Operator: 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 can be submitted at any time via the Q&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 is appropriate to do so. Before we begin, I would like to submit the following poll. I would now like to hand you over to management.
Arron Tolley: Meeting, and welcome people to Aptamer Group's full-year results for the 12 months to 26 June. I am Arron Tolley, Chief Executive, and I am joined by Andrew Rapson, our Chief Financial Officer. I would just like to start out by saying this has really been a year of two halves. The H1, we signed our first licensing deals and set out a clear plan for the next three years. The H2, we have expanded our lab offering and pipeline, setting the stall out for the next several years. Today's presentation aims to update you on the progress. Show you what we said we would do with the funding, what we have actually done in the six months since we received it.
Arron Tolley: We will broadly cover four areas, a brief overview to the business and the year's milestones, the financials, which Andrew will take you through, and then operational progress across the commercial platform licensing, progress on our artificial intelligence work and our two therapeutic programs. Finally, a brief update on things that have happened since year-end, our post-period highlights, and where we are going to go from here. We are happy to take any questions at the end, so please submit them as you go. Right. So onto the next slide. To the presentation team. I am Arron Tolley. I am co-founder and Chief Exec. My background is I have a PhD in structural and molecular biology.
Arron Tolley: I've spent the last 18 years building the technology and the company, taking it from a company started in the basement of my house many years ago to one that now works with the majority of the world's top 20 pharmaceutical companies. I run the day-to-day side of the business. I sit on the board, the scientific advisory board, and remain reasonably hands-on with both the science and commercial strategy. In particular, I've taken responsibility for the AI and machine learning strategy that formed a reasonable part of the April fundraise, which I'll update on later. With me is Andrew Rapson, and I'll pass over to him to do a quick introduction. Thanks, Aaron. Good afternoon, everyone, and thank you for joining us today. I'm Andrew Rapson. I'm Chief Financial Officer of Aptamer Group. I joined the business in August 2022 and became CFO in August 2023.
Arron Tolley: I'm a chartered accountant with more than 20 years' experience in finance and have worked with AIM-listed companies for over a decade now. Today I'll talk you through the group's financial performance for FY26 and how our financial position supports the next phase of our commercial growth. Thank you. For anyone new to the story, I figured we'd just do a brief orientation. Aptamer Group is a York-based AIM-listed company, a recognized global player in aptamer/Optimer development. We discover and manufacture Optimer binders. These are short nucleic acid molecules that essentially do the job of antibodies, but they can be made faster, they can be made chemically, and they can be made against targets where antibodies struggle or fail entirely. We do this on our proprietary automated discovery platform, which David and myself have spent the past 18 years building and refining.
Arron Tolley: The core of this is essentially liquid handling robotics running highly parallel selections. This is multiple different selection projects in parallel. We believe this outperforms anything comparable out there in the market. Our customers are generally pharmaceutical companies and large biotechs. Today we can still say that we work with 85% of the top 20 pharma companies. A good proportion of that is now repeat business, which I'll come on to. We are a revenue-generating company. We've moved into the next phase of growth, which is looking to license and build an asset portfolio. This particular phase is taking these assets that our platform produces and converting them into licensed products that earn recurring royalties and supply income alongside our fee for service revenue.
Arron Tolley: Over the last 12 months, and in particular the last six, these have been, I would say, the most technically dense in the company's history. We've spent some time building the platform out for the next phase of growth, and in that period we've managed to grow revenue by 28% to GBP 1.5 million. Importantly, a 36% increase in repeat business from large pharma. We've signed two licensing deals with Twist Bioscience and Alphazyme, set up manufacturing internally to supply the materials for these deals, and delivered the products and received our first licensing income. We've set out and delivered an AI strategy, hired a team, built and trained our first in-house models on our own proprietary data, and put the first AI design candidates into our lab, and we've done this all within a six-month period.
Arron Tolley: We've also bought, commissioned, installed new automation that has cut discovery timelines by half and added much-needed capacity to the system. I'll come on to explaining how this ties into the artificial intelligence program a bit later. We've launched a targeted radiotherapy program, signed our first radioligand contracts with a top three pharma company, and initiated separate animal studies with a consultancy company who are expert in the handling of radioisotopes. We've designed and manufactured and tested Optimer siRNA conjugates, which is effectively a drug molecule for our planned fibrosis pre-clinical animal studies. We finished the year with GBP 4.4 million of cash and a sales pipeline that has grown from GBP 4.8 million to GBP 7 million on account of repeat business converting potentially into multi-target material transfer agreements, which I'll explain in a bit more detail.
Arron Tolley: I'll come back to each one of these in the operational review, but first I'll pass over to Andrew to take you through the financials.
