AGPU

Thank you for joining us today. This is Axe Compute's Q1 2026 investor presentation. Before we begin, I'd like to direct everyone to slide two, which contains our important legal disclosures and forward-looking statements. Please take a moment to review. Note that today's discussion includes forward-looking statements subject to the risks and uncertainties described in our filings. We'd encourage everyone to review our 10-K filed March 31st, 2026, and our 10-Q filed May 15t, 2026, for the full picture. With that, I'll now hand it over to our CEO, Chris Miglino, to get us started.

Thank you, Erin. Good morning, and thanks for joining us. I'm Chris Miglino, the CEO of Axe Compute. With me today are Josh Blacher, our outgoing Chief Financial Officer, and Jeremy Yaukey-Witter, our incoming CFO, and Kyle Okamoto, our President. Today, we're presenting our Q1 2026 earnings. We appreciate you taking the time to hear about the company. I realize that a lot of you may be new to our story, so today I want to tell you three things: what we do, why it works, and where we're going. Enterprises have been told to work with the constraints of whatever compute data centers happen to have available on their timeline, at their price, in their location. If you want GPUs, they tell you to get in line.

30, 36 to 52 week wait list and you have to take the region that the data center offers. You have to take the architecture they support. They want the off-takers, the renters of that equipment, to configure their business around what they can give you. That's the compromises that enterprises have been making in AI compute. We see it differently. We're partnering with businesses to build on their terms. Three things make that real. Choice. Any kind of GPU, any location, any configuration match, matched to the workload that the company needs. We are seeing customers wanting all kinds of GPUs, not just the latest GPUs that are out there. There is a gamut of customers that want stuff that has been out there for years. Enterprise, we handle sourcing, matching, logistics, our customers build around their businesses.

We have global reach. Our supply team is engaged with talking to data centers globally that allows us to deliver inventory that might be available very quickly, and then other customers that may wanna build custom build-outs at these different centers all over the globe. We're experts at going out and finding the power that's necessary, that is available for the off-takers to do what they need to do. The timelines at the bottom shows how fast we've executed on our plan. At the end of September, we launched the strategic compute reserve and enabling Axe to own tokens to buy compute. The best way to understand this is the same way consumers and teams can use tokens to engage with OpenAI and Claude, we use our tokens to buy bare metal compute. That turns into cash for the company.

That's why investors should view our compute reserve as additional cash. While it's not technically viewed that way from a GAAP perspective, we can turn those tokens into cash as needed and relatively quickly. We then rebranded and listed as AGPU on Nasdaq in December. In February, I started as the CEO. Even though it's new role as a CEO, I've been involved in structuring this entire transaction with the legacy public company and helping negotiate the terms with the legacy company and helping do the raise for the initial creation of the compute reserve. I'm well aware, and I was up to speed on the company. In February, we then closed $12 million in compute transactions, and then we closed a $260 million landmark deal in April.

We've assembled an amazing team that sells to off-takers, the people who rent the compute, and the team that sells to the data centers. I couldn't be happier with the team that we've assembled right now. Everything is working out great with the team. Let me tell you a little bit about this large transaction we did, because I know that we announced the transaction in a press release, but we've never talked about it. First off, it's the largest contract that the company has done in our history, albeit that, you know, we got going here since February of this year.

This is a foreshadowing of what we think is going to be the future for the company. The contract is a 36 month agreement for 2,304 NVIDIA B300s at 4.8 MW of dedicated N+1 redundant power in a U.S. Tier III data center. The targeted deployment is Q3 of 2026. This is all in progress right now. You know, the customer pays monthly in advance regardless of their utilization on a committed basis. There's obviously the power and the redundancy is there inside the data center. We signed and announced this deal at the end of April. The build is actively underway. The machines have been ordered, the power's been allocated, the hardware is being deployed. The first financial installment is expected to be received this month, and it's very substantial.

The revenue recognition for this transaction, when the cluster goes live, translates to around $21 million per quarter in revenue. That's done. That's once this thing gets installed, we'll be seeing $21 million every three months. If it, you know, if it launches in month two of the next quarter, we'll recognize two-thirds of that, but $21 million per quarter going forward for the next 36 months. We think that this model is what's gonna drive value for Axe and our cash flow and equity value. Let me show you a little bit about how that works. I want you to understand why enterprises choose Axe to partner with. The customer begins their workload size and regional location requirements to us. They bring them to us.

Axe does three things. We match the right GPUs, the right data center location, and all the supporting infrastructure, networking, power, rack, NVIDIA reference architecture, and so on. We help arrange the financing of the build-out. In some cases, there's SPVs that are created, and others we fully participate in the equity and the debt in the transaction. The consumers pay monthly in advance, usually with a 15%-30% prepayment upfront and the balance billed monthly in advance. At the end of it all, Axe owns the hardware that we provided the equity for. The equipment sits on our balance sheet as a hard asset. When the customer's terms ends, we are then able to redeploy that equipment to the next customer. We're able to utilize the capital to finance the equipment.

Think of it the way institutional investors think about data center real estate buildings. They amortize them over 30 years. We're doing the same with GPU clusters over three, sometimes even five. Every deal we close builds asset value on the balance sheet, not just cash flow. Even though these transactions are cash flow positive, they're eating down the debt that we put onto the equipment that we put in place when we deploy the clusters. As we grow, we can be seen as a virtual data center owner that doesn't own the buildings, but we own the equipment globally. And we've seen there is still strong demand for NVIDIA chips that came out three years ago. In fact, some older chips are being rented out now for more than they had two years ago.

The value of these chips that are amortizing off over the next three years will be significant at the end of that timeframe, is our prediction. With that said, I'll now hand the call over to Josh Blacher, our outgoing CFO. Josh has been an important part of the company's journey. I'd like to thank Josh, who has acted as fractional CFO for the company for some time now. The company's at a point where we're ready for a full-time dedicated CFO. While we'll miss Josh and appreciate his contribution, we're excited to welcome Jeremy as the new CFO of the company. Josh.

Thank you, Chris. I've had the pleasure of serving the company as Chief Financial Officer since September 2023. As previously announced, this will be my last earnings call as I transition out of this role. I'm excited to introduce my successor, Jeremy Yaukey-Witter. Jeremy, congratulations on this new role. The company is in excellent hands. Jeremy will walk you through the financials for our first quarter ended March 31st, 2026. Jeremy.

Thank you. Thank you, Josh. I'd first like to take the opportunity to thank Josh for his service to the company. We appreciate the foundation he's helped establish and which I'm excited to build on. To everyone listening, it's a pleasure to join you today. I started with the company three years ago and previously served as the company's controller. The foundation of my career was built at KPMG, where I provided audit and attestation services to publicly traded and private companies across various industries, including technology and energy. I've been along for each step of our strategic transition, and I'm thrilled about the direction in which the company is headed.

Before I go through the numbers for our first quarter ended March 31st, 2026, I want to frame what you're looking at in our filings because our financial statements for the first quarter reflect the transitional state of our business at that time with two different segments at very different stages. They also contain certain non-cash items that I want to make sure are clearly understood. Looking at our income statement, our reported net loss for Q1, 2026 was $7.7 million. I want to explain that number up front because much of it is non-cash in nature and driven by accounting rules that require us to mark our digital asset holdings to market every quarter. Specifically, we recorded $4.3 million in losses on digital assets during the quarter.

Under U.S. GAAP, our Aethir token holdings are carried at fair value at each reporting date, with changes flowing through the income statement. The price of the Aethir token declined during the first quarter, which resulted in a $4.3 million non-cash mark-to-market loss on our token holdings. Setting aside that digital asset fair value adjustment, our underlying operating loss was approximately $3.4 million, reflecting our operating cost structure as we continue to transition the business to focus on our compute services segment. Total revenue for Q1 2026 was $35,000 compared to $110,000 in Q1 2025. The year-over-year decrease reflects reduced sales in our legacy drug discovery services business, which remains in continuing operations as we evaluate strategic alternatives.

Our compute services segment contributed minimal revenue in Q1 2026 related to just a handful of compute contracts that commenced at the end of March. In line with U.S. GAAP, we recognized revenue on our compute contracts ratably over the service period. Our contract liabilities, representing customer prepayments received ahead of revenue recognition, increased from $144,000 at December 31, 2025 to $786,000 at March 31, 2026. Approximately $650,000 of that balance was related to compute services and represents contracted revenue that will be recognized as compute services are provided in subsequent periods. Total operating costs and expenses were $3.5 million in Q1 2026 compared to $2.4 million in Q1 2025.

Q1 2026 expenses were primarily driven by general and administrative expenses of $2.9 million, up approximately $1.1 million from Q1 2025. The primary driver was a one-time recognition of severance expense to our former CEO following his departure in February and the board's appointment of Chris to the CEO role, along with other personnel-related costs. On a per-share basis, the net loss was $0.36 per share based on a weighted average share count of approximately 21.2 million shares. In accordance with U.S. GAAP, that weighted average share count included the 14.7 million pre-funded warrants which remained outstanding as of March 31, 2026, down from the 16.8 million pre-funded warrants that were originally issued pursuant to our October 2025 private placements.

We'll now turn to cash flows in the balance sheet. The company's cash and cash equivalents decreased by approximately $3.9 million during the quarter from $10.8 million at December 31, 2025 to $6.9 million as of March 31st, 2026. The decline reflects our operational spending during the quarter. Cash used in operating activities was $3.7 million in Q1 2026 compared to approximately $1 million in Q1 2025. The increase primarily reflects increased cash used in working capital and increase in cash operating expenses. Cash used in working capital primarily reflected payment of outstanding accounts payable and accrued expenses. Increased cash operating expenses primarily reflected cash payments for additional professional services resulting from the company's adoption of its treasury strategy in late 2025.

The company's cash used in investing and financing activities was insignificant during the first quarter while the company focused on transitioning its operations. Our digital asset holdings had a fair value of $20.2 million as of March 31st, 2026. That compares to $24.4 million at December 31st, 2025. The decrease primarily reflects the mark-to-market adjustment I described earlier, directly tied to the decrease in the market price of the Aethir token during Q1. Our digital asset receivable had a fair value of $15.4 million as of March 31st, 2026, representing our contractual right to receive additional Aethir tokens in future periods pursuant to time-based vesting conditions, also referred to as locked Aethir tokens. These locked tokens vest on a predictable schedule through December 2028.

Of that total, $9.4 million was classified as current, representing tokens expected to vest and be claimed within the next 12 months, and $5.9 million was classified as non-current. Something I'd like to once again draw your attention to is the company's accounts receivable and contract liability balances, which you'll see each jumped by more than $600,000 from December 31st to March 31st. This jump reflects billings for non-cancellable and non-refundable monthly prepayments due from our compute customers. These billings reflect the traction that the company saw at the end of the first quarter as we began successfully closing contracts with customers. Total assets as of March 31st, 2026 were $45.2 million compared to $52.9 million at December 31st, 2025.

Total liabilities were $5 million and total stockholders' equity was $40.3 million, down from $47.7 million at the prior year-end, with the change driven primarily by the $7.7 million net loss for the quarter. I'll now turn the call over to Kyle Okamoto, our president, to discuss our business efforts.

Thanks, Jeremy. six weeks into the job now, I will say that I am even more fired up and excited about this market and this company's future. Today I'm going to cover three things. One is how our business model has evolved to support our customers. Second is the Axe Build delivery model in depth. The third is our pipeline, where the numbers are powerful, to say the least, I think they tell a very compelling story of where this business is going. All right. The first is, you know, how customers grow with Axe. We really have two tracks for engaging with customers. You know, the access available now compute, we will build out a dedicated cluster. Right? Path one and path two. Most customers enter through Axe Compute's immediate access inventory. It's fast.

They leverage our existing compute network. They can start in as little as 24-48 hours. These clients come to Axe Compute because they have an immediate need, and they can't find what they need through traditional hyperscalers or even other neo clouds. The triggers are very consistent. It's not just wait lists of 36-52 weeks. It's also the type of inventory they can't find elsewhere, the locations that they need to meet their own customer expectations like data sovereignty and inference performance, and of course, the pricing transparency that all clients in this world should expect, and then the level of service that they ultimately deserve. Track 2 is our build program that Chris talked about with the $260 million landmark deal. These customers are looking for large and dedicated infrastructure coverage in a specific footprint.

They want to partner for the entire build-out, both technically and financially. They come to us for our expertise and ability to find the space and power, finance and source the chips and other equipment, manage the build-out and operations end to end. These engagements are typically three or five years, with cost efficiency as a priority and of course enterprise-grade SLA requirements throughout. Across both of these tracks or paths, customers value the same things, right? They want choice. They want to be able to get what they want, when they want it and how they want it. They need expertise and support, and ultimately global reach because the world is a very flat place nowadays and you need to be where your customers are, you need to support data sovereignty, and you ultimately need to have very high performance requirements.

