Good day, everyone, and thank you for joining us today for the Lytham Partners Fall 2025 Investor Conference. My name is Joe Dorame, Managing Partner of Lytham Partners. I would like to welcome Scientific Industries, which trades on the OTCQB under the ticker SCND. For today's webcast, from the company are John Moore, Chairman, and Helena Santos, Chief Executive Officer. John and Helena will walk us through their slide presentation, followed by a brief Q&A session. John, welcome. I'd like to turn the floor over to you now. Thank you so much. Scientific Industries is a 70-year-old scientific instrument company, which has recently been transformed over the last five years by Helena Santos, our CEO, and at the recommendation of our board, to focus on digitally simplifying science and particularly life science. I'm going to talk to you a little bit about the transformation that's happened at the company and what our exciting growth prospects are going forward. Next slide. That's our safe harbor statement. Scientific Industries was started 70 years ago to make a product called the Genie, the Vortex- Genie. The company was tremendously successful. We sold to virtually every life science lab in the world. When I joined the company six years ago, Helena was paying a dividend. The company was very profitable. The challenge that Helena had was how do we grow the business? She bought a company called Fluorimetrix. She bought it for $450,000 in some stock. That company developed some very unique sensor technology that was licensed to a company called Sartorius. We collected over almost $9 million of gross royalties. It was a tremendous investment. We netted about $4.5 million. That gave us the insight to invest in a company called Scientific Bioprocessing. In the meantime, we've raised about $30 million. Helena sold the Genie business to METTLER TOLEDO for gross proceeds of $11 million. The company's now got a very strong balance sheet. We have no debt. We're growing a business called Torbal, which I'll tell you a little bit more about in a minute. That's got a growing profitable upside. It's an automation of pharmacy services. We're going to be basically doing a transformation of this company to an AI cloud-based machine learning system, which will be commercialized in the first quarter of 2026. Scientific Bioprocessing is our fast-growing, super high-tech business focused on synthetic biology and personal gene therapy technology. Next, if you could go to the next slide. A little bit of background about the company. Torbal was acquired in 2014. The company has around $3 million of revenue. What we've invested in is creating a family of digitally simplified pharmacy automation tools. This is to basically alleviate a huge problem right now in the pharmaceutical field where, with the graying of the American population, we don't have enough pharmacists. There's something called pharmageddon, which basically means there's not enough pharmacists to dispense all the pills that are being required. What we figured out how to do is how to automate that system. We have a very fast-growing product line. Scientific Bioprocessing was acquired in 2021. That company does about $1.7 million in revenue. We are currently investing, we've invested over $30 million in this product line to date. That contrasts with our approximately $7 million market cap. You can see we've invested a ton versus our market cap in this new product line. It's not completed yet. We'll give you more details about that, about the product roadmap. That'll be completed sometime over the next six to nine months. The company's based in Bohemia, New York. We have 50 employees. We have $11.5 million shares outstanding. We have approximately $10 million in cash and milestone payments from the Genie transaction, which we sold to METTLER TOLEDO. We have no debt. Next slide. Torbal is an icon in the pharmaceutical industry. The company's over 100 years old. We have the dominant installed base of scales in pharmacies. We believe that there's a big opportunity with things that are happening in the pharmacy field, including federal regulations for something called Track and Trace that requires automated tools for the pharmacist to be able to maintain and be able to track pharmaceutical dispensing. There's a target market of about 20,000 independent pharmacies and 48,000 chain and hospital pharmacies. We have invested diligently over the last five years to create the most complete line of automated pill counters at every price point: $3,000, $5,000, $14,000, whatever the pharmacy is looking for. We're the only supplier in the marketplace that has such a complete line. Where are we going next? We believe a product that we've introduced, the Workstation that was introduced earlier this year, is a potential game changer in the industry because it's the industry's first machine learning pill recognition system. We're the only cloud-based competitor in the space. Why is that important? It's important because every time a new pharmaceutical gets introduced, and the first time it's dispensed across our system of several thousand instruments, automatically all the other systems are updated. All our other customers' systems are automatically updated to have that new product that was introduced. We think that since none of our competitors have a system like that, we're going to increasingly distance ourselves and get more and more market share in this rapidly growing space. We're currently looking to accelerate the recurring revenue, which is to about 10% of total revenue. We have a subscription-based system on these systems. The future of our business is going to be in recurring revenue products like the VIVID automated pill counting system. Next slide. I'm going to talk a little bit about Scientific Bioprocessing. We believe that an investment today in Scientific Industries represents a deep value investment. Why? Because we're addressing a very large market, about a $2 billion market in biomanufacturing. We've introduced a new platform called the DOTS platform. What we do is we digitally simplify what is an incredibly complex system called bioprocessing. Bioprocessing is how you make large molecule drugs and large molecule products like fertilizers and flavors and fragrances using our incredibly simple and inexpensive system for manufacturing. Where are we today? We've invested about $30 million to develop and de-risk the technology. We