Andrew Rapson: Thanks, Aaron. So, onto the income statement and cash flow. FY26 was a year of significant commercial and strategic progress for Aptamer Group. As we continued to grow our customer base, we established our first licensing revenues and strengthened the balance sheet to support future growth. Revenues increased 28% to GBP 1.5 million, compared with GBP 1.2 million in the prior year. Of this total, GBP 1.4 million related to fee for service contracts, while approximately GBP 0.1 million was generated from licensing agreements. Whilst licensing revenue remains a relatively small portion of total revenue today, strategically it represents an important milestone for the business.
Andrew Rapson: The licensing agreements signed during the year validate both the quality of our assets and our ability to generate value from intellectual property beyond traditional service revenues.
Andrew Rapson: Over time, our objective is to increase the contribution from licensing, creating a more predictable, scalable, and higher margin revenue mix, while continuing to leverage our fee-for-service activities to develop new commercial opportunities. Commercial momentum remained strong throughout the year. We secured GBP 2.2 million of new fee-for-service contracts and carried a further GBP 0.3 million of laboratory work into the financial year. That resulted in an opportunity pool of GBP 2.5 million of contracts. We recognized approximately GBP 1.4 million of that as revenue during the year, and we carried forward another GBP 0.5 million into FY27.
Andrew Rapson: In addition, our sales pipeline has grown to approximately GBP 7 million. We believe this reflects both increasing market recognition of our platform and the success of our strategy to structure projects in a way that reduces technical risk for customers while maintaining attractive economics for the group. Whilst investing for growth, we remain disciplined on costs.
Andrew Rapson: Administrative expenses increased, accounting for an increase from 31 to 34 employees as we strengthened scientific, commercial, and strategic capabilities across the business. Importantly, the group also increased investment in internal innovation. Research and development expenditure included within admin expenses increased from GBP 0.4 million to GBP 0.6 million. This reflects targeted investment in our fibrosis delivery program, our AI platform, and our radionuclide delivery program following a successful financing completed in April. As a result, adjusted EBITDA loss was GBP 2.3 million, broadly in line with the prior year's loss of GBP 2.2 million, despite the increased investment activity undertaken during the year. One notable feature of the income statement is the increase in the R&D tax credit benefit. The group recognized a tax credit of GBP 0.9 million, compared with GBP 0.1 million in FY25. During the year, we undertook a detailed review of qualifying R&D expenditure and submitted amended claims relating to prior periods.
Andrew Rapson: That was for FY25 and FY24. This resulted in increased tax receivable at year-end, with approximately GBP 0.5 million subsequently received shortly after the reporting date. This demonstrates the continuing value of innovation activities and provides a meaningful source of non-dilutive funding for the business. I just turn onto the cash flow. As expected for a business at our stage of development, we continued to invest in growth during FY26 while also maintaining disciplined control over cash utilization. Net cash used in operating activities was GBP 2.1 million, compared with GBP 1.9 million in the prior year.
Andrew Rapson: This reflects ongoing investment in commercial expansion, platform development, and the advancement of our strategic programs, while continuing to drive revenue growth across the business. We invested a further GBP 0.25 million in capital expenditure and intellectual property. These investments support increased automation, manufacturing capability, and development capacity, helping position the business for future scale.
Andrew Rapson: The most significant cash flow event during the year was financing activity. That was across the July 2025 and April 2026 fundraises. The group secured approximately GBP 6 million of cash proceeds. These funds are enabling us to accelerate development of our AI initiatives, progress therapeutic assets towards key value inflection points, and expand capabilities that support future licensing opportunities. As a result, year-end cash increased from GBP 1.1 million to GBP 4.4 million. I turn to the balance sheet now. Our financial position strengthened significantly due to the fundraise in April. Net assets increased to GBP 5.7 million from GBP 1.4 million. Cash at year-end, as I have just mentioned, was GBP 4.4 million, compared with GBP 1.1 million, and the group received GBP 0.5 million of R&D tax credit shortly after the year-end. That gives us a position where our runway now extends through to calendar year 2028.
Andrew Rapson: Working capital balances increased broadly in line with activity levels across the business, reflecting the higher volume of customer projects and growing commercial engagement. The increase in tax receivables reflects that R&D tax credit that I just mentioned. Overall, the balance sheet is substantially stronger than a year ago, provides a solid platform for the next stage of growth. For the next slide, I want to touch on the fundraise that we have just completed in April, and importantly, how these investments support our strategy to create long-term value for shareholders and deliver a route to EBITDA breakeven. Our strategy is centered on transforming Aptamer from a predominantly fee-for-service business into a platform company built around proprietary technology, differentiated therapeutic assets, and recurring licensing revenues. The first area of investment is artificial intelligence and machine learning.
Andrew Rapson: Over the last 15 years, we have generated substantial proprietary data through our Optimer discovery programs. We believe this data set represents a significant competitive advantage. By investing in AI, we are not simply improving operational efficiency, we are creating a discovery engine that can accelerate candidate identification, enhance success rates, generate new intellectual property, and potentially create an additional revenue stream through AI-enabled services and future licensing opportunities. The second area of investment is advancing our therapeutic programs towards in vivo proof of concept. This is a particularly important objective because animal validation is often the milestone that allows pharmaceutical companies to meaningfully evaluate partnering opportunities. Our aim is to generate high-quality preclinical data that demonstrates the value of our platform and supports larger licensing discussions. Third, we are targeting some of the most attractive and fastest-growing areas of pharmaceutical innovation.
