Aptamer Group (LSE:APTA) — Interim Results

0:00 Good afternoon, and welcome to the APTAMER GROUP PLC investor presentation. Throughout this recorded presentation, investors will be in listen only mode. Questions are encouraged and could be submitted at any time via the q and a tab situated on the right hand corner of your screen. Simply type in your questions and press send. The company may not be in a position to answer every question it receives during the meeting itself. However, the company can review all questions submitted today and publish responses where it's appropriate to do so. Before we begin, I'd like to submit the following poll. I'd now like to hand you over to doctor Aaron Tolley, CEO. Good afternoon, sir. Good afternoon. Thank you.

0:32 So thank you for taking the time to listen to our results, for the six months to the 12/31/2025. I'll just skip through the obligatory disclaimer slides before coming on to introduction. So I'll just introduce myself first. So I'm Aaron. I'm cofounder of APTAMER GROUP. Founded the company in 2008. I have a PhD in structural biology and biophysics. And for my sins, I've run the company for, the past fifteen or sixteen years. Good afternoon, everybody. I'm Andrew Rappson, CFO at APTAMER GROUP. I have over twenty years experience now as a chartered accountant. Joined APTAMER in August 22, and I've been CFO since August 23. And I've worked in the AIM environment now for, just over ten years.

1:22 Okay. So I thought we'd start with a a quick brief overview for those people who are not familiar with the company. So we're a small biotech based in The UK. We have a global reputation for developing our version of APTAMER, which are optimist through our proprietary high throughput automated selection platform. The founders, David Bunker and myself, we've spent the last fifteen years building this automated platform, which we believe outperforms other similar platforms in the market.

1:51 We essentially provide a service making what's referred to as affinity ligands that can be used in a variety of different areas in the life sciences market, particularly where antibodies are not suitable or cannot interact with certain challenging targets, and that will become important a bit later in the presentation. We have a leading position in this alternative affinity ligand market, meaning that we have worked with almost all of the top 20 pharma companies providing solutions with our antibody alternative platform. So as a company, we've built this high throughput, high capacity discovery engine. We we've also integrated in house assay development so that we can increase validation and also on-site manufacturing that that helps us support our customers, particularly important, when we license products and we need to we need to manufacture them for that purpose.

2:43 As I've said, as a company, we deliver binders for challenging targets where customers have previously failed with antibodies, generally speaking. And our and our platform has many key technical advantages compared to antibodies in for several high value niche areas. We're recognized as a key player in the industry. We've got relationships with 85% of the top 20 pharma companies as well as with other blue chip companies like Unilever.

3:09 Many of the businesses that we work with have run multiple discovery projects with us, showing the need for the technology and a and an interest in hitting these targets that are beyond those that are possible with antibodies and small molecules or other similar formats. We've continued to grow the platform for from a reset basis a few years ago with fee for service revenue increased 40% on last year, and we've managed to increase revenue over the last half year by 27%. The the model for the business is to essentially retain intellectual property on the discovered optimists and build recurring revenues through the layering on of licensing. And this year, I'm pleased to report that we've received our first royalty income from commercially launched products. And I think on this slide, I'd really like to emphasize three main points. Firstly, the technology advantages that the platform has, things like intracellular delivery, low immunogenicity, which is important if the molecules were to be used as a therapeutic, scalable manufacturing, which is obviously important if you need to make lots of the molecule to fulfill orders.

4:11 And it just it just makes the platform attractive to pharma for several for for several different reasons, and in particular, in several high value areas. We've got good commercial traction, 85% of the top 20 pharma companies, multiple repeat business contracts, and we have multiple revenue streams from fee for service all the way through to licensing, giving us clear visibility, of revenues moving forward over the next few years. So at this point, I'll pass over to Andrew to cover the financials and to give you an operational update. Thanks, Aaron. Yes. So I'll now take us through the financial review, and, we'll start with the income statement and cash flow. So revenue for the period was naught 830,000, so that was up 27% on the prior period. This was all fee for service revenue, driven by some strong contract signing through October and November, where we had several several notable contract signings with top pharma customers.

5:09 The strength of the contract closing has resulted in a £2,000,000 signed deals in fee for service order book for the period. From this, we've recognized 830,000 in revenue, and we usually expect about 70% of this to ultimately come through from the pipeline to be recognized in the P and L as revenue, and we'd expect that to be through before the end of this financial year. Further to this, as we updated in the trading update, we closed the period with a sales pipeline of 3,100,000, and certainly we'd expect some of that to close and add to our revenue before the end of this financial year. We executed two licensing deals in December 25, but these didn't contribute revenue during the period.

5:55 These licenses will start generating revenue in the second half of the financial year. We've continued to keep the admin expenses under control, and have reported 1,500,000, which is on par with the 1,500,000 reported in the prior period. The headcount remained relatively stable at 30 employees versus 31 at the start of the period. Contained within admin expenses are r and d costs of 200,000, which again is consistent with the prior period. These costs include costs associated with progression of our internal fibrotic liver delivery program, where we have generated excellent preclinical data being non toxic, stable and non immunogenic. This gives us good data to continue discussions with pharma partner with regards to licensing, although progression through animal work, should be the real value inflection point for this asset.