The fourth is really our service. Our job is to make sure that regardless of how clients want to engage, clients never have to go anywhere else. Whether they stay on track one or move to track two, the experience, the support and the relationship are seamless. Now, let me walk you through what it actually means for Axe Compute to deliver a large cluster like the $260 million deal. Some may question, you know, why would somebody choose Axe Compute for something this big? The answer is that we have a full infrastructure partner relationship. We are not a vendor here. Here's what it really looks like across these six steps. From an architecture perspective, we design the full solution with their needs at the center.

That could be what type of GPUs, what type of CPUs, what type of onboard storage, high-speed shared storage, what network fabric choices, private and public networking, power and cooling, rack layouts, ancillary services, take Kubernetes or Slurm as an example. It's really all in the aim to build a true AI factory for our clients. The customers tell us what they need, we figure out how to get the job done. Second is financing and procuring. Axe funds the build. We source the hardware, NVIDIA B300s, Grace Blackwell GB300s, whatever the job requires. We deal with orchestrating lead times of various components, all with transparency so clients know what they want to know throughout the process. The customer does not have to bring their own CapEx, we're providing this on an OpEx model.

We of course secure data center space and power in the right location, making sure that we have right of first refusal to support expansions for our customers, making sure that we provide N+1 redundancy to support enterprise-grade SLAs or higher. You know, really all match the data sovereignty and performance requirements. Of course, we've got to build, deliver and support, which is happening now. We install, test, hand over, provide response times, resolution times, SLA, ticketing system integrations, et cetera. Of course, using NVIDIA reference architecture, we make sure that the client is very much involved in that process from the get-go. Another unique point of Axe Compute is that we offer an upgrade path, customers can move to the latest GPU architecture during the term.

We don't want to lock them in on an older GPU generation and not allow them to move to the latest and greatest, to keep up with the market innovation and growth. With of course, Axe Compute supporting that growth. At the end of the day, Axe Compute then owns the hardware. Right? At the end of an Axe Build, the equipment is on our balance sheets as a hard asset. We own it, we can redeploy it, we can provide GPUs as a service to different clients. Every deal builds that asset base. That last point is really what makes this business model attractive beyond just positive cash flows, right? It's repeatable and it compounds. Let me talk about the pipe. Before I show you the pipeline. Oh, here it is. Let me set the market context here, right?

Because these numbers matter. We're operating in a market that people like McKinsey and Gartner estimate has already crossed $1 trillion in AI compute in 2026. That's with a T, trillion. It's growing at a 30%+ CAGR through 2034. Total data center CapEx is, you know, projected to be over $6.7 trillion through 2030, from McKinsey. Obviously the demand is there and it's showing no signs of slowing down. It's quite the opposite actually. Now here's what that demand looks like in our pipeline after just a few months of operating, as Chris mentioned, really starting this business earlier this year. And of course, after closing our first large Axe Build deal, in my first three weeks at the company, that obviously accelerates quite a bit on the pipeline, right?

I want to be clear here, this, a pipeline is a pipeline, right? These are qualified prospects, not signed contracts. Not all of them will close. We share this because we believe it's material context for understanding the opportunity in front of us, not as a forward-looking commitment to any specific revenue outcome, right? This is a sampling of, I think there's 45 prospects in this more advanced pipeline stage. That's representing about over 36,000 GPUs. Of that mix of GPUs, 72%, so about 26,000 GPUs are Blackwell requests. Blackwell, Grace Blackwell, B200s, B300s, GB200s, GB300s, et cetera. That really shows that our clients want the most powerful compute in the world right now for their cutting-edge use cases and innovations that are ultimately reshaping and touching every aspect of the world.

This is a pipeline total contract value across these qualified deals of over $4.3 billion. What's interesting here is that the commitment length mix is very telling. The majority of these deals trend toward 36 and 60-month commitments. Customers understand that it's very important to secure critical AI infrastructure to power their businesses, and they are willing to commit to that to ensure that they have a secure and steady supply of compute to power their businesses. These are not spot requests for a few hours or a few days. Enterprises are making these long-term infrastructure decisions and looking for a true partner.

The bottom line here, if we close, let's say, three or four of these deals this year, you know, that's $hundreds of millions in incremental contracted revenue on top of the $260 million already signed. We're quite excited. That's definitely one of our key focuses. With that, I will hand it back to Chris for closing remarks.

Thanks, Kyle. Kyle and the team have been doing an amazing job. We're, we're setting the foundation for long-term success at the company. We're at the right place at the right time, more so than anything I've ever seen in my career. The deals we're making now will make the company for years to come. I think that the transactions that will get done this year will provide revenue that will be substantial, you know, over the next three to five years. We don't see that slowing down at all. Our, our approach is, it's scaling fast. You know, we're not the data center, but we're the company that builds and owns what's inside the data center. I know we've covered this point a lot, but the first deal that we've done has opened a floodgate of opportunities for us.

In addition to the $21 million a quarter that that particular transaction will bring, it's led to a pipeline of over $4.3 billion, if you missed that in what Kyle said earlier. You know, I've publicly said that I believe that we close around $1 billion in transactions this year. You know, seeing the pipeline numbers that are with the team, I'm very confident that that will happen. Off-takers or people that rent the equipment like our model, and they wanna work with us. You know, the most important part is building asset value. It's the part that matters the most for investors thinking about long-term value. Our two tracks add meaningful revenue assets to our balance sheet. With Axe Build, every cluster we deploy adds owned AI infrastructure to our balance sheets.

Assets that amortize over the term and redeploy to the next customers. We're not just generating cash flow, we're building a company with a strong foundation for the future. With that said, I wanna thank you for your time and your consideration and interest in Axe Compute. I think that, you know, obviously the numbers that are reflected in this first quarter are not representative of the business itself, and you'll start to see that kick in the second and third quarters of this year when the model that we've put in place truly starts to reflect to the income statement, cash flow and to the balance sheet. Thanks for being with us here today, and we appreciate your time.

Good morning, everyone, and thank you for joining us today for Axe Compute's Fiscal Year 2025 Investor Presentation. Our common stock trades on Nasdaq under ticker symbol AGPU. On today's call, you'll hear Christopher Miglino, our Chief Executive Officer, Kyle Okamoto, our President, and me, Joshua Blacher, our Chief Financial Officer. Before we begin, I'd like to direct everyone to slide 2, which contains important legal disclosures. Please take a moment to review those. With that, let me hand the call over to Chris. Chris?

Hi guys. How are you? I'm excited to start as the new CEO of Axe just over 30 days ago. What we've accomplished in the last 30 days is quite remarkable. I'll get to that in a little bit. In September of 2025, we launched our strategic compute reserve, our GPU capacity platform. By December, we initiated a strategic expansion into AI infrastructure and rebranded as Axe Compute on Nasdaq. In February of this year, I stepped into the CEO role, and just this month, effective March 26th, we added two exceptional industry leaders to our board, Theodore Zhu and Thorsten Dirks. Theodore Zhu is a semiconductor pioneer with over 85 patents in the United States, the founder of Iotelligent Technology, and former president CEO of Celestial Semiconductor.

Thorsten Dirks is one of Europe's most accomplished technology executives with nearly two decades of board experience and former CEO roles at Telefónica Deutschland, Lufthansa Eurowings, E-Plus Group, and Deutsche Glasfaser. Together, Zhu and Dirks bring more than four decades of combined experience spanning semiconductor innovation, large scale telecommunication transformation, international M&A, and enterprise digitization. I'd also like to announce today that Kyle Okamoto is starting as the president of the company, and we're very excited to have Kyle join us. We're now entering the execution phase of the company, in which we will which will demonstrate how our vision of being a leader in the compute market will take shape. I also briefly wanna address our drug discovery services legacy segment.

Strategic options are under evaluation, and we'll share more of that process as it develops. Now let me expand on our vision. Our mission is simple. We're bringing choice to the market. GPU compute has become one of the most precious commodities in the global economy, and yet access to it has been gated, slow, expensive, and concentrated in the hands of a few hyperscalers with wait lists that stretch 36-52 weeks. We're changing that. Axe Compute gives enterprises three things that they can't get from the incumbents. First, we have choice, any GPU, any location, any configuration matched to your specific workload. You're not locked into a single provider's hardware catalog. Second is speed. We can develop it in as fast as 24-48 hours, subject to availability, not weeks, not months, but days.

That means you can innovate, experiment, and pivot in real time. Third, distribution. With 200-plus global locations across our network, we can meet enterprises where they operate and where their customers are, respecting data sovereignty requirements along the way. This is a platform we're building, and the market is just enormous. I want to direct your attention to a significant change. We've executed approximately $12 million in total contract value over the last month or so, subject to deployment and performance terms. We're entering Q2 with an expected monthly contract value of approximately $850,000 as deployments come online. That translates to $7.7 million in contracted 2026 income signed at this time. We now have more than 20 enterprise customers with over 30 active deployments live.

I just want to reiterate that we've signed $12 million worth of contracts for the business, and we're, you know, continuing to sign more, but we're off to a great start. I also want to speak to the quality of this income because not all income is created equal. Every contract on our books is structured with partial payments in advance. Customers commit to reserve capacity on a monthly basis. The structure is designed to reduce receivable risk. Many contracts include advanced payment components prior to compute delivery. These contracts are structured to support recurring enterprise income across all NVIDIA companies and established enterprise verticals, covering a diverse hardware mix, including H100s, H200s, B200s, RTX 5090, and RTX 5090 clusters.

The breadth of GPU coverage reflects the breadth of enterprise AI use cases we're serving. As you know, we've launched the compute reserve, the strategic compute reserve. The reserve provides us with tokens that can be used to purchase compute on an ongoing basis. What you see on the slide is a value of that compute reserve. As of this presentation, current market cap of the company is approximately $8.6 million. The value of the strategic compute reserve is $43 million. This is based on March 27, 2026 pricing, the timing of the preparation of this presentation. The token that makes up our compute reserve is the AI infrastructure token ATH. Note that ATH token prices are naturally volatile, as are many cryptos.

The value of as of March 27 reflects a point in time price, and that price will move, you know, we just want you to make sure that you're aware that there's a lot of volatility there. The MNAV ratio is a multiple of the market cap. Currently, it is 0.2 and on a fully diluted basis, it is 0.79. At the current levels, the public market implies a valuation below the reserve value before assessing any value for the operating business or the contracted income that we just discussed on the previous slide. Keep in mind, MNAV is a non-GAAP metric and should not be considered a substitute for GAAP financial measures. Refer to Axe Compute's 10-K for further details on any discounted valuations.

On the compute reserve, we currently have 5.9 billion tokens, which is made up of 2.86 billion unlocked liquid tokens and an additional 3.12 billion tokens that are locked with a monthly unlock cadence running through December 2028. We're not telling investors what the discount should be. We're presenting the numbers and letting the market form its own view. In our opinion, the operating business and early commercial traction you saw on the prior slide is not reflected in the $8.6 million market cap, and we believe execution over time may help close this gap. Investors should keep in mind that AX has the ability to convert these unlocked tokens into cash through the purchase of compute that we then resell.

Let me talk to you a little bit about what that business model looks like. The commercial traction you just saw is real. The slide explains why it's structurally durable. Our model has four components, and they work together in a flywheel, not as independent features. Reserve GPU capacity. Customers commit to reserve clusters priced per GPU per hour with monthly payments in cash in advance, and usually with prepayments on long-term contracts. That eliminates pricing volatility for the customer and receivable risk for us. We get paid before compute is provided. Distributed provider network, 200+ global locations and many providers. Customers get location choice and data sovereignty. Your AI infrastructure isn't constrained by where we've built. We meet you where you operate. OpEx models for customers.

Axe can finance and build dedicated infrastructure, including B300 clusters, so customers get the capacity they need without carrying CapEx on their balance sheet. In an environment where every CFO is scrutinizing capital commitments, that is a meaningful commercial advantage. Strategic compute reserve. As we utilize the capital from these stakes to purchase more ATH, our strategic compute reserve, we may receive up to a 20% token-based incentive, depending on network mechanics. The model is designed to grow the reserve over time. The reserve expands capacity. Expanded capacity enables the next deal. Customers pay us in cash. We use the cash to purchase ATH tokens, and we use that then to buy compute. We may receive additional ATH tokens, currently targeted at up to 20%, depending on network mechanics that can be used to buy more compute in the future.

I just wanna make sure that everybody's clear. Inside our business, the amount of money that you saw on the earlier slide that we have in the strategic compute reserve can be turned into cash through selling that, utilizing those tokens to purchase compute and then reselling that compute to our customers, thus generating cash for the company. Now I'd like to turn the call over to Josh Blacher, our CFO, who will give an overview of the financials for 2025. Josh?

Thank you, Chris. Before I walk through the financials, I want to address something important up front. Our fiscal year 2025 income statement includes two large non-cash items that significantly affect the reported net loss figure and are not reflective of our underlying operational performance. I'll explain both clearly and then walk through the underlying results. First, we recorded $152.5 million in losses on digital assets at fair value. Under ASC 350-60, which we adopted effective January 1, 2025, digital assets are carried at fair value at each reporting date, with that mark to market flowing through the income statement. The ATH tokens we acquired through December 31, 2025 at a cost basis of $102.7 million declined in market value to $24.4 million at December 31, 2025.