Andrew Rapson: Specifically, we are investing in technologies that address what the industry often describes as the undeliverable and the undruggable. This includes therapeutic oligonucleotide delivery, targeted radiopharmaceutical delivery, and accessing difficult biological targets such as transcription factors and RNA binding proteins. These are areas attracting significant pharmaceutical investment, while existing technologies continue to face limitations. The reason this focus is important is that successful technologies in these markets can support very substantial commercial partnerships. We believe Aptamer's platform is well-positioned to participate in these opportunities and create multiple future value inflection points. The fourth area of investment is commercial expansion. Our objective is to increase the proportion of revenues generated from licensing, milestones, supply agreements, and royalties. These revenue streams are typically higher margin, more scalable, and less dependent on continuous headcount growth than traditional service revenues. Finally, we are strengthening our manufacturing and operational capabilities.
Andrew Rapson: This ensures we can support current partners, fulfill future supply obligations, and participate more fully in downstream value generated from programs that progress towards commercialization. Bringing all of this together, our route to EBITDA breakeven is supported by three key drivers. Firstly, continued growth in fee-for-service revenues from our expanding partner base, supported by an increased sales pipeline. Second, increasing contributions from higher-margin licensing revenues, including upfront payments, milestones, supply revenues, and royalties. Third, improved operating leverage through AI-enabled development and automation, allowing revenue growth to outpace growth in our cost base. Importantly, we are not investing this capital simply to grow the current business. We are investing to build a stronger platform business with multiple opportunities to create value.
Andrew Rapson: Success over the next 12 to 36 months will be measured by progress in our AI platform, the generation of in vivo proof-of-concept data, further licensing agreements, expansion of our therapeutic pipeline, and continued progress towards sustainable profitability. We believe this strategy positions Aptamer to capture greater long-term value from its technology, while building more predictable and scalable revenue for shareholders. Alongside the latest fundraise, we launched a new share option scheme, which was approved by shareholders at the 26 April general meeting. The total scheme represents just under 18% of the fully diluted share capital and was designed to align management and employee rewards with long-term shareholder value creation. The first tranche represents 4% of the fully diluted share capital and vested immediately. This was intended to recognize past performance while preserving cash for investment in the business.
Andrew Rapson: The second tranche represents slightly under 5% of the fully diluted share capital, and vests over 3 years, and is subject to a minimum share price hurdle of GBP 0.65 pence, supporting retention and continuity as we execute our strategy. Importantly, over half of the option pool relates to tranche 3, which is performance-based, and this tranche only vests if the share price delivers significant appreciation from the fundraise price, with vesting linked to share price performance between 1.5 times and 3.25 times that level. Including all options and warrants, the fully diluted share capital would be approximately 4.8 billion shares. We believe the structure strikes an appropriate balance between managing dilution and ensuring management's rewards are overwhelmingly tied to delivering value for shareholders. I will now hand back over to Alan to take us through the operational review.
Arron Tolley: Thank you, Andrew. All right, so turning to the operations. This year we have essentially got two jobs. One was to secure the funding that lets us build, and two is to use that to remove bottlenecks between growing pipeline and the revenue it should produce. Let us start with the commercial numbers. Our fee-for-service revenue grew by 28%, and for context, the pharma R&D services market is currently forecast to grow at roughly 8% to 10% a year. We grew at 28%, which is 3 times the market rate, which we believe is good progress against that background. More importantly, repeat business from large pharma grew 36%, and in this industry, repeat orders are not generally given lightly.
Arron Tolley: Repeat business is given when our binders are generally shown to be functional in the customer's hands, having solved the problem, and then we get asked to develop a solution to another problem and so on. So the 36% ahead of larger revenue and bigger deals being brought in. It is the indicator that usually precedes this happening. It is worth at this point as well, being clear about revenue timing and why revenue lags the work in a business like ours. This is not a company like Amazon. Growth in the pipeline and repeat business does not necessarily immediately translate into an uptick in revenue within a few weeks or a few months. There are a couple of reasons why, and I figured it would be a good point to explain this.
Arron Tolley: Firstly, a pharma customer or one of our bigger biotech customers will test a platform on a couple of opportunities, a couple of deals, anywhere between GBP 100,000, GBP 300,000. They will then need to validate those binders in their own assays internally. Generally, that can take between 6 to 12 months. Then at this point, once they are demonstrated to be successful, they expand their interest. We go through another negotiated discussion, and then we bring in more opportunities in the repeat business. The revenue line effectively stays relatively modest through that validation period while the relationship and the data accumulate. So the 36% rise in repeat business is generally what we would consider the evidence that the expansion phase is beginning to happen. We have made four main changes ahead of this year. Automation, new liquid handling systems installed and running.