6:45 There's a small amount of other operating income which relates to subletting of some office space. The comparative is slightly higher because it includes grant income for a project undertaken with Eurostars, which finished in the last financial year. So overall, this gave us an EBITDA loss of 1,000,000 for the period, so a slight improvement of the 1,100,000 reported in prior period. On to the cash flow, the net cash outflow from operations was 1,200,000, which largely reflects the £1,000,000 EBITDA loss for the period. The working capital outflow was 200,000 and this was caused by increased debtors from contracts signing late in the period, work being commenced and then not paid until after the period end. We had the same scenario in prior results to December 24 as well. So often when we're contracting with large pharma, we take extended credit periods, which can be anything up to ninety days in the longest cases.

7:42 During this financial period, had one contract with a large pharma on ninety days, and the other large pharma contracts were on seventy five day terms. Smaller customers are typically on thirty day terms. In July, we raised 1,800,000 net of expenses, and in August 100,000 was raised from the exercise of warrants. This resulted in 500,000 increase in cash in the period, and a balance of 1,500,000 at the end of the period. So if we move on to the balance sheet, the net assets at the period end were 2,300,000 compared to 1,400,000. The strength in the balance sheet being a result of the equity raise in July, contributing that 1,800,000 net of expenses.

8:28 Placing took place at 0.3p, being a 50% uplift from the placing twelve months earlier, which was done at 0.2. Cash at the end of the period, as I mentioned, is 1,500,000. That provides a working capital runway through to the second quarter of twenty twenty seven. This working capital runway being a function of continued fee for service work and starting to generate cash receipts from the two licensing deals that were signed in December 25. Notable items on the balance sheet are mainly the debtors, which are significantly higher than June. As mentioned, we signed several contracts through October, November and into December on seventy five day and ninety day payment terms. So, the work commenced in the period. We recognized revenue in the period, but payments on on many of those fell into January, February, March, following the period end.

9:19 The tax receivable of 200,000, of that 0.15, relates to prior financial year r and d tax credit, and we received the cash on that in February post period end. If we look then onto the operational review. So in terms of fee for service contracts, we had a number of important fee for service contract wins during the period. The first of those was a top three pharma partner contract in the radioligand therapy market, totaling 360,000. This contract has significant potential, and is an area of need where our technology appears to be well suited. This top three partner is already significantly invested into this therapeutic program, making it a critical project for them, and one that we believe could progress quickly as a valuable therapeutic asset.

10:11 We also signed £769,000 worth of new contracts with the same top five pharma partner, mostly across November and December. This gave us a strong finish to the period, but was in a good position for H2. And we received the target proteins during December, so we're able to recognize revenue in respect to the first phase of that project in the period. This top five pharma partner has now conducted several projects with us over the last few years, and exceeds £1,000,000 in total contract value. So, great validation of the value that they see in the technology. Other contract mentions, there's more repeat business with one top ten and one top 20 pharmaceutical company, again following successful projects that we delivered in the prior financial year.

11:01 And then just two other projects that are worth mentioning on this list here. Envisius, that's a potential therapeutic complement for autoimmune diseases, and plays on the fact APTAMER is a non immunogenic. And then an announcement we made with, Matea. So that platform has proved, to work with APTAMERs with high detection levels, which is ideally suited for detection of cryptosporidium in water.

11:26 This one is an important environmental testing platform, and that's potential to reduce huge outbreaks as we all saw widely reported in the Southwest last September. And then we look forward to updating on these and any of the other projects here, as they start to pass through the lab. I'll just move on to the strategic process and start with the licensing. This was probably the real highlight for us in the period. We signed two licensing deals in December 25, one with Twist Bioscience and one with AlphaZyme. AlphaZyme being a subsidiary of Maravai Life Sciences, so two large US customers. These contracts include a mix of upfronts, royalties and supply revenues.

12:13 So we see this as a significant step forward for us. This is the first time that we've licensed products that have been developed for a customer, and they're going into an end use application in a commercial setting almost immediately. So since the period end, both customers have submitted orders for these products, and we look forward to seeing how they how they perform. We've also got a second project with AlphaZyme that's also progressing very well, having delivered working binders to the customer for testing during the period, and having received positive results, following those tests in their hands. And then we've also in this same space got a global enzyme manufacturer assessing several of our inhibitor binders with a view to licensing. So a real step forward on the licensing front for us during these six months.

12:59 In terms of development, the fibrotic liver delivery, showed excellent preclinical characteristics, so that's de risking its therapeutic potential. From here we're looking to complete animal work, which is the major barrier really to unlocking licensing opportunities with this asset. The project with Unilever continued to progress. It's now passed through safety, stability, and it's currently post period now moved to the on skin testing phase. We supplied a large batch of material to Unilever just last month in February, and, that's for them to be able to conduct their on skin trials. And we have an IHC reagent with a global life science conglomerate. We've developed a working binder for this project, and agreed licensing terms early.

