spent a lot of time at Congresses.

Upcoming theres, some large ones anybody.

In San Diego, that's a great source of leads also we have our marketing team that really is going out in major publications, we've set up a series.

Webinars that drive.

Drive interest and then as Matt already mentioned one of our biggest sources of.

Of new deals is what we call scientific migration.

People that start in one company they get familiar with the technology there and then they move on to another company and they say, hey, I want to keep working with them yet.

That's driving a lot of our current deals. Additionally, it really drive why we're working on.

One of the reasons why we really want to work in the academic space not only are the academics coming up with.

Novel ideas of new things that are interesting cut.

Cutting edge ideas, but also their training the next thing to do next.

Era of scientists and these scientists go to other companies and they are familiar with them you have and then that brings additional deal. So it really deals deals to get deals and we.

So we're doing everything we can to keep pushing that forward, but it's in a lot of ways. It starts to feed on itself.

Got it I appreciate that context, and then just on the.

Type of projects that you're getting.

Obviously, some challenging projects were the early ones that you were receiving in the early days how does you know.

That look now are you getting more sort of routine projects or you know a slew of projects just trying to understand sort of how does that how is it looking in terms of the hum for lack of a better word how are you.

Know how challenging the target is worse situations, where a company might be in funding.

Just facing tougher challenge challenges in the market and then funding situation and they're Offloading. The work to you in order to be more efficient capital wise, maybe just give us a sense of the type of projects Youre getting now versus over the last few years yeah.

Yeah, Puneet, great a great question I'm glad I'm glad you brought it up in some ways.

As we look across our portfolio and it is.

At times, its a bit of a misconception that are our technology or our group of technologies. Our suite of technologies are really suited only for difficult targets. Now there are a number of targets that are hard to attract and and.

That partners come to us for but it is it's really not the case that its really only highly conserved or only difficult targets that that come our way in fact, because of the diversity of species and diversity of platforms and other things, we often see partners who are approaching us for for known.

Targets, you know maybe ones that are I'll call them, a household name type target in the community with which we're talking here.

But theyre looking for a new way to approach right now.

It has never been shown before and our technology is quite amenable to that as well, but we've kind of a broad array of diverse targets across our growing portfolio of programs.

And and that is driven not only by the innovation with the platform, but also on the longer term benefits partners can get not only scientifically, but IP and other things as well I don't know bill or Bob you may want to add any color.

No I think you got most of it I mean, there are those partners, who have a target starting nonconventional theyre very novel, sometimes they're multi P M protein.

Best of luck.

Our protein science capabilities. So we can address those targets. So we're ready for those we engage on those we're happy to do that but at the same time, we do have as Matt mentioned, a lot of partners coming in with very well validated targets, let's call it that and in some cases, they're looking for a next generation antibody it might be.

Something where they simply didn't really benefit from an army dabbs format or even Amit.

Mature type of format.

Looking for a different modality in a sense or in some cases, just wanted to leverage chicken.

Our new epitopes that hasn't been seen before in most of the standard service Center discoveries.

Got it.

Last one if I could ask and thanks for hosting today.

Do you.

How do you see the growth needs.

Any dab in these early stages can you compare and contrast, it to what you saw with omni chicken when you launched it in omni rat.

And then one for just for Bob a quick question.

Brokers invested into our screening platform I'm wondering if that changes.

Anything in the market.

Your view thank you.

Yes, you can.

Well, yeah, well I'll take the Brooklyn winner.

I think you're referring to the broker acquisition of genomics and kind of the.

Formerly beacon.

I speak for the platform.

I think that that is platform, we've known well actually we used to have partners, who do suffer from very well with omni rat in house groups successes with our technology is one that actually I had been worked out for a long time is one that I've kind of lost.

<unk> through from Stanford to accelerate to now.

We have a strong IP portfolio, and we really do things a very unique way because of that ship.

I think we're very proud of kind of our throughput both on specifically screening in the recovery I think Thats illustrated with the case study we talked about is the scaled data, we get out and that.

Exploration here is really a foundational tool to empower not just standard discover which it's been and workflows for our partners now for last few years, but really looking forward as a large scale data collection tool, we hope to talk about it more.

Yeah, Thanks, Bob and I'll I'll I'll add.

To that as well are the exploration instruments, the only exploration instruments that exist anywhere in the world are within our walls. If you will.

And that I think is something that is that our partners value.

And attracts them to us as well to your first question Puneet on.