Arron Tolley: They let us do several large pharmaceutical programs in parallel, and they add physical manufacturing capacity to the company. We have re-engineered the core discovery process and cut the time to identify binders by roughly half. We have increased our chemistry capability, standardizing conjugations, adding broader range of functional groups into the molecules that we can now manufacture, including the ability to make our own siRNA conjugates, which will be critical for the therapeutic delivery programs that we will talk about later. We can also use the in-house capacity to support licensing by making our own products further increasing margins. So, in terms of manufacturing, a lot of work that we have previously outsourced, we are now doing in York. That removes vendor dependency, it shortens further timelines for customers, and it is one of the reasons our gross margins have improved from 48% to 53%.
Arron Tolley: So simply put, a bigger pipeline is only useful if the lab can deliver it, and that is where some of the funding has gone to enable us to do that. So the summary really is the platform is now faster, higher capacity than it was six months ago. Our margins are improving and getting higher. Our largest customers are buying more product, and that is effectively the operational base that we needed to have installed to begin converting the pipeline that is growing as we speak. So moving on to the next slide. So the Optimer assets. So the next step in the model, once we can develop binders, is turning the products into assets that we own and we can license and generate revenue from.
Arron Tolley: So if we think of fee for service as the gateway pays for the work, it puts our binders in front of customers in the industry, minimizes our investment needs, and it generates the assets that we can then turn into recurring royalties, and it supplies us with additional income streams. So the wheel on the left effectively shows why this matters for a company of our nature and particularly us as a business. We are not a single asset biotech, where one trial result decides the outcome of the progress of our business.
Arron Tolley: The same platform generates intellectual property across five independent markets. We have got life sciences tools, diagnostics, therapeutics, vaccines, cosmetics. Each of these is a separate route to revenue. None of them depend on the others. This year, we have demonstrated that by producing its first results. We have licensed the enzyme modulation Optimer to Twist and Alphazyme.
Arron Tolley: Both products are launched. They are being used in the market. We are receiving licensing income. We have had further orders from these customers as it appears that they are growing their sales themselves. We are also talking to four further global life sciences companies who are evaluating the same binders under material transfer agreements. News of this has led to further interest in our pipeline in enzyme modulation from potential customers, and we are also building internally our own assets in that particular area. So moving on to update on the AI side of things. The logic here is fairly straightforward. Aptamer discovery is becoming quite a crowded field. Much of the new competition is computational in nature. Our advantage is not that we can write algorithms as a company, it is that we have 18 years of fee-for-service work. We have data sets that nobody else has.
Arron Tolley: On the table here we have, on the left-hand side, shows the gap. The published models are typically trained on 1 to 4 targets or on sparse, publicly available data. Our model is trained on nearly 660,000 or over 663,000 sequences across 223 protein targets, which is a bit different from the 4 or so that general models are trained on. That number has grown sharply since June. We reported 450,000 sequences and 42 targets. This is because we have now loaded our complete historical archive into the training set, and we are now adding to that with every project that we run. This gives us depth and breadth at the same time, which is what you cannot get from the public data sets. Just to add there, we have taken all the publicly available data, and we have added that into our model as well.
Arron Tolley: In the 12 months since we set strategy, we have hired a machine learning team, built the model architecture, trained it to a working state, and manufactured the first batch of AI-designed Optimer candidates. Some companies are spending millions to do this and taking years to get there. Some competitors have raised millions to do this and have also taken years. We have started and completed within 6 months with GBP 4.4 million left in cash at the end of the year. We think this is a really good, positive thing to update the market with. Last week, we doubled our training capacity with a second GPU, which is now installed and operational. What the model we have built is generally aimed to do is to design new candidates computationally from a target structure. This is something that we are aiming towards.
Arron Tolley: Take the billions and trillions of possible sequences and narrow them to a focus set that we can actually test in our labs. Refining our existing binders by identifying the parts of the molecule that drive binding, and this should essentially shorten our time frames for delivery and enable us to deliver better quality products for our customers. Where are we today? The first candidates are being validated in our wet labs. We are not going to jump the gun and claim performance before we have got the data, but what I can say is the model is running, the validation is underway, and we expect to report the results in coming months.
Arron Tolley: That is a milestone, I think, that we will be looking forward to presenting to the market because it will tell us, and it will tell you guys, how much of the discovery process can move effectively from wet labs through to an in silico or computer-based system. The automation is important to mention here as well, because this is the other half. The robots that we have installed, and we have increased the performance on run effectively a loop with the artificial intelligence engine. The robots design the aptamers, the aptamers get manufactured, they get sequenced, data goes back into the model, and it creates a kind of virtuous cycle of data generation and refinement and improvement within the model.