13:47 This asset is in the process of being passed over to the customer for further development and validation, with a view to reaching market towards the end of this calendar year. And then finally, just on investment in manufacturing. In order to be able to meet the needs of the global partners for the enzyme modulators that we've licensed, needed to develop our internal processes in terms of capability and quality. We're now in a position where we have the processes in place, and we would like to be able to increase the capacity as those licensing opportunities grow.

14:24 So I'll just move on to the next slide. So here, we have a selection of the assets, that we've developed over the last eighteen months. And so laid out in order of value verticals across the the top. Sorry, yeah, laid out in value verticals across the top and with the stage of progression laid out down the left hand side. At the top we have the fee for service pool of opportunities, and from that successful projects feed down into one of the verticals shown here as reagents, diagnostics, vaccines, cosmetics, and therapeutics. To date, we've primarily generated assets in the reagents space, as I've just been touching on with Twist and AlphaZyme.

15:11 And we've licensed assets that are starting to generate passive income. So we focused in these areas, and the technology, really the areas that technology lends itself to, and now it's proving that it can be adopted in a commercial setting. So these reagents combined with our existing fee for service work have the potential to cover cover our operating costs alone. As a team, we've focused on passive income because it allows us to generate more predictable revenues and then layer on with new assets. Some of the higher value assets take longer to get to market, and so it's important for us to have a mix of asset opportunities so we can start generating passive income to contribute to those costs. And so eighteen months ago, we shifted the focus of the company from that fee for service work to asset generation.

15:58 And in that time, we've now tripled the size of the asset portfolio. And those assets are are beginning to shift from customer validation to licensing agreements as we've seen with AlphaZyme and Twist. So with both of them signing in in December, both now submitting orders and have launched products on the market. They've both got them on their websites. And those based on those orders and forecasts that they provided to us, we can see potential on each individual asset of circa 400,000 per annum in revenue contribution to help go towards covering our costs. We've now got a second project that's moved well with AlphaZyme. I expect that to be a similar scale in nature. And that's approaching a point where it's very close to licensing. Indeed, AlphaZyme have confirmed they would like to take it forward.

16:50 And we've got two further companies, at the top of the list listed as global enzyme manufacturer. We've got, yeah, a global enzyme manufacturer and a UK based company now both evaluating this technology with a view to licensing. So overall, this vertical appears to be developing very well. And while we focus broadly, in line with our fee for service work, our highest value assets lie within the therapeutic sector. And this is what we want to double down on to increase shareholder value for the future. So the opportunity with the top three pharma, they have an urgent need, and as they've progressed with their current projects and our technology could provide a solution, this could give us a relatively near term access to a therapeutic offering.

17:37 And we'll take, and we'll be taken forward, at pace, we believe, with the top three pharma partner. The radioligand therapy market is particularly high value and top three partner is heavily invested in this particular project. So we see this as a really key opportunity for us, an opportunity for real value. Also in that therapeutic space, I've mentioned the fibrotic liver delivery, so that's progressed really well. But the critical need here is to get the animal work. We've got a number of partners who are wanting to see that as a proof point to be able to take this forward and really unlock the value that's in that technology. In between those two verticals, we've got the diagnostics. The really interesting one here for us is the fetal diagnostic test. So that was developed previously in previous financial year, sorry. This is currently at the evaluation stage with a global partner.

18:30 Again, this could unlock some real value. The technology here prevents the need for an amniocentesis test during pregnancy by testing the pregnant mother's blood. This technology would allow diagnosis of genetic conditions at an earlier stage with less risk, than under the current process. So yeah, this technology has received good feedback so far. Like I say, it's currently under evaluation and, yeah, we look forward to seeing how that progresses. The other major one now on the cosmetics, as we've mentioned, is Unilever, which is progressing well. It's got to the on skin testing phase. We've supplied a large batch of material and they're currently conducting their trials.

19:16 So the asset portfolio has more than tripled to 14 assets in the last eighteen months. And so we feel there's a real good opportunity here to unlock more shareholder value, with any of these coming through, outside of the reagents that we've already been licensing, could really add transformational value to the company. So in summary, there's a number of assets that have developed and are increasing. The passive revenue generating licensing has started and we're predicting that to grow. And the success with any of the larger assets could be transformational for us and include upfronts and significant recurring royalties. So yes, the portfolio is built really well, and we're excited by the opportunities that we see in it. I'll now pass over to Aaron to take us through the post period highlights.

20:16 Thank you, Andrew. Just let me move the slides on to the post period end. So I'd like to I'd like to start really with a recap on what we set out to do with the 2,000,000 that we raised in July 25. So this was to support asset negotiation, invest in manufacturing, begin the development of AIML development program, and now advance our liver fibrosis siRNA delivery platform. So in order, what have we actually done?

20:45 So we've completed two licensing deals that could generate over 1,000,000 in passive income over the next few years based on supplier forecasts of three nonexclusive licensing deals. We're in the process of closing that third one, as Andrew just alluded to. We have two other companies evaluating this technology under MTA with a view to generating further passive income. It's, you know, it's not beyond the wit of man to see that these could potentially cover all overheads in due course for us as a business, and this is just, like, a handful of the potential assets that we've got. We've invested in manufacturing capability to fulfill these orders, and we've delivered against them. And when you contextualize all of these numbers with our growing fee for service pipeline, it paints a more derisked picture and real progress for the company. So we we've also undertaken more work in the s r and a delivery space, extending the work that we've done on liver fibrosis to fibrosis in general, looking at applications in kidney and lung and other potential areas. And we're ready to put these conjugates into animal models. And this work will be started shortly after the fundraise completion and does not use, any of the new funds for the liver work. This is still largely funded after the 2,000,000 set out in July 2025.