A $78.3 million unrealized decline on those holdings, which is non-cash. The tokens remain on our balance sheet. Second, we recorded $52.7 million in losses on derivative instruments. This relates to the Crypto PIPE transaction executed on September 29, 2025. Because the value exchanged involved ATH tokens rather than a fixed dollar amount, US GAAP required us to treat the contract as a derivative liability at fair value through earnings. Evaluation was performed to measure the change in fair value of the instrument between execution on September 29, 2025, and on settlement on October 7, 2025. When the deal closed on October 7, the derivative liability was derecognized and the ATH tokens were recorded as assets, while the pre-funded warrants as equity. The $52.7 million reflects the fair value movement between September 29 and the settlement on October 7.

Again, entirely non-cash. Please keep in mind that together, these two items account for $205.2 million of our $233.1 million net loss. Full year 2025 income statement highlights. Revenue from continued operations for the fiscal year ended December 31, 2025 was $125,000, compared to $85,000 in fiscal year 2024. This revenue is entirely attributable to our legacy drug discovery services business segment. Our compute services segment did not generate revenue in 2025, as our go-to-market pipeline was still being developed during the company's strategic transition. We expect compute services to be a meaningful contributor beginning in fiscal year 2026. Total operating costs and expenses for 2025 were $28.6 million, compared to $10.4 million in fiscal year 2024.

On a per-share basis, the net loss was $13.37 based on a weighted average diluted share count of approximately 17.4 million shares. The weighted average share count reflects the significant share in pre-funded warrant issuances associated with our PIPE transaction during the fourth quarter of 2025. Balance sheet highlights. Turning to the balance sheet, we ended fiscal year 2025 with $10.8 million in cash and cash equivalents, compared to $0.6 million at December 31, 2024. This is driven by the proceeds of our PIPE financing transactions in October 2025. Our balance sheet now includes two new asset categories that did not exist a year ago. First, digital assets of $24.4 million, representing our 2.8 billion ATH tokens on hand.

Second, the digital asset receivable of $15.5 million, representing our contractual right to receive additional ATH tokens in the future pursuant to time-based vesting conditions, also referred to as locked ATH tokens. Those tokens are expected to unlock on a predictable schedule through December 2028. Total assets as of December 31, 2025 were $52.9 million, compared to $5.0 million for the prior year. Stockholders' equity was $47.7 million at year-end, compared to a deficit of $0.2 million at December 31, 2024. The restoration of equity to positive territory and our regaining of compliance with Nasdaq stockholders' equity requirement in December 2025 were significant milestones for the company. This concludes my financial review. I'd now like to turn the call over to Kyle Okamoto, our President, to discuss the company's compute strategy and near-term pipeline. Kyle?

All right. Thanks, Josh. Appreciate that. Fired up this morning. Good morning, everyone. I'm absolutely thrilled to be here to walk you through how our business actually works and why the market dynamics are so favorable for what we're building. Let's start with the market. I would say this in brief: we are in an AI supermarket. Right. Super cycle of AI. In 2026 alone, Gartner projects AI spending will reach $2.5 trillion, with a T. AI data center spend is expected to grow at over 31% annually by 2030. In 2026 alone, global AI infrastructure CapEx exceeds $1 trillion, up from just $290 billion two years ago. That's massive growth.

An accumulative projected spend of $6.7 trillion by 2030, sourced by a bunch of reputable research organizations, and I think everybody overall in this space that spends day to day will think that those numbers are just far too low. The structural shift, though, is what matters most for Axe Compute. AI workloads grow from 25% to 70% of all global data center activity by 2030. That's tripling the share of workloads within data centers in just four years. That's not just more AI. That's a fundamental shift and recomposition of what compute infrastructure is really for. I would say four things are driving this paradigm shift. One, hyperscaler CapEx is running at $600 billion combined entering 2026. 97-97 GW of new capacity are coming online through 2030.

Three, inferencing is now overtaking training as the dominant AI workload by 2027, meaning distributed latency-sensitive compute that cannot just run in three U.S. regions. Has to be where people are, where applications live, where agents live, et cetera. Lastly, enterprises are actively moving toward bare metal performance as they get smarter and more capable of using GPU-based compute and away from hyperscaler abstraction. We, Axe Compute, are positioned directly in the path of this shift. Let me walk you through how we actually serve customers. When you put Axe Compute side by side against the public Neocloud segment, the contrast is pretty striking, and frankly, the investment case becomes very clear. Our distribution model, as Chris mentioned, spans over 200+ locations, over 100 different configurations. That's choice.

Our competitors are largely operating in a single country or maybe a few data centers in limited regions, usually with a single configuration stack. Axe Compute has anchored around providing choice in a highly centralized and consolidated market. We also target deployment timelines as fast as 24-48 hours or sometimes faster, right? Of course, subject to availability. This is versus, you know, weeks and months, like Chris mentioned, for the rest of the market, right, the overall market. We're primarily leveraging an OpEx model, and that allows for very predictable economic scaling, but ultimately less drag. We don't have to spend 18 months building out a data center. We work with partners that are building out data centers. Our peers require heavy CapEx infrastructure investments to keep up with sales. We can meet that demand now across a very wide net.

We're designed from the start to deliver 100% bare metal performance in tier three and tier four data centers backed by enterprise-grade SLAs designed really to support those high-performance workloads. Our peers obviously offer a mixed bag of virtualized environmental solutions, but ultimately, we're built from the ground up for this high-performance enterprise-grade workload. Look at valuation. Our basic market cap, as Chris mentioned and Josh mentioned, $8.6 million. Neocloud peers range from hundreds of millions to more than $38 billion as of a couple days ago. Our peers are trading at 7-15x revenue, right, P/S. We're trading at roughly 1x expected income from signed contracts, 1 versus 7-15, against a $52.9 million audited asset base.

The bottom line here, as the slide says, "The market is not yet pricing Axe Compute as a Neocloud with real income and real assets." We believe that changes as we continue to simply execute. Let me walk you through the pipeline and some deal economics. One of the questions we get from investors is, how predictable are income streams? Let me walk you through an example of that to highlight the more detailed mechanics of our business. For example, a 10-node H100 cluster on a 12-month commitment generates around $1.3 million in ARR. Gross margin on a deal like that runs around 8%, maybe a little higher. Customers prepay in advance 10% of the total contract value at sign. That shows a commitment to stick around for the full 12 months, and put money on the table.

They also pay the first month's rent in advance, which means we have cash in hand before we tie up compute resources. Each settlement then may generate additional ATH token incentives, currently targeted at that up to 20% level that Chris mentioned, which then compounds the strategic compute reserve. Our COGS each month, for the next month that we book that compute, get 20% cheaper, and that compounds over and over. Income is priced at a per hour per GPU rate on a reserved capacity basis, so clients get a consistent bill each month with no hidden fees. We've built Axe around what's wrong with the centralized cloud world today, and one of those key tenets is you get a surprise bill at the end of the month, and you don't know where your spending is.

You don't know what you're paying for egress or hidden storage charges or API calls or, you know, service tickets or things like that. So no hidden fees. Contracts are typically 6-12 months or longer and always with monthly advanced payment. This structure is really designed to reduce receivables exposure, but also to give customers predictability in their underlying economics and align with their monetization models. Of course, we also have ancillary upsell services like shared storage. Think, you know, things like VAST or WEKA, CPU nodes, when customers have larger clusters for orchestration, or things like managed Kubernetes that is simply out of the box on a software and API basis. These things all can bolt onto a deployment, ultimately driving up margins and stickiness with clients.

What this creates is really a business where contracts are structured to include upfront payment components prior to deployment. Contracts are long-term, contracts are recurring, and every deal simultaneously grows both our P&L and our token reserves. That's that compounding model. That's that flywheel that Chris was talking about. It's not a linear model. Let me shift to how customers actually get started with AX and how they can grow over time. We basically serve customers through two main approaches, and there's a pathway between them. One is what we call start fast. It's designed for speed, it's designed for experimentation, and ultimately, it provides massive choice.

Clients can get running in less than a day, 24-48 hours on average, across any GPU type, any configuration, all 200+ locations with flexible term lengths, full bare metal performance from day one. This is the lowest friction on-ramp in the market. They can see all of our selections. What's available, where is it, what the network and the configs, and all the little details that they need and care about most. In most cases, they can, you know, easily try that out before they buy. Tier 2 is what we call AXE Forge, and it is for enterprises who want to scale very strategically with a larger cluster. Here we have either our partners or Axe ourselves can cover the CapEx build costs, so customers can still stay on that OpEx model, even at significant scale.

We're talking thousands of high-end B300 GPUs, for example. We use NVIDIA reference architecture design. We can offer, you know, service-level commitments if we deploy late to stand behind our commitments to deliver that cluster on time, and at the performance levels that client expects. We also allow clients to upgrade during the committed term as technology evolves to the latest and greatest GPUs. The whole point is to structure a long-term partnership, not a vendor transaction with rigid lock-in, allowing customers to grow and to excel and to exceed over time. Customers can also move from tier one to tier two as their needs grow, right? With no disruption, no penalty, no lock-in. That's the whole intention of this model. In short, we wanna grow with our customers, not trap them.

I hope that was helpful, and with that, I'll hand it back to Chris to close us out.

Thank you, Kyle. We're really excited to have you join the company, and we look forward to you bringing your expertise in this area to the Axe Compute family. I wanna cover a couple of things in closing. You know, this is a massive market. It is growing faster than anything I've ever seen in my entire life. It reminds me of when the Internet started, except the demand is persistent, and I think that we are just at the forefront of companies getting into this space. I think that, you know, a lot of people have embraced AI, but I still think that there is a world of companies out there that are just starting to get into it. I think that we're, you know, well.

We're well-positioned to take care of those people as they come online throughout the world and do it quickly. We have, in the last 30 days, signed $12 million worth of contracts. That's a lot of money for a 30-day run, and we're just getting started there. That brings us around $835,000 on a monthly contract value, and that's over 20 different customers. I could tell you that, you know, there's a lot more that's in the pipeline that we're seeing out there. We're bullish on what we're seeing here.

The idea that we can continue to use the tokens that we have to go out into the market and turn that into compute, which then turns into cash, I think is something that investors really need to understand. Because this provides us with the ability to not have to go to market to raise additional capital. In addition to the cash that we have on hand, we also have the strategic compute reserve that can also turn into cash by turning that into compute. As you become more familiar with our business, I think you'll start to understand the true value of that compute reserve and how we can gain additional tokens from participating in buying more of the ATH tokens over time.

I think if anybody's interested in setting up a one-on-one call with us, we would welcome having the conversation. You can reach out at [email protected]. I would, you know, I'd like to thank the investors that have come along with us on this journey. If you do have any questions, please let us know. Hopefully today's presentation gave you a little bit more insight into where we are and to where we're going. Thank you for joining us today.

Good day, and thank you for standing by. Welcome to the Predictive Oncology Second Quarter 2024 Earnings Conference Call. At this time, all participants are in a listen-only mode. After the speakers’ prepared presentation, there will be an opportunity to ask questions. Please be advised that today’s conference is being recorded. I would now like to hand the call over to your speaker, Mr. Glenn Garmont, Investor Relations. Thank you. You may begin.

Welcome, and thank you, everyone, for dialing into the Predictive Oncology second quarter 2024 financial results call. First, you’ll hear from our Chief Executive Officer and Chairman of the Board, Raymond Vennare; and our Chief Financial Officer, Josh Blacher, who will review our financials. Certain matters discussed on this call contain forward-looking statements. These forward-looking statements reflect our current expectations and projections about future events and are subject to substantial risks, uncertainties and assumptions about our operations and the investments we make. All statements other than statements of historical facts included in the call regarding our strategy, future operations, future financial position, future revenue and financial performance, projected costs, prospects, plans and objectives of management are forward-looking statements. The words anticipate, believe, estimate, expect, intend, may, plan, would, target and similar expressions are intended to identify forward-looking statements, although not all forward-looking statements contain these identifying words. Our actual performance may materially differ from that contemplated by the forward-looking statements as a result of a variety of factors, including, among other things, factors discussed under the heading Risk Factors in our filings with the SEC. Except as expressly required by law, the company disclaims any intent or obligation to update these forward-looking statements. Now I’d like to turn the call over to Raymond Vennare, Chief Executive Officer. Raymond?