Arron Tolley: Each time we go around this process, the model gets stronger and we get better quality data, and it gets us much closer to what is referred to as a generalized model, where aptamer sequences will be possible to generate what is referred to as in a de novo setting or without actually doing any lab work. That is why the lab automation and the artificial intelligence were funded together. It is what will allow a team of 30 people plus to handle multi-target and multi-year accounts without the head count growing in step with. That is what good operational delivery looks like within a company of this nature. Moving on to an update on the targeted therapeutic side of the company. The AI engine and the automation are effectively tools. They operate and work within our fee-for-service side.
Arron Tolley: What we have to look at is what we point the technology towards that is of very high value. The next two slides will aim to show you what we are actually pointing the technology towards. We are looking at two therapeutic areas, both of which are delivery-focused, which is getting molecules to the right cells within the body, and where our binders have properties that peptides, antibodies, and protein technologies lack. Firstly, we will talk about the targeted radiotherapy. Radioligand therapy is essentially using a targeting molecule, in this case an aptamer or an Optimer, to carry a radioactive isotope directly to a tumor cell. It is one of the fastest-growing fields in oncology at the moment, where big pharmaceutical companies are actually acquiring assets quite aggressively, so it is important that we get on the front foot here.
Arron Tolley: We entered into this space in October 2025 with a radioligand discovery contract with a top 3 pharma company. We are looking forward to update the market on that as we move that forward. Building on that with confidence internally, in March this year, we launched our own programs in partnership with a company called Radiopharmium. This is a consultancy that works with radioisotopes. We just cannot handle radioactive material in York, so we have to partner this in order to get the data.
Arron Tolley: We have identified three high-value targets of our own, taking the pipeline to four assets, one of which is partnered, and three where we hold fully the intellectual property. I think it is critical to explain our progress in this area is not particularly slow going. We are actually doing really well. It takes time to do the work properly and get things ready for animal studies.
Arron Tolley: There is a lot of precursor work that needs to be done. The technical progress that we have made here really does matter, so I will take the time to explain. Stability, historically, is a weakness of radioligands. If you imagine that these molecules have highly radioactive particles attached to them, then they are obviously designed to damage cancer cells and damage DNA in cells and proteins and so on and so forth. The actual carrier molecules are very important for them to have high levels of stability. Our team has established standardized radiolabeling methods, which is effectively adding a small cage on the end of the molecule that enables the radioactive particles to be conjugated to them. We have managed to achieve a 99% radiochemical purity at clinical-scale activity levels.
Arron Tolley: We have done some head-to-head in vitro, which means in test tube studies, with radiolabeled Optimers, and we have shown 76% to 90% less radiolytic degradation than protein and peptide comparators. So what this means is the Optimers that we have tested are much more stable than their protein counterparts. If that holds in an in vivo setting, if that translates through to an animal model, it means a more stable therapeutic molecule with a more useful, longer therapeutic window. That testing is currently underway. In March, we told you that we would have some in vivo data across our therapeutic programs within 12 to 18 months. Material has been shipped to Radiopharmium, and the first in vivo studies are in progress, and we expect some results by the end of this calendar year, if not early into next calendar year.
Arron Tolley: The second area applies the same idea, but really to a different payload. This is the delivery of genetic medicines to the right cells. The second program is what is referred to as therapeutic oligonucleotide delivery. This is a market growing at close to 20%, and it has one defining problem, as do a lot of technologies currently, which is delivery. siRNAs and antisense oligo drugs work incredibly well, but almost all of them struggle with delivery outside of the liver. In fact, targeting very selective types of cells within the liver, such as the cells responsible for fibrosis, which is one of the things that we have looked to doing as a company. Getting them to be delivered to any other tissue is an industry unsolved challenge.
Arron Tolley: We believe that conjugating Optimer or Optimers to these siRNAs and antisense oligos can represent a way to overcome that unsolved challenge. Optimers can be generated to bind selectively to cell surface markers and can effectively act as a GPS coordinate to guide the therapeutics to the tissue of interest. We have three delivery vehicles in development. We have our fibrosis/liver vehicle, which is the lead that we are working on. It is in preclinical characterization. It has shown no toxicity as of yet, good stability, no markers of immunogenicity in the tests that have been done. These are all three things that typically end or kill a delivery candidate early in a discovery program. The in vivo study design, which is how we are going to test these molecules for efficacy in animals, is finalized.
Arron Tolley: The study partner has been selected, and we are currently, and have made the siRNA conjugates in-house for the study. The kidney vehicle has been identified and shown to be selective for a specific type of kidney cell that would allow siRNA delivery for the treatment of chronic kidney disease, and we are moving through that process in the same way as the fibrosis delivery vehicle, although we are just slightly behind pace on that. This year, we started a third program. We are looking at a shuttle to carry therapeutics across the blood-brain barrier. This is a very early-stage project. It is still in target ID, characterization, and discovery. We expect initial results to come over in the next few months. Beyond these three, we are exploring further tissue targets through partnerships that can provide preclinical animal data.