22:00 We've planned our AIML model and started collating the data. We've evaluated and done extensive due diligence on how to enter this space. It's taken almost a year to build the plan and recruit the right person. I'm pleased to report that he'll be starting with us in a couple of days and has a PhD in machine learning in DNA protein interactions, which is the underpinning technology of our platform. We've also built on the radiopharmaceutical deal with the top three pharma company, and we started to build our own data packs in this space to demonstrate and derisk the technology platform that we're developing. And the first data pack we alluded to in an r n s previously shows better payload stability than peptides or protein comparators that we've evaluated, and this is a key differentiator for this technology.

22:49 We've also built around this concept, a relationship with an expert, Louis, who's recently been featured in a BBC report, and he he will be managing our development of our radioligand program and the animal model work. So this brings me on to the fundraise. How much? Why now? You had funding until 2027. I know there'll be many questions which we'll come on to later. But before we get to that, I'd really like to cover what we raised and and and why we raised it. So the company announced that we'd raised approximately 4,275,000 before expenses, and we still have a retail offering that's going that could raise up to naught 500,000 at naught 0.6p per share.

23:36 The proceeds will provide the necessary capital for the company to, one, strengthen the market position and protect revenue through strategic AI and ML adoption. And I'm going to read these out for a particular reason. We're looking to derisk the platform for therapeutic development by accelerating multiple assets through pre preclinical programs. We're going to increase the chance of getting transformational upfronts by entering three distinct therapeutic areas. The first one is the gene therapy delivery, which is the siRNA liver delivery area, the radiopharmaceutical delivery programs that I've just mentioned, and we're already partnered with the top three pharma company, and looking at these these areas of undruggable targets, which I'll come on to later.

24:21 We will establish a presence in this high value space and capture larger deal values and drive expansion of the company. And and in principle, we are looking to accelerate production workflows to maximize all the passive income through the licensing, which essentially means we're gonna invest a little bit more in manufacturing capacity so that we can meet the tight deadlines that we're under as a company. So I'd like to start out with giving some context in this. So APTAMAs are essentially molecules, called oligonucleotides, and oligonucleotide medicines are gaining momentum. There's 30 plus approved therapies, 300 clinical programs, billions in capital outlay by big pharma. And our platform, which is an optimized version of an oligonucleotide, is showing potential for precision targeting in this space. And we obviously, as a company, for our shareholders, want to get access to that market.

25:17 So about 85% of potential targets are not easy for existing technologies such as antibodies or small molecules for various reasons, which I could do an hour presentation on, but I won't I won't do that now. But there's a a subset of those targets that are amenable to APTAMER technology. And it's important to explain that APTAMAs, as I've just said, are oligonucleotides, and they're designed

25:40 and have natural properties that allow them to directly interact with some of these challenging molecules. So it's also important to explain that we we use as standard all of the modifications used in modern siRNA and antisense oligo platforms, which is one way how we differentiate our product from a traditional APTAMER, which is why we've referred to our platform technology as OPTIMAs. And we've demonstrated the ability of our platform to deliver gene therapies to challenging cell targets in in our liver siRNA platform. We've also created multiple examples of molecules that bind to targets antibodies cannot bind to. All of our results in all of these different areas for the last fifteen years are held as data, tons and tons of data files, all amenable for AI and machine learning.

26:29 So it makes logical sense to combine our existing data into an AI ML model to enable us to compress timelines, generate highly valuable tools more quickly to high levels of precision, particularly in high value niche areas. So what does that actually mean?

26:49 So as we alluded to, only 15% of proteins are currently targeted, which is represented by the little yellow circle there. The remainder of the targets are essentially, undrugged proteins or undruggable targets. And two of those, areas, if you think of it like the next layer of value out, if this was an onion, are RNA binding proteins and transcription factors. And these two molecule classes naturally bind to oligonucleotides. But currently, pharma are trying to to drug them with

27:22 small molecules and antibodies, which are not the natural binding partner for this type of molecule. So we have two areas of unmet need, undeliverables and undruggables. So undeliverables is where there is a medicine, but no way of targeting that medicine to the site of interest. And an undruggable is where there is a target, but current molecules can't bind to it particularly well, if at all. And in this case, we're looking at RNA binding proteins and transcription factors where optimus can and will excel.