Thank you, Glenn, and good morning, everyone. I would like to begin this morning with a recap of a significant announcement that we made just a few weeks ago regarding the successful retrospective multiyear ovarian cancer study that we completed with UPMC Magee-Womens Hospital conducted over the past five years. As a result of this study, the findings of which were presented at the American Society of Clinical Oncology Annual Meeting in June, we have expanded our artificial intelligence and machine learning offering to independently pursue the discovery of novel biomarkers that can predict patient outcomes and drug responses in oncology. With these capabilities, we are very well positioned to play a significant role, not only in validating biomarkers that have already been discovered by potential partners, but also in discovering our own unique biomarkers and playing a more active and direct role in drug discovery and development. Please recall that the Magee study was designed to identify key features that drive overall survival endpoints in ovarian cancer, a very serious cancer type with a very high rate of recurrence. This study included data from 235 ovarian cancer patients from 2010 through 2016, a broad array of inputs, including patient data, whole exome sequencing, whole transcriptome sequencing, drug response profile and digital pathology profiles were used to train the 160 models that were included in the study. As we previewed during our first quarter conference call, we were able to obtain an end-of-life data that supports novel ovarian cancer biomarker discovery and development. We are very pleased to report that we were able to deliver strong predictive models with high levels of accuracy, and our machine learning capabilities demonstrated the ability to identify prognostic subgroups within ovarian cancer patient population. This progress represents a natural extension of our core artificial intelligence capabilities, where we employ our active machine learning and diverse patient tumor samples preserved in our extensive biobank to predict responses to drugs with a very high degree of accuracy. We are now taking this one step further by applying state-of-the-art deep learning approaches for biomarker discovery for both overall survival and drug responses. This includes our ability to extract differentiating features from our digitized pathology slides, which, in and of themselves, are potential biomarkers. Our platform now enables us to pursue deep learning as a methodology to accelerate the initial stages of biomarker discovery and stratify patient cohorts and further extend our capabilities, either independently or in partnership with our biopharma companies. Ovarian cancer represents a significant unmet need in oncology, with epithelial ovarian cancer being the deadliest of all gynecologic malignancies. While these cancers are sensitive to front-line chemotherapy in approximately 75% of cases, these women will ultimately experience disease relapse in an equal percentage, which is incurable. Outside of primary chemotherapy, there is no universal treatment decision path to determine the agent, sequence and timing of the standard of care for chemotherapeutic agents. These capabilities extend well beyond ovarian cancer and can be used in the discovery of biomarkers for other cancer types as well as diseases outside of oncology. External sources have valued the biomarker discovery market at more than $51 billion in 2024. So this is a very significant opportunity for us to leverage our unique set of assets and capabilities to play a role in the discovery of next-generation therapeutics, while creating enduring value for our shareholders. We look forward to further validating these capabilities through development collaborations with leading biopharmaceutical partners and health care networks. Also during the second quarter, in addition to our biomarker discovery initiative, we launched a novel organ-specific 3D cell culture technology that more closely mimics human tissue architecture than 2D assays. It does this by preserving critical interactions between a tumor and its cellular and extracellular surroundings and creates a more representative method for in vivo clinical testing for drug candidates. This allows for more robust predictions of clinical outcomes and can be used to optimize candidate selection for subsequent clinical development. The potential benefits to drug developers are numerous. They decrease the cost of new drug development and the time to market, but also reducing the need for animal testing and time-consuming iterations during clinical trials. The 3D cell market is estimated by third parties to grow 14% annually from $1.4 billion in 2022 to $5.3 billion in 2032. Also worth mentioning is the progress that we have made with our Accelerating Compound Exploration program, otherwise known as the ACE initiative. This program, as you may remember, is geared toward novel discovery through partnerships with universities and academic institutions and was created to provide early-stage academic development groups access to Predictive Oncology’s artificial intelligence platform, which, as you also know, leverages our extensive and diverse biobank of heterogenous tumor samples. The ACE program is designed to enable academic investigators to evaluate their drug compounds and facilitate more informed selections of drug tumor type combinations to increase the probability of future clinical success by efficiently addressing tumor heterogeneity earlier in development. This program, which we have been nurturing for more than a year, has resulted in our first collaboration with the University of Michigan. The library created by University of Michigan’s Natural Products Discovery Core is one of the largest collections of pharmaceutically viable extracts in the United States. This library which has been meticulously constructed over the past decade, in the laboratory of Dr. David H. Sherman at the University of Michigan’s Life Sciences Institute, is comprised of strains from Asia Pacific, Middle East, South America, North America and the Antarctic. Most importantly, this collaboration represents Predictive Oncology’s foray into true drug discovery. With the addition of University of Michigan’s natural products and drug candidates, we are very well positioned to expand our small molecule capabilities to include development of large molecule models using our proprietary AI and ML platform. Several publications will definitely come out of this drug discovery initiative. To ensure that we remain nimble and able to capitalize on this and other new opportunities that continue to emerge, we announced more recently that we implemented a comprehensive and strategic cost reduction initiative aimed at streamlining our operations and extending our cash runway. As a key part of this initiative, we made the challenging decision to consolidate our Birmingham operations, which houses our Biologics business into Pittsburgh, which as you know, also serves as our corporate headquarters. From a strategic perspective, it is important to understand the context of this action. First and foremost, it is incumbent on the company to remain laser focused on its core capabilities with respect to the application of artificial intelligence to drive drug discovery. Second, the very thing that enables our ability to model and predict drug tumor responses identify biomarkers and predict outcomes with such accuracy is the quality of the tumor samples in our biobank and the significance of the pristine longitudinal data that has been generated from those samples. This has now been externally validated and was presented at the Association of Surgical Oncology. The ability to deliver on the accuracy of our predictions and relevance of our models requires constant sequencing, characterizing, curating and digitization of tissue samples, drug response data and pathology slides. This is an ongoing effort and one which drives the precision with which our AI-generated models are perfected. In the absence of these silent endeavors, we cannot possibly distinguish ourselves in the marketplace. All of this requires dedicated resources and in this case, the reallocation of those resources from Birmingham to Pittsburgh. Lastly, innovation perpetuates value creation, and adding value to the company impacts valuation of the company. By adding value, we are signaling our relevance to the market with respect to the significance of our core assets. This initiative, once fully implemented in Q4 of this year, is expected to reduce our run rate for cash used in operating activities by approximately $2.5 million annually, which equates to roughly 20% of our cash burn based on our stated 2023 cash used in operating activities of $13.2 million. As a point of preference, the Birmingham segment generated a net loss of $2.0 million in 2023 and $1.8 million in 2022, with de-minimis-supporting revenue. Moreover, since Birmingham has become essential to our core focus in Pittsburgh over time, and in light of its lack of profitability, this simply became the right decision for the company and the shareholders moving forward. We would be remiss not to extend our gratitude to our partners in Birmingham, especially Dr. Larry DeLucas, Senior Vice President of Biologics, for his years of leadership and dedication. Thank you, Larry. To further strengthen our financial position, we've announced over the last few months a couple of significant capital raises, $5.0 million in total that also helped to bolster our cash balance sheet and extend our runway. In May, the company raised $3.7 million, net of $0.6 million of issuance costs or $3.1 million in net proceeds through its at-the-market facility through the issuance of 1.6 million shares. And in July, the company raised an additional $1.3 million in gross proceeds through the exercise of 958,000 warrants through our warrant inducement transaction. And now I would like to turn this call over to Josh Blacher, our Chief Financial Officer to review our second quarter financials in detail. Josh?

Thank you, Raymond. We concluded the second quarter of 2024 with $5.3 million in cash and cash equivalents compared to $8.7 million as of December 31, 2023, and $4.1 million in stockholders' equity compared to $8.3 million as of December 31, 2023. Note that our cash balance as of June 30, 2024 includes net proceeds of $3.1 million that we raised from our ATM facility in May, but excludes amounts raised subsequent to the end of the second quarter from the warrant inducement transaction that Raymond described earlier. Our net loss per share for the second quarter of 2024 was $0.68 per basic and diluted share as compared to $0.98 per basic and diluted share for the second quarter of 2023. The company recorded revenues of $279,000 for the second quarter of 2024 compared to $490,000 for the comparable period in 2023. Revenues for the quarter ended June 30, 2024, and June 30, 2023, were primarily derived from the company's EGAN operating segment. General and administrative expenses primarily consist of management salaries, professional fees, consulting fees, administrative fees and general office expenses. G&A expenses decreased by $567,000 to $2.1 million in the three months ended June 30, 2024, compared to $2.7 million in the comparable period 2023. The decrease was primarily due to lower employee compensation and decreased investor relation costs, offset by increased consulting fees. Operation expenses primarily consist of expenses related to product development and prototyping and testing. Operations expenses decreased by $100,000 to $893,000 for the three months ended June 30, 2024, compared to $993,000 in the comparable period in 2023. The decrease was primarily due to decreased cloud computing expenses related to our Pittsburgh operating segment. We expect these types of savings to continue going forward. Sales and marketing expenses consist of expenses required to market and sell our products, including staff-related expenses, for individuals performing such work. Sales and marketing expenses decreased by $145,000 to $284,000 for the three months ended June 30, 2024, compared to $429,000 in the comparable period in 2023. The decrease was primarily due to lower employee compensation, including sales commissions. As a part of the cost savings initiative, we've taken a hard look at marketing, spending in general as it relates to ROI hurdles, so you can expect that such reductions will continue going forward. Net cash used in operating activities was $6.6 million for the six months ended June 30, 2024, down from $7.0 million for the comparable period in 2023. The company incurred net losses of $3.2 million and $3.9 million for the quarters ended June 30, 2024, and June 30, 2023, respectively. As of June 30, 2024, the company had an accumulated deficit of $175 million as compared to $168 million as of December 31, 2023. That concludes the financial overview. We will now open the call up for questions. Operator?

Thank you. [Operator Instructions] Mr. Vennare, I'd like to turn the floor back to you and close the question-and-answer session.

Thank you very much, and thanks, everyone, for being on the call. So that concludes our call for today. We hope that you take away from this call that we are extremely excited to actively pursue novel biomarker discovery and play a more direct role in the discovery and development of next-generation therapies, either independently or with a partner. This represents a tremendous opportunity for us to bring new hope to millions of patients worldwide in cancer and other high-need indications, while creating long-lasting value for our shareholders. Thank you again for your support and your patience, and I look forward to the next quarterly update in November. Have a great day.

Thank you. This concludes today's conference call. You may disconnect your lines at this time. Thank you for your participation.

Ladies and gentlemen, good morning, and thank you for standing by. Welcome to the Predictive Oncology Q1 2024 Earnings Conference Call. [Operator Instructions] Please be advised that today's conference is being recorded. And I would now like to hand the conference over to your speaker, Mr. Glenn Garmont, Investor Relations. Mr. Garmont, please go ahead.

Welcome, and thank you, everyone, for dialing in to the Predictive Oncology First Quarter 2024 Financial Results Call. First, you'll hear from our Chief Executive Officer and Chairman of the Board, Raymond Vennare; then our Chief Financial Officer, Josh Blacher, will review our financials. Certain matters discussed on this call contain forward-looking statements. These forward-looking statements reflect our current expectations and projections about future events and are subject to substantial risks, uncertainties and assumptions about our operations and the investments we make. All statements other than statements of historical facts included in the call regarding our strategy, future operations, future financial position, future revenue and financial performance, projected costs, prospects, plans and objectives of management are forward-looking statements. The words anticipate, believe, estimate, expect, intend, may, plan, would, target and similar expressions are intended to identify forward-looking statements, although not all forward-looking statements contain these identifying words. Our actual future performance may differ materially from that contemplated by the forward-looking statements as a result of a variety of factors, including, among other things, factors discussed under the heading Risk Factors in our filings with the SEC. Except as expressly required by law, the company disclaims any intent or obligation to update these forward-looking statements. And now I'd like to turn the call over to Raymond Vennare, Chief Executive Officer. Raymond?