Arron Tolley: We have a particular interest in cardiovascular delivery and skeletal muscle, which are currently also unmet needs. Across these 2 slides, the picture is 4 radioligand assets with 1 with the top 3 pharma and the preliminary in vivo data due on the others by calendar year end. A fibrosis vehicle entering animal studies, a kidney vehicle in optimization, and a new brain delivery program started and discussions are underway on extra targets and different areas. Moving on to the post-period review. Everything so far covers the year to June. We did not obviously pause at the end of the year, so we would like to bring you up to date with things that we have done. To start with the commercial pipeline, that stood at GBP 4.8 million, and it is now today over GBP 7 million.
Arron Tolley: To be clear by what I mean when I refer to pipeline, I mean a qualified opportunity that we are actively quoting against or in legal negotiations. Nothing earlier than that gets quoted in our pipelines when we put any news out. The growth since June mainly comes from the shift that I alluded to earlier. Customers who are currently spending on one-off development projects in discussions now to move towards multi-year, multi-target master service agreements, several of which are now in active negotiation with top pharma companies. If these convert, they will give us contracted volume and visibility rather than revenue on a project-by-project basis. This is the foundation that we wish to lay to get a path towards EBITDA break even. I cannot give exact timelines on these deals, but we expect them to start closing shortly.
Arron Tolley: These protracted negotiations have largely been behind the slower rate of RNS releases as existing deals get wrapped into these larger agreements. Technically, several important things have happened. Folic acid binders have gone to Imperial College London for integration into lateral flow assays. The fibrosis vehicle in vivo study design has been finalized. Conjugates have been made and purified in-house, and this work will start soon. The radioligand delivery Optimers have been synthesized and shipped for animal studies. On licensing, we are now developing our own assets and enzymes and looking at applications in cosmetic fields to build on the success that we have seen with Twist and Alphazyme deals. These are self-funded, so the group would keep all of the IP rather than sharing them with a development partner. Each one that we can successfully generate and develop adds to the pool of assets available for out-licensing.
Arron Tolley: We are also continuing to explore extrahepatic delivery targets through partnerships. This is different tissue types that I mentioned in the last slide. We are looking to partner with companies to get additional preclinical animal data packs that are required to engage larger pharma partners. This is a more cost-effective model by partnership because it allows us to gain access to animal models and the data that is required across a broader range of opportunities and target types than if we were using our investment money to do that. We are already looking at liver, kidney, blood-brain barrier internally with our siRNA delivery work. We aim to update the market on partnerships for cardiovascular and skeletal muscle, which are hot areas of interest, and we will update as we progress through signature on those partnerships.
Arron Tolley: Over the last several months, we have focused on AI and automation, expanding the pipeline with repeat business contracts, passive income generation via expanding opportunities for licensing, generating molecules for animal studies, and expanding our partnerships for additional delivery system animal data validation. I will close off with the roadmap that we set out in April and where we are against it. This is the roadmap that we published in April, and I want to report where we are against progress. We set out a 36-month plan in 3 phases. We are 6 months into the first phase, integration and discovery. The milestones for this phase were to get the expanded manufacturing capacity operational, to have wet lab data flowing into an AI model, to have the model trained on our historic data set. All of these are done, and they are ticked on the slide.
Arron Tolley: The second phase, the 12 to 18 months phase, is a pre-clinical validation and scaling. Its 2 headline deliverables effectively are in vivo proof of concept data across 2 therapeutic programs and the launch of the AI-enhanced fee for service offering. On the first one, the radioligand in vivo data is expected, as I have said earlier, by the end of the year, and the fibrosis study will be following shortly after due to the length of time difference between the 2 types of study. On the second, the first AI design candidates are now in validation, and the AI-enhanced service offering follows those results. We could probably launch that now, but we wish to be cautious and wait for internal validation on the candidates before doing so. The third phase, which is 18 to 36 months out, is effectively the commercialization phase.
Arron Tolley: The aim here is to out-license at least 2 validated therapeutic assets, and we aim to do that by diversification and partnership that I described earlier to get multiple shots on goal with respect to getting animal validation data for delivery across a range of different tissue types. To make the AI model itself available for licensing, this one is probably the more difficult one to predict the exact timeline for, because it will rely on the model generalizing, which may happen sooner rather than later. Generalization effectively means that we would be able to do what is referred to as de novo discovery. That is discover sequences without having to do any lab work, and that is obviously the holy grail of the discovery for these kinds of molecules.
Arron Tolley: I would also add, and it is not on the slide, that we will be doing this alongside a growing base of tools and cosmetic assets that we have talked about on the asset wheel a few slides back. To close, in April, we set out a specific plan. 6 months further on, the manufacturing capacity is operational, the AI model is built and in validation. Radiotherapy and delivery programs are entering animal studies. We have our first licensing income. We have got repeat business from large pharma, up 36%. We have grown the pipeline to GBP 7 million, and we are on the cusp of multi-target deals. We ended the year with GBP 4.4 million of cash, which funds the plan and the company into 2028 and enables us to make good headway towards our EBITDA breakeven position.