27:55 So to put that into context, two examples of deals in these areas, and and why we're targeting these areas as a company. So pharma are paying large amounts of money to hit these two different target areas and develop new medicines. So we've currently got active projects in the undeliverable space targeting siRNA medicines, and also radiopharmaceuticals. Both of these are high growth, multibillion dollar market with large pharma showing increasing interest and high value deals over recent years. For the undruggables,

28:26 which are on the right hand side, we aim to focus on two target classes of transcription factors and RNA binding proteins where pharma is showing increasing interest with multiple high value deals. And and and effectively, they're trying to unlock access to molecules that can target this space. The key point is there's large amounts of capital flowing into this area, and big pharma is signing multibillion dollar collaborations, hundreds of millions of dollars of acquisitions around platform technologies that their standard chemistries can't reach. And as a I suppose as an investor and from a an investor point, I'd like to leave you with the message from this slide that there is clear precedent for large upfronts and milestones when a platform opens up hard to drug targets, like transcription factors, even before a single asset reaches clinic.

29:14 But to balance, we must get there, and animal model studies are a key component in that journey. So where does AI and machine learning fit? So it's very clear. AI is fast becoming standard across all areas of life, and it's really critical in data heavy areas such as life sciences. And we already stated twelve months ago the need to combine our data into an a l an AI ML model, and we've been working towards that goal. So over the past twelve months, we've noticed increasing competition in the fee for service space from new startups claiming an AI competency, which means for us, building this model is a defensive position that needs to be taken immediately. We've evaluated several options, including in licensing partly developed AI ML platforms.

30:05 And in doing so, what we have found is that some of the current models available are trained on a handful of target proteins, and the best one that we've come across through our due diligence was with just over 20 targets at a cost in excess of £5,000,000 with what we could see, and the £5,000,000 was for access to that platform. With what we could see was a a

30:26 relatively basic level of training datasets on around 20 proteins. It it would appear and on the the left hand side of the slide, you can see the under the competitor's approach, that competitors are essentially using free online generic data. Some of them are now racing to backfill these models by creating wet labs to get more data to make their models more accurate and more usable, and this is another reason why we need to act more swiftly. So what's our advantage and why we're so confident, or why am I so confident? Well, we've already spent fifteen years operating a wet lab, collecting all of this data that is is nigh on ready to feed into an AI model. So we don't need to back fill with wet lab data. We've already got it. And rather than two to four targets or 20 targets, we've worked on over 400 targets across a range of different areas.

31:18 So, you know, we we believe that we have a massive advantage over existing companies. And we also have a ready made high throughput liquid handling lab unparalleled worldwide for generating training data. So how does this tie into RNA binding proteins and transcription factors? If you look on the diagram, you can see that we have wet lab data that that talks about 400 targets. We're planning to add around 60 specialist targets to this in the area of RNA binding proteins and transcription factors, which is color coded by the pink and the green kind of data piles within that diagram. And we'll take all of the online data, and we'll bring the weight of our fifteen years worth of wet lab data across 400 targets to provide accuracy and feed it all together into one big model.

32:09 This will be supported by the development of an additional minimum 60 targets across the focus area of RNA binding proteins and transcription factors with the view to building highly valuable and needed assets. We will further refine this model by adding outputs of the animal data that we plan to do and also detailed structural biology studies that we're currently building a consortium in in order to do that. And the the output of this really, is looking to be a world leading engine that can be speedily built and outcompete others in the market. And at the same time, FIFA service platform will continue to generate revenue and supply data from ongoing discovery projects. So move on. So what does this what does it do, essentially? What does this actually mean?

32:56 So the output to this, as generated by this kind of flywheel diagram, is AI powered APTAMER engine at the top, generates molecules and generates data that can produce candidate molecules and so on and so forth, and it feeds back into itself. So effectively, it will increase our fee for service revenue because the addition of AI services is a chargeable add on. It will essentially speed up what's referred to as hit ID and development timelines. And interestingly, from the data that we've got, we would expect that it will about half the time it takes to deliver an asset or develop an asset. And if we take half of the time to develop the asset, it will cost us half of the amount of money, both in reagents and also FTE time. So that will increase our margins on a per project basis.

33:44 The data that we get will be fed into the model, and it will focus the model, on pharma's next challenging areas as I've just explained in the past few slides. The outputs effectively of this will be licensable assets aligned with these high value markets, almost ready for out licensing with the addition of the animal studies. Ultimately, this model effectively feeds itself. It can act as a standalone asset once developed, available for pharma to license to explore key themes in RNA protein interactions across these different target types. So the the four kind of key take homes of of value layers effectively is enhanced fee for service, accelerated timelines, improved hit rates, premium pricing, standalone AI licensing, the out licensing of the molecules that are generated, therapeutic pipeline. It derisks candidate discovery for undruggables and makes that more quick. And effectively, the the the compounding effect of the data advantage. And what I mean by that is every project that we do is a fee for service basis, and every therapeutic r and d program that we do feeds into the model and improves AI predictability and accuracy.

34:56 So AI is really, it's not a key. It it it's it isn't a pivot. It's it's essentially a multiplier in our proven platform and a necessary immediate addition, or we would get left behind essentially by other companies that are doing this. So it's something that we must and absolutely have to do now. So how does this finally link through into animal studies and data proof points? Well, you might be asking yourself, why no massive upfront £10,000,000 deals for APTAMER GROUP? How did some of the companies on slide 19 reach hundreds of millions in value and be bought by pharma? And the the short answer to this is strong preclinical data packs with animal proof of concept in areas of unmet need that effectively position those companies, for an acquisition or a purchase from pharma to get access to that data.