And comparing and contrasting omni gab versus Ian I'll say the early days of our initial launch of omni chicken or the first launch of omni rat I think the difference now.

One is <unk>.

Just the level of validation around our platform we are.

Leveraging the heritage of the chicken, which now has a program in the clinic and others that are quickly approaching the clinic.

There's a lot more visibility.

For not only our organization, but our technologies really driven by the hard work of these folks on the stage and a number of other folks.

Back in the office.

And around the country.

From a business development perspective from a marketing perspective from a scientific.

An exploratory research perspective, which is something we've leaned a lot more into with some key hires recently, so I think theres a lot more visibility.

And.

I'll say getting the kind of feedback that was high I highlighted and Todd section really leading up to a launch and at the time of the launch. This is inbound feedback from partners. So that that visibility is something that we really haven't had in the past when we've launched a new technology. So for me personally that excites me about the impact that.

Could have and in the ramp up.

We've invested.

And as I said substantially in our infrastructure over the last year.

Year, and a half expanding our capacity for chicken related programs are really in anticipation of this and other downstream innovations and so we feel like we're well positioned and we're excited about the initial feedback we're getting from partners.

Super Thank you guys.

Thanks Puneet.

Alright, it looks like the next question is coming from Steve Willey go ahead and on mute your line Steven will take your questions.

Yes can you guys hear me Okay, yes, we can okay, great. Thanks for doing this.

I know, Kurt and I guess, Matt you guys have spoke to some of the attrition that we're seeing I guess earlier in the year and I think Curt you mentioned.

That you are now starting to see some delays to some of your partnered programs. So just wondering if you could comment a little bit.

The delay side, and I guess, where in the <unk>.

And the trajectory of clinical progress Youre seeing these delays.

Yeah, I'll I'll comment and Kurt can fill in a couple of things going on one.

You know as a programmed approach what we called out preclinical phase, which our hurdle for preclinical is quite high from an industry perspective, we only put something in that preclinical bucket.

If it is in pre IND studies and the partner has confirmed and intend to file an IND.

And go into clinical trials, and I think that's where despite the fact that we started the year.

With.

The expectation of three to five new clinical starts this year and by the end of Q3, we had already reached five so we've seen that that progression that said the mix of programs of those five was different than we anticipated one of which was a roche program exciting from a a medic.

Coal and scientific perspective, but because it was a grandfathered license doesn't carry economics with it.

So the mix has been a little bit different and as we get into the details of those 14 preclinical programs that are really pre IND and are approaching first clinical trials.

There are or I'll.

I will say.

Subtle differences from and what what we mean by delays in different programs right, where maybe there's it's taking more time or they've decided to Ah Ah.

Readjust their manufacturing plants for the first clinical trial that kind of thing. So we've seen some of that with some of the smaller players.

So it's difficult to say, what's exactly driven by macro factors or not but we feel it's best to just be transparent about how we're seeing the pipeline developed we're very excited about the growth in our programs that are approaching the clinic.

But each one has a slightly different I'll say story behind it we did see early in the year as Kurt referenced.

Some therapy area realignment by by a big pharma partner and and that that can either be driven by macro factors or could potentially just being an internal factor as well, it's somewhat difficult to know exactly so hopefully that answers your question.

Yes, it does.

And then maybe just.

As you've kind of rolled out.

Just kind of curious as to what are the applications from partners that youre seeing the most interest in right now I guess is it is it on the radio pharma side I guess, that's what alternatives scaffold.

I think the imaging part that Bill talked about is really interesting is it against.

We can serve targets. We're obviously on the chicken helps us it against these multivalent targets like TNF receptor family members that require this.

This is like in Baltimore, <unk> or whatever to be agonize, just curious as to kind of where the industry interest is right now on the single domain applications, yeah, yeah difficult months to say specifically honestly for the programs that are in progress just for partner confidentiality reason, but.

This is opening new markets for us and in many ways as you say radio pharma.

Blood brain barrier application for antibodies, but.

Bill and Tom maybe you guys can add color.

Yeah.

Radio pharma it definitely is one in certain situations, where an ADC might not be as appropriate.

We get it we get a lot of interest in the single domain antibodies for creating novel multi specifics because that's really a unique thing you could do with them since they're so small you can tether you know two or three or four of them together in various ways.

You can really sort of titrate the amount of focus you have on a particular target. So you could have.

Three two or three single domain antibodies.

One targeting the one against the other so so theres modularity that really is driving a lot of interest. So these new modalities.