Arron Tolley: I think the main take-home from the slide is that within the first six months, the team have delivered the first 12 months worth of work. Thank you for your time, and that concludes the formal part of the presentation, and Andrew and I will now take your questions.
Operator: That is great. Thank you very much for your presentation. If I may just bring back up your cameras. Ladies and gentlemen, please do continue to submit your questions just by using the Q&A tab situated on the top right-hand corner of your screen. Just while the company takes a few moments to review those questions submitted today, I would like to remind you that a recording of this presentation, along with a copy of the slides and the published Q&A, can be accessed via our investor dashboard. As you can see, we have received a number of questions throughout today's presentation, and if I may just start off with the first question here, which reads as follows: Can you please let shareholders know why the patent applied for by Aptamer Group and Unilever has not been published?
Arron Tolley: Well, I think it has been published. The application went in early 2025, February, March. It will not have been granted yet. It is still in that phase, but I believe you should be able to find that online now.
Operator: That is great. Just turning to the next question here. How are the Twist and Alphazyme licenses going, and when can we expect to see the first revenues?
Arron Tolley: Generally speaking, they are going well. We have seen the first revenue, so we have reported GBP 0.1 million of licensing revenue in this period, which came from those two contracts. Both customers there have launched new products, both are in the public domain, so you can find their products on their websites with our Optimer included. Twist, I think have progressed fairly well so far. It is going through a customer validation phase. We knew that when they get to product launch, that they will be looking to push this out to new customers, and that can take some time. So far so good. Seems to be progressing quite well. We expect to receive supply agreement payments and royalties through this financial period.
Operator: That is great. Just moving on here. How is the fortified foods rapid testing program progressing?
Arron Tolley: I think I can take that one. We have delivered the folic acid binders to Imperial College London for integration into a lateral flow test. We have developed sample preparation methods for four different food types. This is where we extract material from the food substances in order to add the samples to the lateral flow device. That was the first part of the program prior to developing the lateral flow. The program aims really to produce an affordable field test for monitoring folic acid levels in fortified foods.
Operator: That is great. We have just got a question here around AI. How will you prove the AI model is better than your existing platform?
Arron Tolley: That's a good question. How will we prove that? I think we'll prove it by taking existing aptamers that have been generated from our standard platform, adding the data into our AI model. That will then give us additional molecules that it suggests could perform better. We would manufacture those and test them and compare the results. Do the aptamers that come out of the AI model perform better than aptamers that come out of our standard service offering? And we believe that will be the case. The first AI-selected candidates are currently undergoing lab validation. We do need to demonstrate that they perform against the intended targets before we launch the service, as I alluded to in my presentation. But the aim really will be faster discovery, improving the performance of the molecules. As we validate that, we'll provide updates to the market.
Operator: Thank you. Can you update us on the next milestone in the Unilever program?
Arron Tolley: Do you want to take that one, Andrew?
Andrew Rapson: Can do. Yeah. Unilever, I think the last update we gave was going to on-person testing. It's still in that phase of work with Unilever. Obviously, we're not allowed to report too much on the detail there, but Unilever are still progressing with that and seems to be progressing well so far. It's going through scientific development. Obviously, testing it on-person is quite a different environment to testing it in the lab, so we're working with Unilever on that process.
Operator: Thank you. Just moving on here. With programs running across diagnostics, cosmetics, food testing, radiopharmaceuticals, and oligo delivery, is the company spread too thin?
Arron Tolley: So yeah, it's a good question. All of the different programs that we work on effectively use the same platform, almost like a machine that manufactures nuts and bolts, so it doesn't really matter where they go. The platform, the fee for service work all comes through a standard platform offering within our company. That fee for service model generates near-term revenue. It allows us to then provide opportunities for licensing across a broad range of different areas. The automation supports that. The investment in the automation increases our ability actually to spread ourselves thinly across different areas. So no, I wouldn't say that we are spread too thinly. If we were trying to do 30 or 40 different therapeutic areas, then obviously that's a big stretch.
Arron Tolley: Generally speaking, offering our platform out to generate binders to a multitude of different targets for different application areas is not a stretch.
Operator: Thank you. The next question we've got here reads: how many assets are in active licensing discussions, and which is closest to signing?
Andrew Rapson: I think the area where we've had the most success is in the enzyme modulating reagents to date. Obviously, with the two licenses we signed in the year, we've had numerous parties who are interested in that technology, either for the same or very similar enzymes, either to work on development or take an existing product. We've currently got four companies that are assessing variants of those assets for their own use, for going into their own products. They're probably the closest and the most ready assets to be licensed in the near term. We've also got an agreement that we announced last year with a 2% royalty for an immunohistochemistry, but obviously that one's ready from a licensing perspective if and when the asset gets to a commercial stage.
Operator: Thank you. What will success look like for the in vivo studies? When do you expect first data, and what sort of values can we anticipate for licensing?