Thank you, Glenn, and good morning, everyone. Thank you for joining us today. I would like to begin this morning with an update on a truly groundbreaking study that we recently completed with UPMC Magee-Womens Hospital in Pittsburgh. This was a retrospective multiyear study to determine if we could leverage our artificial intelligence capabilities to build multi-omic machine learning models that would be better than clinical data alone in predicting both short- and long-term survival outcomes among ovarian cancer patients. Ovarian cancer represents a significant unmet need in oncology with epithelial ovarian cancer being the deadliest of all gynecologic malignancies. While these cancers are sensitive to frontline chemotherapy in approximately 75% of the cases, these women will ultimately experience disease relapse in an equal percentage, which is incurable. Outside of primary chemotherapy, there is no universal treatment decision path to determine the agent, sequence and timing of the standard of care for chemotherapy agents. The Magee study was designed to identify key features that drive overall survival endpoints. It included data from 235 ovarian cancer patients from 2010 through 2016, a broad array of inputs, including patient data, whole exome sequencing, whole transcriptome sequencing, drug response profile and digital pathology profiles were used to train the 160 models that we included in the study. We are very pleased to report that we were able to deliver strong predictive models with high levels of accuracy and our machine learning capabilities demonstrated the ability to identify prognostic subgroups within an ovarian cancer patient population. Further validating the significance of these study results, we announced a few weeks ago that an abstract detailing the study has been accepted for presentation at a very prestigious American Society of Clinical Oncology Annual Meeting, better known as ASCO, which is being held May 31 through June 4 in Chicago. The presentation, which will be delivered by Dr. Brian Orr, gynecologic oncologist at the Hollings Cancer Center, Assistant Professor at the Medical University of South Carolina and lead investigator of the study is scheduled for Monday, June 3 at 9 a.m. Central Time. As we stated last quarter, the potential implications for the Magee and other clinical decision-makers are significant as these models can be used as an important decision support tool to better tailor therapies to individual patients and positively affect overall survival. The implications for Predictive Oncology extend beyond that, however, we believe there are many opportunities to utilize this information for purposes other than clinical utility. The possibility does exist to leverage these data to develop digital pathology applications and new predictive models for other cancer types. And other such application would be to drive the design of more efficient and effective clinical trials. Also, with the ability to identify novel biomarkers that are correlated with survival, we can leverage this information to become more directly involved in drug discovery itself in addition to acting as a partner to others to expedite drug discovery. This has formed in my vision, as you know, for the company. The successful results of this ovarian cancer study not only clinically validate our ability to successfully predict outcomes, they serve as a sort of proof-of-concept that supports further work towards that goal. With these compelling results in hand, we are accelerating our drug rescue, drug repurposing and drug combination initiatives and more fully leveraging our artificial intelligence, machine learning and wet lab capabilities to evaluate the drug response of hundreds of diverse patient tumors against hundreds of drugs in a fraction of the time and at a fraction of the loss of valuable samples. Turning now to another recent development. Last month, we announced the collaboration with Fujifilm to co-market our EndoPrep sample treatment technology, together with Fujifilm's PYROSTAR bacterial endotoxin detection reagent to reduce protein interference and bacterial endotoxin testing of biopharmaceutical products. For those interested in learning more, the first joint webinar will be held on Wednesday, May 29, at 10:00 a.m. Eastern Time. Endotoxins also known as lipopolysaccharides LPS are components of the outer cell membrane of gram-negative bacteria and are released when intact bacteria are disrupted. Sub-nanogram levels of endotoxins can trigger immune responses such as inflammation and fever in patients, even leading to systemic shock and death. Endotoxins are highly resistant to sterilization processes and accurate detection and removal of endotoxins in biopharmaceuticals are required before entering animal trials or human clinical trials. PYROSTAR is widely considered to be the best detection system for measuring endotoxin levels in biologic products. When paired with EndoPrep, they can accurately detect residual endotoxins in the presence of interfering glucans and reduced interference of most biologic products with detection assay. In a proof-of-concept study, we achieved reproducible and accurate measurements of endotoxin in the presence of specific interfering proteins in biologics. The study results indicate that 3 or 4 tested biologics went from not failing in the 50% to 200% detection of challenge endotoxin to falling in the 50% to 200% detection range as required by the FDA for clinical testing. In addition to demonstrating the versatility of our biologics technology, this collaboration will allow Predictive Oncology to make a significant positive impact on drug safety. We are very pleased to have the opportunity to work with Fujifilm on this project as they are a clear industry leader in the development of endotoxin solutions for injectable pharmaceuticals and biological products. We also announced recently that we are making meaningful progress with FluGen in the development of a first-of-its-kind intranasal flu vaccine. This project is part of a $6.2 million Phase IIb grant awarded by the United States Department of Defense. Pursuant to this agreement, we are utilizing our formulations expertise to help FluGen develop its M2SR vaccine that is soluble and stable in a refrigerated state, which is a vital part in the drug development process. Most importantly, this would also address the need for a longer vaccine shelf life to support global distribution, including remote locations. Unlike the standard of care flu vaccines, M2SR stimulates mucosal, humeral and cellular immunity. In an unprecedented challenge trial, M2SR demonstrated protection against infection and illness across 7 years of virus DRiPs, and M2SR induces a durable antibody response with potential to cover an entire flu season beyond. M2SR also has shown activity as a vaccine vector for other respiratory vaccines in infectious diseases, including a COVID-19 flu combination. With our proprietary HSC technology and artificial intelligence platform that efficiently analyzes more than 4,000 different drug formulation combinations using FDA-approved excipients. We are able to find the optimal formulation tailored to the final product's application in only 3 to 6 months using as little as 20 micrograms of protein. Our novel design of experiments is a critical component currently being utilized for the development of FluGen's flu vaccine. This is exactly the kind of innovation that we strive to be part of, and we look forward to the continued development of this groundbreaking advancement in the vaccine field. Moreover, as I mentioned in our last update, we have recently announced the development of our latest stem cell technology breakthrough, a novel protein expression method for G protein-coupled receptors, GPCRs and other membrane protein classes. This capability supports drug discovery for a variety of diseases, including aggressive cancers. Turning now to other collaborations we have discussed in the past. Let me give you a brief update on Cvergenx as well as the most recent submission to the center for the advancement of science and space. You may recall that last February, we announced the collaboration with Cvergenx to develop the first ever genomics-based approach to precision radiation therapy and drug discovery using artificial intelligence. The objective of this collaboration is to leverage and maximize the combined power of Predictive Oncology's expertise in artificial intelligence and Cvergenx's proficiency in biomarker development to identify novel radioprotector and radiosensitizer drugs. Over the past year, we have made significant progress, having now evaluated trained or developed models to predict changes in radio sensitivity for more than 3,000 different drug exposures as well as using well-established gene expression databases. These findings form the basis of an NIH SBIR Phase 1 grant to screen vast libraries of compounds to accelerate the potential development of drugs, drug combinations or repurpose drugs, sensitize or protect human subjects from the effects of radiation. The significance of identifying of these radiosensitizers and radioprotectors extends well beyond drug repurposing, however. Using these models, for example, we would be able to proactively screen workers in the nuclear energy industry and military and in the clinical setting, optimize the planning and treatment of patients receiving radiotherapy. So our work with Cvergenx has potentially broad utility across a number of important applications. And in the process, we have been able to expand those data sets, which may be leveraged in several important ways with respect to commercialization. First, to screen individuals for radiation sensitivity or resistance to optimize the clinical effect of radiotherapy. Second, to screen for interactions between sensitive or resistant patient tumor samples and therapeutic compounds. And third, to identify combined or developed novel or repurpose radioprotective or radiosensitizing drugs. These are not isolated developments, with synergistic activities that have created new and more interesting opportunities, which has led to collaborations with Merck & Company, OCMS and Redwire Space. And now I would like to turn this call over to Josh Blacher, our Chief Financial Officer. Josh?

Thank you, Raymond. We concluded the first quarter of 2024 with $5.2 million in cash and cash equivalents compared to $8.7 million as of December 31, 2023, and $4.0 million in stockholders' equity compared to $8.3 million as of December 31, 2023. In April, we established a new at-the-market ATM financing vehicle, which will allow us to sell common shares from time to time. Our current dollar value to pass through the ATM is over $3.5 million. Our net loss per share for the first quarter of 2024 was $1.04 per basic and diluted share as compared to $0.86 per basic and diluted share for the first quarter of 2023. The company recorded revenues of $420,000 for the first quarter of 2024 compared to $240,000 for the comparable period in 2023. Revenues for the quarter ended March 31, 2024 and March 31, 2023, were primarily derived from the company's Eagan operating segment, which contributed revenues of $404,000 and $216,000 for the quarters ended March 31, 2024, and 2023, respectively. General and administrative expenses primarily consist of management salaries, professional fees, consulting fees, administrative fees and general office expenses. G&A expenses increased by $291,000 to $2.6 million in the 3 months ended March 31, 2024, compared to $2.3 million in the comparable period in 2023. The increase was primarily due to increased professional fees, including audit and consultant fees as well as increased business factors, offset by decreased employee compensation as well as decreased depreciation due to fully depreciated assets. Operating expenses primarily consist of expenses related to product development and prototyping and testing. Operations expenses increased by $224,000 to $1.1 million in the 3 months ended March 31, 2024, compared to $879,000 in the comparable period in 2023. The increase was primarily due to increased employee compensation associated with our research and development efforts. Sales and the marketing expenses consist of expenses required to market and sell our products, including staff-related expenses for individuals performing at work. Sales and marketing expenses increased by $369,000 to $740,000 in the 3 months ended March 31, 2024, compared to $370,000 in the comparable period in 2023. The increase was primarily related to severance related to a former executive. Net cash used in operating activities was $3.4 million for the first quarter of 2024, roughly flat with cash used of $3.4 million for the comparable period in 2023. The company incurred net losses of $4.2 million and $3.4 million for the quarters ended March 31, 2024 and March 31, 2023, respectively. As of March 31, 2024, the company had an accumulated deficit of $172 million as compared to $158 million as of December 31, 2023. That concludes the financial overview. We will now open the call for questions. Operator?

Thank you. Ladies and gentlemen, we will now be conducting a question-and-answer session. [Operator Instructions] Ladies and gentlemen, since there are no questions in the queue, I now hand the conference over to Raymond Vennare for his closing comments. Raymond?

Thank you very much, everyone. I just wanted to again say that we are very pleased with our progress with the new developments that we've been able to initiate over the last few months. We appreciate your ongoing support, and we look forward to our next update in the next quarter. Thank you very much.

Thank you. The conference of Predictive Oncology has now concluded. Thank you for your participation. You may now disconnect your lines.

Greetings and welcome to the Predictive Oncology Fourth Quarter 2023 Earnings Call. At this time all participants are in a listen-only mode. A brief question-and-answer session will follow the formal presentation. [Operator Instructions]. As a reminder this conference is being recorded. It is now my pleasure to introduce your host, Glenn Garmont, LifeSci Partners. Thank you Glenn, you may begin.

Welcome, and thank you, everyone, for dialing into the Predictive Oncology full year 2023 financial results call. First, you'll hear from our Chief Executive Officer and Chairman of the Board, Raymond Vennare; then our Chief Financial Officer, Josh Blacher, will review our financials. Certain matters discussed on this call contain forward-looking statements. These forward-looking statements reflect our current expectations and projections about future events and are subject to substantial risks, uncertainties, and assumptions about our operations and the investments we make. All statements other than statements of historical facts included in the call regarding our strategy, future operations, future financial position, future revenue and financial performance, projected costs, prospects, plans, and objectives of management are forward-looking statements. The words anticipate, believe, estimate, expect, intend, may, plan, would, target, and similar expressions are intended to identify forward-looking statements, although not all forward-looking statements contain these identifying words. Our actual future performance may materially differ from that contemplated by the forward-looking statements as a result of a variety of factors, including, among other things, factors discussed under the heading Risk Factors in our filings with the SEC. Except as expressly required by law, the company disclaims any intent or obligation to update these forward-looking statements. And now I would like to turn the call over to Raymond Vennare, Chief Executive Officer. Raymond?