have nine patents. Over 120 publications have been written about our technology. We have over 400 customers. Our business is around $1.7 million in sales. This is with an incomplete product. We haven't completed the entire product. I'll explain to you in a minute about what the product is and what remains to be developed. Where are we going? We're looking to complete the product roadmap in 2025 and 2026. We're looking to accelerate the growth of the product once we have a complete product. Our goal is to hit break-even by 2028. We believe we'll have in excess of $20 million in sales and 20% EBITDA by 2029. The products that we're developing are going to be incredibly important for creating a new environment in biomanufacturing, which is going to enable artificial intelligence. I'll explain why that's not easy right now and why it's going to be incredibly desirable by our customers. Next slide. We have a vision of how biomanufacturing is going to reshape global economies and capture potentially a $3 trillion market opportunity in the next decade. What Jensen Huang of NVIDIA says is, you know, what's the next big thing that's going to happen because of artificial intelligence? He says it's digital biology. That's a pretty safe projection on his part because the initial customers for artificial intelligence and NVIDIA chips were biological applications, like something called the AMBER system out of the University of California, San Diego, which used basically the NVIDIA chips in parallel processing, the GPU, to convert what was a protein folding model that was on supercomputers to less expensive parallel processing using NVIDIA's chips. That was the first commercial application of artificial intelligence. You're probably aware of the fact that DeepMind, the creators of DeepMind, which is an AlphaFold program, is a protein folding projection system, won the Nobel Prize this year. That basically used AI in the NVIDIA systems for projecting how proteins will fold. That's extremely important for biomanufacturing. What was important about that was AI used existing public sources of data on protein folding to be able to create that library. DARPA, which is, as you probably know, the inventor of the internet, the funder of the internet, has an important program in synthetic biology. What they're saying is that the big future in AI is to be able to combine what's called the dry lab, which is how you do computational biology using artificial intelligence, with the wet lab, which means being able to validate it with real-world experiments. How do you connect that world between atoms and bits? That's where we play a role. If you go to the next slide. What's the problem in synthetic biology today? There's a very high cost and 90% failure rate of what's called scale-up from the lab to commercialization. What they look to do in synthetic biology is to take small vessels where they do discovery and scale up through shake flasks to the system, the AMBER system that we licensed our sensor system to, and then to biomanufacturing. 90% of those scale-ups fail, and they typically cost at least $3 million. That's according to Boston Consulting Group. There's a real pain point in the scale-up of synthetic biology. What have we done about that? What we've done is we've created this DOTS technology platform, which has reduced the cost of experiments from $10,000 to $200 per experiment. What our thesis is, is that our customers are going to use these very inexpensive experiments to be able to de-risk the scale-up and manufacturing costs. Basically, we're creating a situation where our customers, for 10% of the cost and 10x the output, can do more experiments so that when they do scale up, they're ultimately successful. That's going to reduce the cost of drug development and improve the return on investment of our customers. If you go to the next slide. How are our devices used, and how does artificial intelligence improve the use of our devices? What we're doing is we're taking the most ubiquitous, the most commonly used vessel in biomanufacturing, the shake flask. We're putting the same type of monitoring control that's used on the same experiments that cost $10,000, and we're doing them for $200 per experiment. Why does that matter? It matters because we're creating a million data points per experiment from vessels that are normally just manually sampled. Instead of getting a single data point from an experiment, you're getting a million data points. Our customers are able to take those extremely large data sets and use it with artificial intelligence, large language models, to be able to predict what hidden insights are there and to predict what experiments they should do next and to improve the outputs and reduce the failure rate in the scale-up. If you go to the next slide. We address this $2 billion bioprocess market by being able to bring these established solutions to the most commonly used vessel, the shake flask. You can see on the right, the benchtop fermenter. These systems are very large. They typically cost between $125,000 to $1 million. What we've done is we've simplified it into this DOTS platform. It's very, very simple. If you go to the next slide, what we're doing is we're bringing the simplicity, ease of use of shake flasks, and the low cost, but also delivering the monitoring and the controlling of these much more expensive systems. What does our system consist of? It consists of the DOTS multiparameter reader, where we're able to read dissolved oxygen and biomass, temperature, pressure, and fluorescence. We have a very sophisticated multiparameter sensor. We have a feeding system, which is a single feed system. Right now, we have future generations of this coming up in the next year. We can actually feed either base or a glucose source into the shake flask. The great thing about our product is our customers have literally billions of dollars of investment in incubators and shake flasks. We're basically selling them an upgrade kit. We have a very sophisticated software program, which is also very easy to use. We have a single-use product, which is a sensor that you drop into the shake flask. We have a very nice margin of greater than a 90% margin on that. That enables the monitoring of real-time dissolved oxygen. In the first quarter of next year, we'll be coming up with pH. Sometime next year, we'll be coming up with glucose. This is an optically read sensor. What