35:49 So following the the eighth rejection in a row from big pharma based on no animal data, and the radioligand program with the top three pharma, we decided to just to take the power into our own hands and build our own differentiated set of data packs to derisk and enable our BD team to compete for high value deals. And the only way that we can do that is with animal data and to focus on areas of unmet need to add this kind of layer of value where pharma has, as as I've referred to earlier, a blind spot. So we currently have five active programs and plan to rapidly build others. In oligo delivery, we've got, our liver fibrosis program, which is the most advanced. This is ready to go into animal models immediately and will represent a major milestone for the platform that will support out licensing.

36:38 We've got some assets in chronic kidney disease. That's very close to being ready to go into animal models and just requires a couple of extra months worth of development work, and that will shortly be shortly be then placed into animal models. In the radio farm area, we have partnered with a top three pharma company already on an undisclosed cancer target, which could potentially progress onto a clinical molecule, but almost certainly will progress into animal models within the next twelve to eighteen months. We've also identified three further radio pharma targets, which we believe are very high value. In the undruggable class at the bottom of the slide, we've identified multiple targets across transcription factors and RNA binding proteins that, one, an ideal fit for our technology and, two, enable a pathway to clinic and potential deals.

37:30 So the team are ready to move these into the discovery phase and then move them through into animal studies. And finally, we have a a molecule that we've progressed to lead optimization stage, for leukemia in partnership with CR UK. This project is several years old, but we will now endeavor to work with them to move this towards preclinical animal studies and potentially further in due course. So this this approach effectively gives us multiple shots on goal, multiple attempts at animal studies, and derisks the whole, platform, essentially, or derisks the chance of failure in any single asset program. And this is where we believe the big value add will come for the company. So what does this look like? So this this slide essentially shows how we intend to deliver value with the the major inflection points at this raise funds, and these are all highlighted in yellow.

38:24 So in the first year, we will build on the foundations. We'll integrate our data into AI. We'll advance our pipeline. By eighteen months, we expect in vivo proof of concept. So this is the animal studies coming out across two programs outside of those ones that were mentioned within the liver, unlocking licensing conversations in high value areas. And beyond that, we're targeting our first out licensing of these technologies as significant milestones that that that will define the company as a as a platform company alongside other areas such as the AI model being launched for access, and AI launch of enhanced fee for service revenues. So just to move on in summary. Financial performance, a 27% uplift in revenue for the period. 1,500,000 in cash at the end of December that does provide runway to quarter two twenty twenty seven.

39:20 Operational performance, significant contract wins in high value, high growth radio pharmaceutical areas with a top three pharma partner. Nearly 800,000 in new contracts secured from one top five pharma company and with good success in the lab. Two royalty bearing licenses signed in December generating revenues. Licensing revenue is expected there for h '2 financial year '26, but we have generated some revenue from that from upfront payment and supply contract. Further assets are now under evaluation with a view to licensing. We've invested in manufacturing and our quality processes to meet the demands, which was not which was no, like, insignificant feat, and I do have to, like, congratulate the team for for being able to do that on such short notice. Post period, significant new fund fundraise announced in March providing capital to be able to generate these AI models that I've just explained, take advantage of the company's fifteen years of discovery data to, you know, ideally become a global leader in this particular area and generate this in vivo proof of concept data that we believe will unlock significant kind of value inflection points for the company moving forward.

40:35 So that, I believe, concludes the formal part of the presentation, and I will be happy to take any questions that you may have. That's great. Thank you very much for presentation. And if I may just bring back up your cameras. Ladies and gentlemen, please do continue to submit your questions just by using the q and a tab situated on the right hand corner of your screen. Just while the company take a few moments to review those questions submitted today, I'd like to remind you that recording of this presentation along with a copy of the slides and the published q and a can be accessed via investor dashboard. As you can see, we have received number of questions throughout today's presentation. And if I may just start off with the first question here, which reads as follows. Do you anticipate definitely needing further funding in 2028, or is the run runway length referred to a conservative base case that assumes no material royalty slash licensing revenues or upfront payments from potential pharma partners, etcetera, such that additional funding may not be required if things go well?

41:30 So I'm happy to take that one. So this really is a a base case scenario. We've we've made this prediction on the basis that we continue with our fee for service growing at roughly 10% per annum. We've included our anticipated licensing revenues from AlphaZyme and from from Twist. Well, this doesn't include any then of the any of the up side from any of those other assets that we talked about through the presentation. So we're there's a wide breadth of assets. We've discussed Unilever, the fetal diagnostic, the liver fibrosis, the top three pharma. There's lots of other assets there. Any one of those could add material amounts of revenue and extend that runway further. So yes, I think it's right to say that, we would consider this as a base case, scenario, and there is a reasonable chance that additional funding wouldn't be required should any of those other assets materialize, with any upside value.