Thank you, Glenn. And good morning, everyone. It has now been slightly more than 12 months since we essentially restructured, repositioned, and implemented our new strategic vision for predictive oncology. And I have to say that I'm very pleased with the progress that we've made in a relatively short period of time. We have not only identified previously unutilized assets within the company, but we have further bolstered one of our most significant and valuable assets, our intellectual property and trade secrets. Sometimes progress is invisible. Trying on this unique set of integrated assets and capabilities, we have now begun to articulate what we believe is a compelling offering for accelerating oncologic drug discovery and development on a global scale. 2023 was a difficult but important year for us. It was transitional and necessary. Rebuilding is never easy. It was also a year of learning and responding to that knowledge. It has enabled us to incorporate valuable commercial lessons from our first year in the market to further refine our business development initiatives and set the stage for accelerating growth moving forward. As reminder, and particularly for those who may be new to our story, Predictive Oncology is unique in the evolving artificial intelligence in drug discovery market. We are the only company to our knowledge that is able to bring together cutting edge artificial intelligence and active learning technology with a proprietary biobank of more than 150,000 tumor samples, more than 25 years of longitudinal patient specific drug response data, a CLIA certified wet lab and more than 200,000 pathology slides, which are currently being digitized and incorporated into our PEDAL platform. We can add to that reservoir of proprietary assets more than 40,000 formalin fixed paraffin embedded blocks of human tissue, and an expanding portfolio of intellectual property. This platform, which is more than just an artificial intelligence platform, but its scientific methodology generates efficient, highly accurate predictions of how tumors respond to drugs, and supports those in silico predictions with clear validated in vitro experimentation. Our biobank allows us to introduce patients and tumor heterogeneity into the earliest phases of drug development, which enables our partners to gain critical insight into the prioritization and future development of potential drugs that have greater or lesser degrees of clinical success well before human clinical trials are initiated. Having technically, scientifically, and commercially validated PEDAL platform, we have clearly demonstrated that we are able to predict if a tumor will respond to a given drug with 92% accuracy. The implication for drug developers is that they can mitigate the risk of failure and expedite the probability of success in ways that have never been seen before. It has been well documented that drug development is inherently expensive and risky, particularly in the area of oncology. Over the past 20 years, in fact, there have been approximately 1500 drugs selected for clinical trials, only 115 of which were ultimately approved for clinical use. In other words, less than 8% of all cancer drugs that enter Phase 1 trials are actually approved by the FDA. By harnessing the power of our PEDAL platform, drug developers are able to save many millions of dollars and thousands of man hours, pursuing the development of drug candidates that we predict are most likely to succeed in the clinic, while avoiding the risk of the dancing candidates, which we may have predicted, might fail in later stages of clinical trials. With PEDAL, we are also able to generate proprietary data that can aid our drug development partners in training novel AI, broad tumor response models. While others in our industry have certainly attempted to replicate what we have already developed, and currently own, they simply cannot duplicate the comprehensive historical archive of tumor samples, drug response data, and domain expertise that we possess. This speaks volumes about the importance of our unique ability to integrate data from multiple sources into a single solution that can successfully introduce tumor heterogeneity into the early drug discovery. Moreover, we believe our biobank and large repository of drug response data gives us an enduring competitive advantage that will take years if not decades to reproduce. Although we don't discuss this as much as we could, the fundamental significance of owning and controlling the entire continuum of biological samples, historical drug response data, computational capacity, anthology reference sets and wet lab experimentation means that we are in control of our own destiny with respect to the use of these assets. Ultimately, if not inevitably, we will not only be in a position to identify drug candidates ourselves, but to license those candidates directly to Big Pharma. I would now like to provide an update on some of our more notable engagements from 2023 beginning with cancer research horizons. Recall that we have been working with CRH, the world's largest private funder of cancer research to evaluate three of their preclinical glutaminase inhibitor drug compounds to determine which cancer types and patient populations are most likely to respond to treatment with those compounds. In only a matter of a few weeks of actual lab time, we were able to deliver the results of this first campaign, which was able to identify subpopulations of patients that were more responsive to their compounds across four different tumor types, colon, liver, lung, and ovary. Armed with this information, CRH is now in a position to prioritize the development of the strongest candidates on the ideal tumor types and in the process gave significant time and resources by pursuing only those targets that are most likely to succeed in the clinic. The next step here might be to use a sampling of the subpopulations of interest, presumably responders in one or two of the tumor types of interest to perform more extensive molecular sequencing, including DNA, or whole exome and or RNA or whole transcriptome. This would provide much more information for the purpose of better defining responsive patient tumor samples. From our perspective, this engagement with CRH provides crucial third party validation of our PEDAL technology and serves as an important reference point as we engage with other leading cancer drug discovery and drug development companies. Turning now to UPMC Magee-Women’s Hospital, we announced last quarter that we successfully completed a multi-year retrospective study, build multi-omic machine learning models that could predict overall short and long term survival in ovarian cancer. Ovarian cancer treatment represents an unmet need in oncology, with epithelial COVID [ph] ovarian cancer being the deadliest of all kinds of cologic malignancies. While these cancers are sensitive to frontline chemotherapy in approximately 75% of the cases, these women will ultimately experience disease relapse in an equal percentage which is incurable. Outside of primary chemotherapy, there is no universal treatment decision path to determine the agent, sequence, and timing of the standard of care chemotherapeutic agents. The Magee Study included data from 235 ovarian cancer patients, and was designed to identify key features that drive overall survival endpoints. We are very pleased to say that we were able to deliver strong predictive models with high levels of accuracy and our machine learning capabilities demonstrated the ability to identify prognostic subgroups within an ovarian cancer patient population. We continue to engage with Magee on additional methods of incorporating these models into clinical practice. One potential application would be the development of an AI driven decision support tool, leveraging the features that we identified as having prognostic importance for the model to tailor therapies for individual patients and positively affect overall survival. Another such application would be to drive more efficient and effective clinical trial designs. While these discussions are ongoing, we are in parallel, utilizing this information for purposes other than clinical utility. The possibility certainly does exist to reevaluate this data to develop biomarker leads, digital pathology applications, and new predictive models for other cancer types, as well as models for drug rescue, drug repurposing, and drug combinations. Leaning heavily on this evidence in fact, we recently submitted a proposal to the RK Mellon Foundation to further enrich the data sets necessary for modeling, including sequencing activities, aggregation and curation of clinical information especially outcome data, and the digitization and futurization of more than 200,000 pathology slides currently in our possession, delivering significant value and unique insights to highly regarded collaborators such as Magee and through them gaining access to drug developers and CROs who can benefit from our models is a key factor in our business and corporate development efforts moving forward. Our work with both CRH and Magee confirm without question, our ability to aggregate, analyze, and model multi-omic data to successfully predict patient responses to certain drug targets across heterogeneous patient populations. Again, it is the patient heterogeneity that is incorporated into our models that truly sets us apart from others in the industry, both new and established AI players, as patient heterogeneity is a major reason why oncology drugs fail in later stages of clinical development. Turning now to other collaborations that we have discussed in the past. Let me give you a brief update on Cvergenx, FluGen and Fuji [ph], as well as the most recent submission to the Center for the Advancement of Science and Space. You may recall that last February, we announced a collaboration with Cvergenx develop the first ever genomic spaced approach to precision radiation therapy and drug discovery using artificial intelligence. The objective of this collaboration was to leverage and maximize the combined power of Predictive Oncology’s expertise in artificial intelligence and Cvergenx proficiency in biomarker development to identify novel radio protector and radiosensitizer drugs. Over the past year, we have made significant progress having now evaluated, trained, or developed models to predict changes in radio sensitivity for more than 3000 different drug exposures using well established gene expression databases. These findings form the basis of an NIH SBIR Phase 1 grant, screen vast libraries of compounds to accelerate the potential development of drugs, drug combinations, or repurposed drugs to sensitize or protect human subjects from the effects of radiation. The significance of identifying these radio sensitizers and radio protectors extend well beyond drug repurposing however. Using these models, for example, we can proactively screen workers in the nuclear energy industry and in the military and in a clinical setting, optimize the planning and treatment of patients receiving radiotherapy. So our work with Cvergenx has potentially broad utility across a number of important applications. And in the process, we have been able to expand those datasets, which may be leveraged in several important ways with respect to commercialization. First, to screen individuals for radiation sensitivity or resistance to optimize the clinical efficiency of radiotherapy. Second, screening for interactions between sensitive or resistant patient tumor samples and therapeutic compounds. And third, to identify, combine, or develop novel or repurpose radio protective or radio sensitizing drugs. These are not isolated elements, but synergistic activities that created new and more interesting opportunities. For example, as you might remember, our Biologics Group is led by Dr. Larry DeLucas, former astronaut and Senior Scientist for the space station. Because of that experience, and given his relationship with NASA, we recently submitted a proposal to the Center for the Advancement of Science and Space to use our technology on the space station. Larry and his team have now developed a novel membrane protein expression system to produce significant quantities of biologically active G protein coupled receptors, also known as GPCRs, and other membrane protein classes. The reason for this is that the microgravity environment in space can improve cell differentiation and increase the rate of cell growth and size which enhances the yield of expressed GPCRs. The more practical and immediate opportunity, however, is that this concept has also led to collaborations with Merck & Company, OCMS, and Red Wire Space. As a result of these developments, we have just filed intellectual property or novel method and system for expression and purification of G protein coupled receptors. When issued, we will be in a position to broadly out license this technology to biopharma for numerous drug development applications. You may remember from our last call that Predictive Oncology and FluGen entered into a collaboration to develop a novel first of its kind flu vaccine to market as part of a multi-million dollar project funded by the Department of Defense for which a Phase 2B grant has been submitted to the NIH. I'm pleased to say that this grant has now been awarded, the details of which will be disclosed in the coming weeks pending approval by the Department of Defense. Predictive Oncology will play a critical role in making FluGen’s vaccine more stable and sustainable in a refrigerated state, which is a crucial requirement in the drug development process. And lastly, Predictive Oncology and Fuji [ph] will in the next few weeks announce their intention to co-market our endotoxin detection and treatment technologies as a novel solution for injectable pharmaceuticals and biological products. According to a recent report by Future Market Insights, the $6 billion injectable drug market is expected to grow by 5.8%, reaching the projected value of $10 billion by 2034. Before turning the call over to Josh to review the financials, I would like to recap recent conference activity. During the initial months of 2024 we had a meaningful presence at several investor conferences geared toward raising awareness of our company among high quality institutional healthcare investors, as well as potential collaborators. These include Biotech Showcase in San Francisco, The Bio CEO and Investor Conference in New York, the 2024 New Cancer Oncology Conference in New Orleans, during which I sat on a panel discussing the topic of precision medicine. And finally, the H.C. Wainwright First Annual Artificial Intelligence Based Drug Discovery and Development Conference. We have more such conference appearances planned for the balance of 2024 and we view these events as a critical element of our effort to create long-term value for both our partners and our shareholders. At this point, I will turn the call over to Josh Blacher. Josh.

Thank you, Raymond. We concluded the fourth quarter of 2023 with 8.7 million in cash and cash equivalents compared to 22.1 million as of December 31, 2022, and 8.3 million in stockholders equity compared to 21.8 million as of December 31, 2022. Our net loss per share in 2023 declined approximately 50% to $3.48 for basic and diluted share, $6.98 per basic and diluted share for 2022. The company recorded revenue of 1.8 million in 2023, compared to 1.5 million in 2022. Revenues for the years ended December 31, 2023 and December 31, 2022 were primarily derived from our Eagan operating segment. The Eagan operating segment contributed 1.135 million and 1.064 million for the years ended December 31, 2023 and December 31, 2022 respectively, while the Pittsburgh operating segment contributed 493,000 and 359,000 respectively. Operation expenses primarily consist of expenses related to product development, prototyping, and testing. Operation expenses decreased by 142,000 to 3.7 million in 2023, compared to 3.8 million in 2022. The decrease in operations expenses in 2023 is primarily due to approximately 132,000 lower research and development expenses related to office closures and approximately 52,000 lower related to staff expenses. These decreases were offset by higher cloud computing expenses associated with our Pittsburgh operating segments. Net cash used in operating activities was 13.2 million in 2023 compared to net cash use of 12.4 million in 2022. Cash used in operating activities increased in 2023, primarily due to cash operating losses as well as changes in working capital, including decreases in accrued expenses in contract liabilities, offset by an increase in accounts payable. Net cash used in investing activities was 302,000 in 2023 compared to 476,000 in 2022. Cash used in investing activities decreased in 2023 primarily due to a decrease in the acquisition of property and equipment. Net cash provided by financing activities was 149,000 in 2023 compared to 67,000 in 2022. Cash provided by financing activities in 2023 was primarily related to proceeds refinancing insurance premiums over the insured period with a short-term note payable, while cash provided in 2022 was primarily proceeds from the issuance of common stock and warrants. The company incurred net losses of 14.0 million and 25.7 million for the years ended December 31, 2023 and December 31, 2022. That concludes the financial overview. We will now open the call for questions. Operator.

Thank you all very much again for participating in this call. I just want to reiterate the fact that we are we actually are very pleased with our progress since we implemented our new strategic vision for the company a little over a year ago, and acting on the information that we have learned, accelerating our traction in the marketplace with many of the companies that I mentioned in my remarks. So if there are no other questions, I want to thank you all for participating. I thank you for your continued support. And I thank you for remaining involved in the company and we look forward to reporting again soon. Thank you.

This concludes today's conference. You may disconnect your lines at this time. Thank you for your participation.

Good day, and thank you for standing by. Welcome to the Predictive Oncology Q3 2023 Earnings Conference Call. [Operator Instructions] Please be advised that today's conference is being recorded. And I would now like to hand the conference over to your speaker for today, Mr. Glenn Garmont, Investor Relations. Mr. Garmont, please go ahead.

Welcome, and thank you, everyone, for dialing into the Predictive Oncology third quarter 2023 earnings call. First, you'll hear from our Chief Executive Officer and Chairman of the Board, Raymond Vennare; then our Chief Financial Officer, Josh Blacher, will review our financials; finally, Dr. Pamela Bush, our Chief Business Officer, will join Raymond and Josh to answer any questions that you may have. Certain matters discussed on this call contain forward-looking statements. These forward-looking statements reflect our current expectations and projections about future events and are subject to substantial risks, uncertainties and assumptions about our operations and the investments we make. All statements other than statements of historical facts included in the call regarding our strategy, future operations, future financial position, future revenue and financial performance, projected costs, prospects, plans and objectives of management are forward-looking statements. The words anticipate, believe, estimate, expect, intend, may, plan, would, target and similar expressions are intended to identify forward-looking statements, although not all forward-looking statements contain these identifying words. Our actual future performance may materially differ from that contemplated by the forward-looking statements as a result of a variety of factors, including, among other things, factors discussed under the heading Risk Factors in our filings with the SEC. Except as expressly required by law, the company disclaims any intent or obligation to update these forward-looking statements. And now I would like to turn the call over to Raymond Vennare, Chief Executive Officer. Raymond?