Arron Tolley: The studies effectively aim to establish a proof of concept for targeted delivery radiotherapeutic candidates, and that will support potential licensing. What would success look like? It would look like targeted delivery to particular tissue types. If we're looking at delivery to the liver, we would imagine to produce data that would show aggregation of the molecules in that particular area of the animal. We would be looking at PKPD, so pharmacokinetics and distribution data to show that the Optimer aptamers have good potential for delivering therapeutic cargos. The values and licensing kind of numbers from that would be terms that are negotiated with partners downstream, so I couldn't comment on that side of stuff if that's what's referred to as success. But success from a technical point of view would be evidence of tumor reduction and targeted delivery.
Arron Tolley: I can comment on technical success, but not necessarily financial or commercial success at this current stage. It's too early.
Operator: That's great. Just turning to the next question. How much of the sales pipeline do you expect to convert?
Arron Tolley: That's a good question. There's been a notable uptick from GBP 4.8 million to GBP 7 million. That includes opportunities under negotiation. It's separate from the contracted work and/or recognized revenue. It depends largely on customer uptake. The reason that the pipeline has increased is because we've had an uptick in projects from customers, repeat business, 36% in particular that we referred to earlier. That's typically around companies spending, arguably, I don't know, say half a million, GBP 600,000 in or across three or four projects.
Arron Tolley: Given that companies are now regularly spending that kind of money with us, what we're looking to do here is say to them, "Well, if you're going to spend that kind of money across three or four projects with us per year already, why don't we have a risk-shared approach, and you pay us that money every year, but we do 10 to 20 projects for you per year, and we recognize the success on delivery?" That then opens us up to much more potential revenue from each of the companies without the company having to risk any more money than they're already spending.
Arron Tolley: This works very well for us because our success rates are reasonably high as a company, and it works well for the pharmaceutical companies evaluating new technology because they don't have to spend any more money than they're already spending, and then any extra cash comes from their budgets on success only. Those are the kind of multi-target deals that we're currently in the process of negotiating. How much of the pipeline do we expect to convert? Typically, at the later stage of discussions, we convert around half of our pipeline, if not slightly more than that.
Operator: Thank you. Just turning to the next question. You are working with some of the world's largest pharmaceutical companies. What will it take to turn these projects into larger, longer-term commercial deals?
Andrew Rapson: I can take that one.
Arron Tolley: Yeah, you can.
Andrew Rapson: Do you want me to take that one? I'll take it.
Arron Tolley: You can do. It is just really success in an area that they currently don't have success in, and that is not meant to be a glib answer. If we are looking to partner with a company for the delivery of drugs to the brain, for example, past the blood-brain barrier, then obviously, that would require data to demonstrate Optimer could deliver cargos through the blood-brain barrier to have an effect on, say, a neurological target. I don't know if you have got anything you want to add to that, Andrew, really.
Andrew Rapson: Just really the mix of opportunities that we have got. Something like Aaron is talking about there is going to be a longer-term prospect, a lot of hurdles to overcome. Something a lot simpler like the reagents for the enzyme modulation. I was working with a $10 billion company in Twist that went from discovery through to a product within 18 months. And that is a 10-year agreement that we have got there. They can potentially move quite quickly, but it really depends on which field it is in.
Operator: Thank you. Just turning to the next question here. You have multiple paths to revenue generation. How homogenous is the process for a binder in one area versus another? Essentially, how scalable is this?
Arron Tolley: It is reasonably scalable because, as I said earlier, most of the projects that we do undergo a standard process that we can run in parallel alongside other projects. Without getting too technical, we have a high throughput liquid handling robot that can handle multiple projects at once. When we set up the robot to undertake the customer's work, we tailor each of the selections to bespoke conditions for that particular project, and then the machine runs effectively through the night, basically undertaking that bespoke project for the customers all in parallel.
Operator: That's great. Just the final question we have here. Are any of these developments able to be patented and protected?
Arron Tolley: Yes. Pretty much all of the projects that we work on, that we solve a novel problem, the actual binders themselves that come out, the sequences, the validation data for that individual use case. Because the libraries that we use are enormous, we typically pan from a library that's around 1 times 10 to the 15 different molecules. So chances of getting an aptamer with an identical sequence more than once is nigh on impossible. So if the Optimers that we generate have a particular structure or a particular sequence that performs a particular function, then that can be patented alongside that. So the vast majority of what we do is patentable.
Operator: That's great. Thank you for answering those questions from investors. 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 I know is particularly important to the company, Aaron, can I please just ask you for a few closing comments?
Arron Tolley: Yeah. I'd just like to thank and show some appreciation for all the investors, both institutional and retail, that support the company, and look forward to updating you on future progress.
Operator: That's great. Thank you for updating investors today. Can I please ask investors not to close this session as you will now be automatically redirected to provide your feedback in order that the management team can better understand your views and expectations. This will only take a few moments to complete and-