42:33 That's great. Thank you. The next question we have here reads, there are some who feel that the latest options are a giveaway with no stretch element to it. It would be helpful to understand the motivation slash drivers about the latest options package for the board. Why has it ended up the way it has, and why should I vote for it? Okay. That's a tough question, and I fully understand where that's come from. I know that the the fundraising, the new option schemes raised some questions on the boards. We do we do read them from time to time to keep up to date with sentiment, particularly around tranche one and the 25% cap. So I'd try to address these directly and transparently. Firstly, I would point out all the cornerstone investors saw the scheme and rationale before agreeing to invest. We disclosed the full details to prospective places so everyone invested on an eyes open basis.

43:27 The the the structure of the options package is designed and cleared by Spark and AIM under rule 13 before the final placing price was fixed. And I can guarantee that there has been no bucket shop, Stitch Up, Return of Pope, or anyone else. And to be honest, and this is probably unprofessional in this forum, but I'm really quite offended by the comments that affect that are being put out there. It's just it's just not necessary. To to be clear, all existing options have been canceled and replaced. The new package is essentially designed to reward past sacrifice, retain the team for the next three years, the critical years, and align incentives with the growth, the new capital that we've just raised is going to fund.

44:16 So tranche one in in order. That's essentially deferred compensation for 2023 to 2025. During that period, myself, the board, all took below market salaries, zero bonuses to preserve every pound for the business. You know, at the naught point six p price, it delivers an aggregate value equivalent to around 60% of annual salaries. It saves the company cash. It's tax efficient, and it recognizes the, you know, the personal 40,000,000 paper loss for the founders, myself and Dave. You know, we we lost when we had to refinance the company between the both of us, 40,000,000. So we lost 99% of all of our value. And and and, you know, this gives us some opportunity to to recover some of that for the last fifteen or sixteen years of hard work that we've put in. The old scheme at this point had become a disincentive after the dilution and the business model pivot.

45:14 So we've pivoted the business model, and we now shoulder more early stage risk and cost towards these bigger licensing deals, and we've replaced the entire old package. It's the same 25% policies before, but with newer, more realistic hurdles that start from today's placing price. You know, net new options after cancellation are materially lower than the headline figure. I think Andrew will probably come on to explain that if there's a question on it at some point later. But overall, why is it fair to the shareholders and why vote for it? Well, because it's a it's a full reset after genuine sacrifice. We we lost 99% of the original IPO value, took 60% pay cuts, delivered the commercial pivot. We've now secured the runway to 28 minimum.

46:00 The the the formal appraisal was fair and reasonable. AIM agreed with that. And, you know, the scheme only pays out meaningfully if the share price rises, which is exactly what what I feel the alignment is with the long term shareholders. And I think that's what people want ultimately. Although I do understand, the pushback and the comments. So rather long answer, but I hope that's explained the the context. That's great. Just turning to the next question. In light of the fundraise announced today on the March 25, is the board of directors intentions to lower the targets set previously for directors to receive share options, or are they confident that the current and future contracts will deliver shareholder value and meet the existing targets set? Do you wanna take that, or do you want me to do that?

46:48 Yeah. I can take that. So, no, we, won't change the targets. They're they're more achievable from today's base because the old ones were seven times to 12 and a half times the the naught 0.2p placing price under the old scheme, the 24 scheme. Trans three of this new scheme still requires a share price to be 3.25 times, higher than the the point six, placing price, and none of that trans three kicks in until at least one and a half times, the point six issue price. So for full vesting, we require market cap to be north of 65,000,000. And then we and we made sure under this scheme that the the the total quantum, the value earned, if you like, through that scheme was was on a par with what we've done previously.

47:46 I think you could argue that the dilution, I guess, is it's certainly based on the 25% that we took before. As Aaron touched on, there's, a lot of sacrifice, particularly from the founder's side, which is why there was wanting to be some, meaningful, like, knowledge of of that and the reduced salaries that were taken, but that was all done within the 25% option pool. It could have been that, like, Alan touched on some of it to be paid out in cash, but that wasn't really seen as the best way forward, neither was it to issue shares which would crystallize a a tax charge immediately and would would would require some selling of the shares in the market, and that certainly wasn't what anybody at the board wanted to see happen.

48:37 So that really, you know, explains why why it took that form. Ultimately, with the warrants that we've offered with this with this latest placing to investors, it means the the the dilution is between 1114% on a fully diluted fully diluted basis. So, yeah, that's a a summary of where where we've ended up. That's great. Thank you. Why all the raising of capital when you inform us that you have enough to run to q two twenty twenty seven? So, yeah, the the q two twenty twenty seven still holds and was was fine purely from a a working capital perspective. But as Aaron has touched on, there were far greater reasons, I guess, for for this raise, primarily driven by the need for animal model data and for the AI enhancement of our of our current offering.

49:35 Also, we're signing a couple of these licensing deals as a manufacturing requirement, and we've laid all that out in the circular that's just been published as well. So, yes, that we've allocated a little bit more. A million pounds of this we've allocated to working capital, and that will see us through well into 2028. And that's to give us the time frame to execute on these r and d programs that Aaron's just outlined. Thank you. Which two assets will you progress through animal studies? Why only two? Well, there there won't only be two. So if investors go back and look at the slide, which I can't pull up now, we have the siRNA liver delivery technology, which we will put through.