Glenn, thank you very much, and good morning, everyone. In March of this year, we were very pleased to announce a research collaboration with Cancer Research Horizons, whereby we would utilize our AI drug discovery platform, our PEDAL platform, to evaluate several CRH preclinical glutaminase inhibitor drug compounds to determine which cancer types and patient populations are most likely to respond to treatment with these compounds. As a reminder, CRH is the innovative engine at the core of Cancer Research UK, the largest independent funder of cancer research in the world. CRH has a network of more than 4,000 cancer researchers, an annual research spend of more than $370 million, 11 drugs currently on the market and another 160 candidates in various stages of development. Today, I am pleased to announce that we have provided CRH with the initial results of this research collaboration, which, as you might imagine, is a very significant milestone for our company, not only in terms of the results themselves, but because we were able to achieve these results in a matter of weeks. By prioritizing the development of the strongest candidates for the ideal tumor types based upon the output from PEDAL, CRH can save significant time and resources by pursuing only those projects that are most likely to succeed in the clinic. With our proprietary biobank of more than 150,000 tumor samples and CLIA-certified wet labs, we believe we can predict with a higher degree of accuracy than anyone else the probability of clinical success because we were able to introduce patients and tumor heterogeneity into the very earliest stages of drug development. And we can support our predictions with actual in silico modeling and bench level experimentation. With our data in hand, CRH can now prioritize the development of these compounds and seek potential licensing deals with large pharmaceutical companies for further development. This is significant for two reasons. First, because we are now eligible for development and commercialization milestones in the event that a licensing deal is executed as well as potential sales royalties; and second, because we believe the success of this first campaign, which, as I said, was completed in several weeks, should pave the way for additional projects from CRH. It is difficult to overstate the significance of the external validation that our initial campaign with CRH provides. And this relationship has had a very positive impact on our business development efforts elsewhere. I am pleased with our progress to date and believe we have created a solid foundation on which to drive future growth. The emergence of AI is fundamentally changing how drugs are discovered and subsequently developed. And we are at the forefront of this exciting and foundational transformation. It is well known and generally accepted that approximately 95% of drug candidates never received commercial approval. But with our unique capabilities, our partners can gain insight into the future of heterogeneous drug response and confidently make strategic clinical drug development decisions with lower financial risk and greater likelihood of commercial success. Turning now to another significant development since our last quarterly update. We announced just last week that we have successfully completed a multiyear retrospective study with UPMC Magee-Women’s Hospital in Pittsburgh. The purpose of this study was to build multi-omic machine learning models that could predict overall short- and long-term survival in ovarian cancer. The study incorporated one of the largest sets of multi-omic data from 235 ovarian cancer patients derived from tumor samples obtained at the time of diagnosis or first surgical intervention. The study was designed to identify the key features that drive overall survival endpoints. And in fact, we have been able to deliver strong predictive models with high levels of accuracy. These data will be presented at multiple national medical meetings in 2024. And we are considering future initiatives to both expand and further utilize these cohorts. The power of our technology is made obvious here because our multi-omic machine learning models have the potential to identify and define certain prognostic subgroups within ovarian cancer. High-grade serous carcinomas, for example, of the ovary make up most ovarian cancer cases and have the lowest survival rate. As far as next steps are concerned, there is certainly an opportunity to learn more about features that were identified as having prognostic importance for the model. This includes features that originate from our own digital pathology slides library. Ultimately, these models could support the tailoring of therapies to individual patients with the goal of positively affecting the overall survival of ovarian cancer patients and the development of invaluable clinical support tools. Clearly, there's an opportunity here to explore drug rescue or repurposing for the treatment of ovarian cancer and in the process of discovery and development, identify significant intellectual property that is specific to these predictive models and beneficial to an AI-driven decision support platform. I would like to take a moment now to review some other significant projects that are ongoing. As you may recall, in February of this year, Predictive Oncology and Cvergenx announced a partnership to develop the first-ever genomics-based approach to precision radiation therapy and drug discovery utilizing artificial intelligence. The objective of this collaboration was to leverage and maximize the combined power of Predictive Oncology's expertise in artificial intelligence and Cvergenx proficiency in biomarker development for radiation therapy to identify novel radioprotector and radiosensitizer drugs. Since then, we have evaluated, trained or developed models to predict changes in radiosensitivity for more than 3,000 different drug exposures using well-established gene expression databases. Based on results from our preliminary models, we have submitted a step one proposal to NASA to search for radioprotective drugs to safeguard astronauts from radiation during space flight. An SBIR proposal will also be submitted to the NIH to propose drugs to protect workers in the nuclear energy industry and the military from the effects of radiation and in the clinical setting to increase the radiation sensitivity of tumor tissue for those patients receiving radiation therapy. As we all know, Predictive Oncology's two most valuable assets are the biobank more than 150,000 tumor samples and repository of drug response data, which are integral to our PEDAL drug discovery platform, both to evaluate and guide the design of experiments and models. Most of our current projects utilize PEDAL to direct drug screening in silico in order to minimize the time and material spent on physical laboratory experiments. The collaboration between Predictive Oncology and Cvergenx is driving expansion of those data sets, which may be leveraged in several important ways with respect to commercialization: first, to screen individuals for radiation sensitivity or resistance to improve the therapeutic effect of radiotherapy; second, to screen for interactions between sensitive or resistant patient tumor samples and therapeutic compounds; and third, to identify, combine or develop novel or repurpose radioprotective or radiosensitizing drugs. Separately but simultaneously, we have successfully developed a novel formulation for a protein drug candidate for an international pharmaceutical company that enabled that company to proceed with their toxicology studies. And in addition to existing contracts with biotech and biopharma companies, we are collaborating with FluGen on a next-generation vaccine related to respiratory disease for which a Phase IIb grant has already been submitted to the NIH. Most recently, we just returned from BIO-Europe, where we met with 40 different pharmaceutical companies over three days. Several of these companies have expressed interest in our formulation services and the purchase of our endotoxin product. In addition, three other companies expressed interest in purchasing our proprietary high throughput self-interaction chromatography platform, referred to as HFC, that enables rapid high-volume screening to determine the optimum solubility and stability conditions for new vaccines. These contracts point to the versatility of our technology to positively impact a broad spectrum of early drug discovery and development projects. And we look forward to more such announcements in the near future. For example, we continue to make progress on a novel method to express and stabilize GPCR, G protein-coupled receptors, which is an important class of membrane proteins that represent an emerging market in cancer drug discovery. It is worth repeating that while we are clearly hyper focused on securing high-value PEDAL drug discovery contracts, we do recognize that these engagements do take time. To support these efforts, we also have a very active biologics business, wherein formulation development and quality control testing are provided to our pharmaceutical development partners on a fee-for-service basis. This is relevant because protein therapeutics play a meaningful role in almost every field of medicine. From antibodies to enzymes and hormone treatment, the number and frequency of protein therapeutics brought to market has increased dramatically. But for these therapies to be effective, an optimal dose of the therapy must be properly circulated, delivered and absorbed in the body. Not unlike the efficient predictive accuracy of the PEDAL platform for drug discovery, our biologics capabilities enable us to efficiently streamline and accelerate the formulation process, identify alternative and more viable formulations for commercial production and drug discovery applications. I point this out because this company is well positioned to generate near-term formulations revenue to supplement building a pipeline of milestone-driven PEDAL contracts. And finally, last quarter, we announced the creation of a Business Advisory Board and the appointment of two individuals with highly relevant yet diverse expertise: Dr. Bernard A. Harris, Jr., who brings with him a wealth of clinical business and operational health care experience; and finance veteran, Andrew Einhorn, who has served as senior finance executive for a broad range of biopharmaceutical companies. As our momentum continues to accelerate, the Business Advisory Board's insight, expertise and perspectives will be invaluable in our efforts to deliver unique solutions to our drug development partners and creating lasting value for our shareholders. We are seeking many outstanding candidates who would add to the diversity of backgrounds and perspectives as we seek to round out our Business Advisory Board. At this point, I would like to introduce our new Interim Chief Financial Officer, Josh Blacher. Josh joined us in August and served as our Principal Financial Officer and Principal Accounting Officer. Josh has served as CFO for several public and private life sciences companies. I'm pleased to have Josh on board. And he has already had a positive impact on helping some of our operating businesses focus more on top line growth and profitability, introducing efficiencies in the finance and accounting department and helping roll out a more robust Investor Relations program. At this point, I will turn the call over to Josh to review the financials. Josh?

Thank you, Raymond. We ended the third quarter of 2023 with cash and cash equivalents of $11.9 million as compared to $22.1 million as of December 31, 2022. In addition, we have 1.8 million outstanding warrants that represent potential source of capital in the future. We have no long-term debt, so our balance sheet is strong. As of September 30, 2023, stockholders' equity stood at $11.7 million as compared to $21.8 million as of December 31, 2022. We recorded third quarter 2023 revenue of $715,000 as compared to $456,000 for the third quarter of 2022. Our gross margin in the third quarter of 2023 was 85% as compared to 76% for the third quarter of 2022. Operating expenses were $3.8 million in the third quarter of 2023, down from $4.5 million in the third quarter of 2022. Net cash used in operating activities was $10.1 million for the nine months ended September 30, 2023, as compared to $9.1 million for the comparable period in 2022. Net cash used in investing activities was approximately $310,000 for the nine months ended September 30, 2023, as compared to $412,000 for the comparable period in 2022. That concludes our financial summary. You can find additional details in our 8-K containing our earnings press release as well as our 10-Q, which is on file with the SEC and available on our website. With that, I'm going to turn the call now over to the operator for Q&A. As a reminder, Dr. Pamela Bush, our Chief Business Officer, is also available for this segment of the call.

Irene, thank you very much. So everyone, that concludes our call for today. We hope that you take away from this call that the entire Predictive Oncology team is very excited about the growth trajectory that we are currently on. In the coming quarters, I would anticipate more collaborations and partnerships with some of the world's leading drug developers and research and academic institutions. And we are very excited to be at the forefront of AI and early drug discovery, playing an important role in the discovery of new oncology drugs, which we believe will not only benefit patients but also create enduring value for our shareholders as well. Thank you again for your support, and I look forward to our next quarterly update in March. Have a good day.

This concludes today's conference. Thank you for joining us. You may now disconnect your lines.

Good day, and thank you for standing by. Welcome to the Predictive Oncology Q2 2023 Earnings Conference Call. At this time, all participants are in a listen-only mode. After the speaker presentation, there will be an opportunity to ask your questions. Please be advised that today's conference is being recorded. And I now, would like to turn the conference over to your speaker, Mr. Glenn Garmont, Investor Relations. Mr. Garmont, please go ahead.

Welcome, and thank you, everyone, for dialing into the Predictive Oncology second quarter 2023 earnings call. First, you'll hear from our Chief Executive Officer and Chairman of the Board, Raymond Vennare; then our Chief Financial Officer, Bob Myers, will review our financials. Finally, Dr. Pamela Bush, our Chief Business Officer, will join Raymond and Bob to answer any questions that you may have. Certain matters discussed on this call contain forward-looking statements. These forward-looking statements reflect our current expectations and projections about future events and are subject to substantial risks, uncertainties and assumptions about our operations and the investments we make. All statements other than statements of historical facts included in this call regarding our strategy, future operations, future financial position, future revenue and financial performance, projected costs, prospects, plans and objectives of management are forward-looking statements. The words anticipate, believe, estimate, expect, intend, may, plan, would, target and similar expressions are intended to identify forward-looking statements, although not all forward-looking statements contain these identifying words. Our actual performance -- future performance may materially differ from that contemplated by the forward-looking statements as a result of a variety of factors, including, among other things, factors discussed under the heading Risk Factors in our filings with the SEC. Except as expressly required by law, the company disclaims any intent or obligation to update these forward-looking statements. And now I'd like to turn the call over to Raymond Vennare, Chief Executive Officer. Raymond?