That's and that can be applied to them.

You know known targets and in some cases are well established targets that are then being combined with a novel target for example, so all sorts of different combinations, but.

Think that most of what we've seen so far is it's driving on this.

Modularity is most of the specific applications.

Yeah, Theres not a lot I would add on that front you know there's car T.

Car T usage and then delivering.

You know different different particles are just different proteins to different areas of the body.

I would just add though there there really has been a lot of partner interest over the last you know.

Ever since we started making it clear that omni Dab what's available.

If you go to these these scientific conferences you know nano.

Single domain antibodies are all the rage B a lot of people are talking about them. There's a lot of different areas of focus that they can be used in and people really see the value in not only the combination of being able to generate.

A.

It generated an antibody but in the Bennett.

In the ecosystem are you I guess in the ER and the host of the chicken.

Joe can make without people at these congresses as I say, you know I'll I'll look at any Lama in the face and say, we can make a way better than antibody than new cars.

It really is it's just a.

It's just a game changer that we can you know we can do the same format, but in a different species. So it's really getting a lot of attention.

We'll add that to my list of other BD analogies I hadn't heard of yet, but that's good yeah.

Forward looking statements.

Yeah.

And then maybe just one more quick one so I think you've talked before about how partners.

Access to I guess Helicopt menu is on the technology.

So I guess as you rollout some of these new offerings, whether it's on the doubt or on the EBIT do these just show up on the menu.

Of offerings that a partner can choose from or do you think theres an opportunity to maybe kind of carve these out as separate entities increased the economic apps can drive the average royalty rate across the portfolio.

Yeah, Yeah, Steve Great question, an important one and as.

It was kind of generally referenced in my slides and the section in my section of the presentation today.

As we've continued to innovate around the platform as we continue to.

<unk> launched new technologies in general that is I'll say, increasing the value to our stakeholders are rightfully, so and and that.

It's something that we.

We see as having the potential to continue as we launch new technologies each of our agreements are slightly different in some ways in terms of access two types of technologies or structure. If you will of.

Economics are related to various technologies, but the but the spirit of your question is very much aligned to how we think about.

Our innovations from a business perspective, so hopefully.

Hopefully that gives you some color. The reality is each agreement is slightly different but but that is part of our strategy. When we think about launching new tech.

Okay very good thanks for doing this.

Thanks for taking the questions, Yes, I think I get it.

Okay. It looks like our next question is coming in from the shotgun <unk> go ahead and on mute. Your line you should be able to.

Ask your question.

Nissan and I'm still showing.

It looks like your line is still muted on your side.

Yeah.

Let's see you shot can you hear me.

Going once.

I don't see any of it or not.

Alright.

It looks like we're having some problems with that one and that that is our last question. Hello can you hear me Hello.

Yes, hi.

Got you got you.

Yeah.

You may find them on for Robyn.

So.

Matt you shortly interesting statistics that you know.

Regarding antibodies that 40%.

That's really right from phase one to clinic.

With your technology, you said you have more.

It means that you can optimize it and you know.

But in antibodies do you expect this tax to go up with your antibody like do you think you can push this number higher like what are your thoughts on that.

Yeah, Great Great question, Shaun and when we talk about a lot so and and those data that I presented very fresh data presented two weeks ago by the antibody Society, a real credit to Doctor Janus Rankers and her team at the antibody Society, who do a meticulous.

This level of monitoring.

<unk> novel antibodies that entered the clinic and specifically that study was centered around.

Antibodies that entered the clinic that are sponsored by commercial sponsors right. So these are highly relevant to to our business.

And.

It was interesting to see as you look at those kind of overlapping time period bars, just the improvement.

That would imply or based.

Based on those data that the industry is getting better at developing antibody based medicines. It's been known for a long time that antibodies can be more targeted and small molecules and have a number of other scientific benefits, but it was really striking to see those numbers come out a couple of weeks ago.

Now as you as you relate that to us as.

As we look at our portfolio.

We have not seen them I'll say clinical failures in our clinical portfolio.

Portfolio.

I I say that you know, noting that we are in a in a business in the pharmaceutical industry, where things out of course, but it is interesting to say, but it but at this point you know with with 31 programs either in the clinic, a commercial or in registration or dataset, it's probably still too early but our success rates thus far.

Ben had been great and I think that is something that.