50:21 We also have the radiopharmaceutical program that we will put through, but that's in partnership with a pharma company. We also have another two or three molecules that we're looking to put through through the radiopharmaceutical in collaboration with a with a non disclosable party at this current term because it's been at this current time, sorry, because it's been negotiated. But we have access to animal model models through Louis, through our our our new onboarded director of radio chemistry for that area. And then the other areas will be the RNA binding proteins and transcription factors. So in reality, over time, we will we will have way more than two animal proof points, which is what I alluded to earlier. Thank you. Which of your current assets will outlicense and contribute to revenue over the next year?

51:13 So, yeah, if we if we think back to that slide with the table of assets, the grid of assets on it, I think they're the ones that are most likely to progress in the short term. Certainly on the enzyme modulating space, we've made really good progress there. We've got two other companies I mentioned. One was a global enzyme provider and one a UK based company, both assessing these binders, and we've had early positive feedback on both those assessments. So I think, they're like, some of them are likely. Unilever is at fairly late stages now, it's on skin testing. We've got the pre Till diagnostic under an MTA with a global partner as well. So I think all of those have really good prospects of of adding to our licensing portfolio in the in the near future.

52:05 Yeah. And I think I'd I would just like to add to that that, you know, have having had a quick read through and and people's genuine kind of concerns about the likes of Unilever and other projects, there won't be necessarily weekly updates on these programs because they take time internally within these big companies to move through. That does not mean, though, that they're not moving forward or something's gone wrong with them. That's not necessarily the case. There there is just time needed for updates to come through and filter through to our analysis. That's great. Thank you. Just turning to the next question. Is the 400 k allocated to manufacturing enough to scale up to the levels needed to supply customers? Yes. Certainly. We think well, we've done a lot of work during the period, so we've got the processes in place now. The capabilities are there, and we can manufacture to certain level with the equipment that we've got. This would allow us to go the next scale up.

53:02 Of that 400 k, it likely cost us a 150 k just to go into that manufacturing space. We've got two pieces of equipment that we've already scoped out that we need to allow us to manufacture on the scale that that these licenses would, well, it will see as well within, capacity then for these licenses that we've already negotiated. And there's a sorry to to interrupt there. There's also another critical point with this equipment, is that it enables us to manufacture the molecules for animal trials to the sufficient quantity and purity, which is really, really important in protecting our intellectual property. The last thing that we want to do is send the sequences for these molecules that could have massive value to us as a company to external parties for manufacture before we have patents, filed to protect the technology. So there's another reason for why we're invested in the, in the scale up for the oligosynthesis.

54:01 That's great. Thank you. When will the AI consortium launch, and who is involved in this? What will it bring to the AI models that you sell? So the I don't think it's appropriate to comment on who will be in the AI consortium other than to say it's highly likely to be academic institutions that have access to structural biology data. And what it will bring to the AI models effectively, it will it will enable much higher levels of predictability of how the nucleic acids and proteins interact on the structural levels. So for those science y type people, if you think of it a bit like AlphaFold, but in the new the oligonucleotide space, that's what we're aiming to do.

54:49 So we've got expertise that's been offered from plan consortium members. But, ultimately, when it's signed off, we will say who it is, but it's likely to be across a couple, two, three, maybe four different university groups, around the country, and that's being worked on at the moment. That's great. Thank you. And I think the last question we've got here reads, how are discussions progressing around the fibrotic liver delivery vehicle? At what stage would you foresee out licensing this asset to pharma buyers? So I can I can take that one? We've had multiple conversations, and I referred to it earlier. We've had eight kind of rejections, I suppose, if you want to look at it that way from big pharma on the basis that we don't have the animal data. As soon as we have the animal data, we will immediately be back in touch with those people at the earliest opportunity to present the data and try to move things forward.

55:42 We have been very close to a deal on a couple of occasions with this particular asset, but, unfortunately, we've no luck because of the fact that we didn't have the animal data. So, ultimately, as a board, we decided to bite the bullet and raise the funding in order to do that so that we can add value in the long term for the shareholders. That's great. Thank you for answering all those questions you can from investors. And, of course, the company can review all questions submitted today, and we'll publish those responses on the Investor Meet company platform. Just before redirecting investors to provide you with their feedback, which you know is particularly important to the company, Aaron, could I please just ask you for a few closing comments? Yeah. I'd I would just really like to say that I do recognize the dilution is frustrating for many people, and, you know, I've felt the pain of being diluted myself previously.

56:33 The fundamentals of the business, however, haven't changed. The raise gives us a stronger platform to rebuild from. The the scheme, I suppose, is the commitment from the team to stay fully aligned with the upside we're now planning to and position to deliver. And we, you know, we do look forward to updating you on the platform, the radiopharmaceuticals progress, the s r and a progress, and all the other things that we're doing in coming months. That's great. Thank you for updating investors today. Can I please ask investors not to close this session? It should now be automatically redirected to provide your feedback in order that the management team can better understand your views and expectations. This may take a few moments to complete, and I'm sure be greatly valued by the company. On behalf of the management team, we'd like to thank you for attending today's presentation, and good afternoon to you all.