Thank you, Glenn, and good afternoon, everyone. During the second quarter of this year, we continued to make significant progress in growing our pipeline with biotech and biopharma companies as well as research institutions looking to incorporate artificial intelligence and machine learning into their early drug discovery process. The importance of our differentiating pedal platform, which includes our vast proprietary biobank of more than 150,000 heterogeneous tumor samples and more than 200,000 pathology slides combined with our CLIA-certified AtLab is beginning to resonate in the market. We are the only AI-powered company capable of predicting clinical success in the very early stages of drug discovery and supporting those predictions with actual in silico modeling and bench level experimentation. This is only possible because we are able to introduce the human element of petrogeneity far earlier in the drug discovery process, essentially looking 5 years into the future of drug development in advance of clinical trials. As I have mentioned before and for those unfamiliar with our company, the word heterogeneous is a key descriptor for predictive oncology. Even though many patients are diagnosed with the same type of cancer, each of those tumors respond differently to a particular cancer therapy. Each tumor and every response is unique. Understanding drug response in a heterogeneous population is invaluable along the entire continuum of drug discovery through drug development. Our unique combination of assets and capabilities offers drug developers, a multifaceted value proposition that includes, first, the mitigation of clinical risk at the most critical stage of drug discovery. Second, by identifying and validating drug targets sooner and thereby avoiding unnecessary trials that are likely to fail later in development. The potential exists not only to significantly reduce the cost of drug discovery, but potentially to expand the drug development pipeline; and third, by accelerating early-stage discovery, replenishing pipeline and optimizing clinical development. The commercial life of these drugs under patent exclusivity is extended and expanded. Clearly, the emergence of AI is fundamentally changing how drugs are discovered and subsequently developed, and we are at the forefront of this exciting transformation. It is well known and generally accepted that approximately 95% of drug candidates are never approved. But with predictive oncology's capabilities, our partners essentially have the ability to look into the future of drug response and to confidently anticipate clinical validation with much lower financial risk and therefore, a much greater likelihood of commercial success. The global artificial intelligence in drug discovery market was valued at $1.1 billion in 2022 and is expected to expand at a compound annual growth rate of 29.6% from 2023 to 2030. The growing demand for the discovery and development of novel drug therapies, a fresh approach to drug repurposing and the need to replenish product pipeline as patents expire are the driving force behind this market growth. Again, with our highly differentiated portfolio of assets and capabilities, we believe that we are incredibly well positioned to occupy a leadership position in this emerging field. This year, for the first time, we had a very notable presence at the 2023 Bio International Convention, which was held in Boston in June. Bio, which stands for Biotechnology Innovation organization is among the most widely attended industry conferences in the world dedicated to partnering and business development within the life sciences. During the conference, our Chief Business Officer, Dr. Pamela Busch, was invited to deliver a presentation on the importance of addressing patient heterogeneity in drug discovery, the advantage of introducing active machine learning into that process, which, as I just mentioned, is a key differentiator for us and an important component of the lab experiments that support or refute the predictions that come from pedal. Also, during the conference, we met with more than 30 customer prospects, several of which have led to substantive ongoing discussions. Annual conferences like Bio are critical to raising awareness of predictive oncology and unique value that we can deliver to our customers. And we will certainly be participating in additional industry-related events in the future. For example, since Bio, we are in active negotiations with a key European player in the formulation space to out-license our proprietary rapid formulation technology for use in a prescribed territory which effectively would expand our reach into Western Europe. Those discussions are ongoing and a term sheet is now being drafted. Again, for the benefit of those who may be new to our story. At the core of our offering is our pedal platform. As we have said before, Pete is comprised of several interrelated components. It is the application of artificial intelligence as a tool that is directed by rigorous scientific experimentation conducted in our own laboratory, which is informed by the most significant resource at our disposal, which is a biobank of more than 150,000 tumor samples and the drug response data derived from those samples. These 3 things comprise the pedal platform. This brings us to our core machine learning core, which means computational research engine, which is a key differentiator -- while Artificial intelligence refers to the programming of a wide range of human tasks, machine learning fundamentally is the ability to make predictions based on data and the data that we are feeding into core is data that our scientists provide as a result of scientific experimentation conducted in our laboratory and informed by our vast biobank tumor samples. We conduct laboratory experiments to validate in silico analysis to prove or disprove the viability of drug compounds scientifically not just statistically. This is our value proposition. This is what tests us apart from all other AI drug discovery companies. As the term machine learning implies the more data that we feed into the system, the more accurate as predictions become over time. Pete has been scientifically and technically tested, validated and verified. Pete can predict with 92% accuracy whether a tumor sample respond to a certain drug compound or not. And in so doing, Pedal can inform the selection of drug tumor combinations or subsequent in vitro testing and facilitating go/no-go decisions before investing in costly and time-consuming later-stage in vivo human trials. Last quarter, we spent a fair amount of time describing our recent contract successes, including the U.K.'s Cancer Research Horizons, which is abbreviated CRH, Evergenix, Sugen and Integra Therapeutics. CRH is the world's largest private funder of cancer research with a network of 4,000 researchers and an annual budget of more than US$370 million. They have provided significant funding that has resulted in the launch of 11 cancer therapies currently on the market and provide critical support for an additional 160 compounds that are in clinical development. Our partnership with -- we'll leverage pedal to develop the first ever genomic-based approach to precision radiation therapy, utilizing artificial intelligence to identify or develop novel or repurpose radio protective or radio sensitizing drugs or therapeutic compounds. There are at least 3 paths for commercialization. First, screening for interaction between patient tumor samples and therapeutic compounds; second, the identification and development of a novel or repurposed radio protective or radio sensitizing drug; and third, the screening of individuals for radiation sensitivity and personalized response to therapeutic compounds. In addition to existing contracts with biotech and biopharma companies, Predictive Oncology and Flu gen are collaborating on a next-generation vaccine related to respiratory diseases for which a Phase IIb grant has been submitted to the NIH. And finally, we are working with Integra Therapeutics, a very well-respected leader in the development of next-generation gene writing tools to advance gene therapies. We are currently preparing to scale up expression of their novel gene delivery protein, which if successful will secure a contract for the ongoing production of that protein. I highlight these contracts, again, not just to demonstrate that our offering is resonating quite clearly in the market, but also to illustrate the many ways in which our capabilities can be incorporated in very disparate clinical development processes. As I mentioned earlier, we have a very robust business development effort in place. And I believe we will be announcing additional collaborations in the coming months, including new or expanded contracts with CRH. It is worth repeating that pedal drug discovery contracts have significant value, but the sales cycle can be lengthy. To complement these efforts, we also have a very active biologics business where in formulation development and solubility testing are provided and by which we are compensated by our pharmaceutical development partners on ACE for service basis. This is relevant because protein therapeutics play a meaningful role in almost every field of the medicine from antibodies to enzymes and hormone treatments, the number and frequency of protein therapeutics brought to market has increased dramatically. But for these therapies to be effective, an optimal dose of those therapies must be properly circulated, delivered and absorbed in the body. Not unlike the efficiently predictive accuracy of the panel platform for drug discovery, our biologics capabilities enable us to effectively streamline and accelerate the formulation process, identify alternative and potentially more viable formulation and amplify the amount of protein actually being produced. I point this out because our company is well positioned to generate near-term formulations revenue in support of building a pipeline of milestone-driven pedal contracts. I would now like to address some rather noteworthy additions to our newly formed Business Advisory Board, beginning with Dr. Bernard A. Harris, Jr. Dr. Harris brings a wealth of clinical business and operational health care expertise to our Business Advisory Board. He currently serves as Chief Executive Officer and Managing Partner of -- for sales Ventures, a venture capital firm that supports and invest in early to mid-stage health care company. He is also the Founder and serves as Chief Executive Officer and Director of the Harris Institute and Foundation, a nonprofit organization that serves socially and economically disadvantaged communities, striving to reach the most underserved populations in the areas of education, health and wealth. Dr. Harris serves on several boards, including Ration technologies, U.S. physical therapy, MassMutual Life Insurance Company and the Texas Medical Center. He has a very diverse and distinguished background, including many years as an astronaut, serving on multiple space shuttle missions and being recognized as the first African-American to walk in space. We also announced the addition of Biopharmaceutical finance veteran Andrew Einhorn to our Business Advisory Board. Mr. Einhorn consults for Danforth Advisors and agency with deep institutional knowledge of the business of life sciences from strategy through execution where he provides financial advisory services to public and privately held companies and with appointed Interim Chief Financial Officer of Cognition Therapeutics in August 2022. Previously, Mr. Einhorn served as Chief Financial Officer of RV Hell Pharmaceuticals formerly known as Osmotica Edge Therapeutics and was Co-Founder and CFO of Oceana Therapeutics Esprit Pharma and ESP Pharma. As our momentum continues to accelerate, the Business Advisory Board's insights, expertise and perspectives will be invaluable in our efforts to deliver unique solutions to our drug development partners while creating lasting value for our shareholders. We will continue to look for outstanding candidates to add to the diversity, backgrounds and perspectives they were seeking to round out our Business Advisory Board. Before turning the call over to Bob to review the financials, I want to close with our recent announcement that we have moved our corporate headquarters from Eagan, Minnesota to Pittsburgh, Pennsylvania. Pittsburgh is a global life sciences research and technology hub and the location of our main laboratory facility. With this move, Pittsburgh is now the epicenter of our company's center for artificial intelligence and clinical operations, further strengthening our commitment to scientific discovery and growth. At this point, I will turn the call over to Bob Myers, our CFO. Bob?

Thank you, Randy [ph]. We ended the second quarter 2023 with cash and cash equivalents of $14.8 million as compared to $22.1 million as of December 31, 2022. In addition, we have 1.8 million outstanding warrants that represent an additional source of capital. We have no debt, so our balance sheet is very strong. As of June 30, 2023, stockholders' equity stood at $14.7 million as compared to $21.8 million as of December 31, 2022. We recorded second quarter 2023 revenue of $490,110 and as compared to $371,591 for the second quarter of 2022. Our gross margin in the second quarter 2023 was 67% as compared to 64% for the second quarter of 2022. Operating expenses were just under $1 million in the second quarter of 2023 as compared to $900,000 for the second quarter of 2022. Net cash used in operation activities were $7 million in the first half of 2023 as compared to $6.4 million for the comparable period in 2022. Net cash used in investing activities was $0.3 million for the first half of 2023, which was consistent with the comparable period in 2022. That concludes our financial summary. You can find additional details on our 8-K containing our earnings press release as well as our 10-Q, which is on file with the SEC and also available on our website. So with that, I'm going to turn the call over to the operator for Q&A. And as a reminder, Dr. Pamela Bush, our Chief Business Officer, is also available for this segment of the call.

Thank you. We will now be conducting a question-and-answer session. [Operator Instructions] Thank you. Our first question comes from Michael Broadbent [ph], a private investor.

I appreciate the call. I wanted to ask the same question I've asked at a couple of the others. Given the trajectory of the company and the increase in expenses, obviously, there's a lot of things still in place. So what is -- is there a new time line that the company will achieve at least a breakeven on operations because the cash burn still has me worried about a potential offering, even though the warrants are still there. A second part of that question is, do the warrants -- at what price would they be exercisable given if there is a raise necessary in the next year?

Bob, do you want to take that? Or do you want me to?

Sure, I'd be glad to. Michael; so to answer your question, our expenses in terms of burn are still rolling along at about [indiscernible]. We had $18.5 million in the bank at the end of March 31, and we're sitting with about 148 in at the end of June. So that rate is pretty consistent. We're solid certainly for moving ahead over the next year and the anticipation and forecasted revenue that we believe will be coming in. And let's take it that way, revenue, let's say, cash from deals that we have, revenues being recognized is different from the cash that we may earn from some of these deals. We'll certainly assist in maintaining our run. In terms of the warrants, right now, the lowest price warrants is $14. And as you know, we were at $4.7 to date in terms of our price. So -- but there's a lot we can do with the warrants, and there's also, as you said, always a potential to raise. But Raymond and I have always been very honest and said to the shareholders that we're going to try to do everything we can to not do another way and to try to bring our cash levels up through revenue and the business we do continually and that is our aim.

And Michael, I would add to that, that we are obviously scrubbing the budget. There are a couple of ways that we're going to address this. One is in order for us to extend the runway we have to reduce the cash burn. So we're certainly looking at that. The balance, of course, is to take advantage of these opportunities that are in front of us, we have to spend money to do that. So we win some of these contracts and need to hire people and get some equipment, then we're going to have to do that as well. But we are acutely aware of that balance, and we're keeping an eye on it literally on a weekly basis.

Okay. And then on the company's current trajectory, is there a potential time line for breakeven on the EPS or we have still a year or 2 years out, 6 months? Any kind of indication you can give based on current forecasts.

Right. Mike, it's a great question, and it's a difficult one to answer based on forecast without a historical knowledge because, as you know, Petalas new. We've had our first deal with CRH, and I think we have a lot of prospective deals upcoming. But without seeing these come in and without knowing exact dates, it's difficult for me to give you an exact date with a breakeven. Our goal is to do so by the end of 2024 or sooner. But a lot depends on how quickly we can turn those sales into revenue and close other contracts.

I will say, Michael, that we've mentioned CRH several times, right? And I think everyone is very well attuned to the significance of that relationship. And we are actively -- I'm here at the laboratory right now. I'm doing a call from the laboratory, and we are working on that project as we speak. So no one is more anxious than we are to move that forward as quickly as possible. But as Bob said, we are doing on our end, certainly everything we can do. We have to work through on the other end, how long it takes our partners, our customers, our collaborators actually get us what we need and give the approvals and just keep the projects moving.

Thank you. There are no further questions. I would like to turn the floor back over to Raymond for closing comments.

Okay. Well, thank you, everyone. That concludes today’s call. We hope that you can take away from this call the fact that all of us at predictive oncology are very excited about the growth trajectory of the company. What’s been happening in the last few months, much of that what we’ve been talking about for the last few months is finally coming to fruition. So in the coming quarters, I would anticipate more collaborations and partnerships with some of the leading drug developers and research and academic institutions. They are critical to the process. We're also very excited to play an important role in the discovery of new oncology drugs. That’s certainly part of the relationship with CRH which we believe and everyone on this call, I truly believe understands the benefits of the patients, but will also create enduring value for our shareholders. So I want to thank you all for your support, and I look forward to the third quarter update, and I wish you all a good day and a good evening. Thank you.

This concludes today's teleconference. You may disconnect your lines at this time. Thank you for your participation.