Validates our technology with partners attract new partners, but it's probably too early or our dataset might be a little too small right now to say how it relates to those new numbers that Janice and her team from the antibody Society reported but we are excited to see that we feel great about the work that our partner.

<unk> are doing the substantial investment into clinical development to have now over 170 clinical trials and our partners are sponsoring that are based on antibody based medicines I think says a lot about their conviction.

Around the molecules that have come out of our tech.

Great.

Thanks for the color I mean, along those similar lines.

What percent of your programs do you see like advancing from preclinical to clinical I mean, do you have that going into those statistics.

How many programs are like you know advanced to kind of like 101.

I don't believe we've disclosed that in the yeah in the recent past, but it's a you know in many ways as you look at that preclinical slice, which again is really more pre I M. D. As I as I said earlier its E. We've found as we look at the you know the programs that have advanced to the clinic.

And that are in preclinical that that so far in our in.

In our pipeline it has not been a matter of if but when and in many ways right that we've had very little attrition in that preclinical pre IMD slice of the of the portfolio pie.

But there can be a lot of variability in time in that place in that space right, whether it's manufacturing or designing the first clinical trial or.

Other other elements that lead up to an I M D.

It's really just been more a matter of when and not if and I and I think that says a lot about the technology and and also the high bar that we place on putting things in that our preclinical bucket.

Great and then last one so from.

From what I see Kona, because it's not.

No large molecule that you haven't clinic snowmobile molecules target like same target like likely you have couple of them you have like actually D. C. D C.

Which are more developed using Amit.

So one other depression differentiation of this molecule.

I mean, I believe the data from San Juan.

One of the differentiations in this market.

I'll provide some thoughts on that.

Yeah, and I'll I'll I'll, just speak generally about the business the way we structure our licenses and then bill can can add color there.

Without talking about specific partners antibodies to specific targets I'll say, we do have a number of partners who are pursuing the same targets maybe for the same indications or maybe for different indications.

Both with omni app derived antibodies, but those will be different on the app derived antibodies for reasons that bill Bill can describe.

And the way generally restructure our license agreements is that they are open to any target partners can pursue any target they want to pursue the one exception to that can be in the ion channel and transport space, where the economics are far greater as Kurt described on a per program basis, and that's because we're also Oh I'll say.

Committing to a a a target space linked to our assays and other things for those programs.

But bill maybe you can offer some color on kind of how that plays out with different antibody.

Yeah, I mean, one of the things that.

We were able to offer our partners and our animal systems as large diverse repertoires to any given target.

And those repertoire as our particular for that target for that partner, meaning that when you're immunizing omni chicken you got a certain repertoire and even a six different army chickens, you've got six different repertoires.

And we're very good in our screening to go through those and identify the best of those but even if another partner comes along would that same target.

We'll set up I mean, not that same cohort of chicken is a different cohort of omni chicken and we'll get six new regulatory and when my nose and we've we've found especially as we incorporate more and more of these bioinformatics tools that allows us to look at a lot of sequences that really we don't get overlaps. So we're quite confident that mark.

Molecules that come out of a campaign, even if it's the same target will not be the same sequences for two different partners and we continue to look at this and monitor it because obviously as we do more and more programs.

<unk> go up but we still are not really worried about that I don't know Bob maybe you want to add on that.

I think actually we can say that we can re insurers with our bioinformatics that we do not view different sequences to tutor partner. So all the IP is always going to be separate.

I think it's maybe the appreciation of the repertoire space, it's like tend to like it tremendously large so I think just imagining that it's just statistically unlikely it's not impossible for them to be overlap and I think also the differentiation is really driven by our partners right. They sometimes give different target product profiles to us that we kind of bashing.

I'm, sorry, I was going to be different as our partners provide their needs.

Hey, guys. Thanks, a lot Brian Thanks Pablo.

Informative.

Alright, Thank you Sean yeah. Thanks.

So so Kurt tells me we have we have no further questions of course, many talents I've I've learned that he also can be a conference call operator.

He did a great job Kurt.

But anyway I want to thank all of you for joining thanks for the engagement and.

And questions.

Really appreciate our investor.

<unk> and and and input Kurt and I will be out on the road will be back in New York City next week at the Stifel Conference as well as the Craig Hallum Capital Conference as well will be out on the road and I just want to finish the program by thanking my colleagues for their presentations today in their input thanking our team.

Back in the office and also thinking our our hosts here at the NASDAQ Entrepreneurial center in San Francisco for furnishing this great space for for the event. So thank you all again and have a great day.

Goodbye.