we're doing is we're closing the gap between what can that $100 million device do versus what can our device, which costs around $5,000 per system, do, reducing the gap between what they can do and what we can do, and therefore enabling our customers to buy lots of devices to be able to do lots of experiments and to be able to use AI to interrogate that data. One of the great things about our product offering is that as we've been introducing the product, as we've been using it, they've been buying it, even though it's not yet complete. Some of the biggest names in life sciences: Pfizer, Lonza, Genentech, Google, Amgen, these are all names that you know. There are different markets that we're going after. The first one is microbial cultures. This is where all of our 400 customers currently exist. We've sold over $7 million of devices over the last several years. We have an established brand. We have thousands of followers on LinkedIn. We're growing into a much higher margin business, which is the mammalian cell culture market. We just launched this product in Q1 of 2028. We have trials that have been done with the largest pharmaceutical companies in the world, all names that you would recognize. They're currently evaluating the purchases of our products. We are going to be launching AI programs with our customers in the near future. On the right, what you see is a reference here where one of our customers, Bond Pet Foods, used our systems to be able to show that they made a $55,000 investment. They were able to realize a $70,000 savings, a nine-month return on investment. These devices have a very quick return on investment for our customers. Please go to the next slide. I'll hand over the call now to our CEO to discuss our balance sheet. Sure. As John mentioned before, we have a nice clean balance sheet with no debt. As of June, we did show cash and investments of about $1.3 million, but that does not reflect the results of the transaction that occurred on August 7, when we sold the Genie portfolio to METTLER TOLEDO. What that did for us, it increased our cash position by about $10 million on a net basis by the time it's all said and done. As a result, we have about currently 20 million shares outstanding on a fully diluted basis between the actual shares that are outstanding and all the options and warrants that are out there as of today, some of which are not fully exercisable as of yet, but on a fully diluted basis, that's what we are showing. Great. I'd like to just conclude by saying that Helena had very successful licensing of our sensor technology to Sartorius. They sold billions of dollars of equipment, making what we'll call the, let's call it the AMBER system, but we call it, it's like the mainframe computer of the synthetic biology revolution. We're coming up with a product which costs about 5% of the CapEx and about 10% of the OpEx of operating that system. We believe that we are going to be essentially the iPhone of the synthetic biology revolution. Why does this matter? It matters because as medical science continues to advance, as new therapies like personal cell and gene therapy advance, the industry is going to need tools like ours to be that iPhone, to basically dramatically bring down the cost so that these life-changing miracles that are being developed by our medical establishment, as those are being brought to market, that they're able to be brought to market affordably, reliably because of technologies like ours. We consider ourselves kind of like the Apple of the genetic and gene therapy revolution. Thank you so much, and eager to answer any questions you might have, Joe, for us. Great. Thanks for that overview. Let's go over a few questions. First, can you elaborate on the rationale and timing behind the Genie division's sale? How will the $11 million in proceeds be deployed? Helena, do you want to answer that one? Absolutely. It was our plan to divest of the Genie portfolio because the Genie portfolio was quite valuable, as obviously evidenced by what we were able to obtain for the sale of it. The proceeds enable us to concentrate on the two growth businesses that we currently have. Also, as a side benefit, it achieves the goal of us getting one step closer to becoming an AI-enabling business in the future and concentrating particularly on those two businesses. Got it. That makes a lot of sense. Next, in your Q2 earnings release, you mentioned an upcoming Nature publication. Can you share a little bit more about it and what the study's focus was, and how did the DOTS platform contribute? That was in support of a project at the University of Delaware. The researchers were doing a study in gene therapy, and they had proven the technology at a small scale in microtiter plates, but Nature had come back to them and said, you know, we'd like to see a larger scale proof of concept. They used our devices to be able to create that larger scale. The article was ultimately accepted in Nature, and we're excited about the upcoming publication of that story. Great. That's very interesting. As you mentioned, you've got a number of trials ongoing. What can you share with us on key outcomes using the DOTS platform? How do you think they'll inform future enhancements? Joe, the question was, what is the product roadmap? Is that essentially what the question is? Essentially, yes. Yeah. What a bioreactor does is it monitors dissolved oxygen, pH, and it actually controls the experiment so that it doesn't go out of what's called the design space. Shake flasks are obviously much less expensive. A shake flask costs around $10 as opposed to, let's say, $125,000 for a bioreactor. Up until now, there hasn't been any ability to monitor or control. Essentially, all they're able to do is do a manual sample. You have to stop the experiment, take a manual sample, and you only get one data point. The organism changes over time. Actually, the most common organism is called E. coli, and it's a living machine that's basically a factory which makes proteins. Like any living machine, it's got to be able to be produced in a controlled environment. That's not able to happen in a shake flask. What we've been able to do is we've been able to add the control piece, but with our liquid injection system, we've been able to do the monitoring piece where we're able to monitor the biomass, how many of the cells are produced, and what is the oxygen condition. The things that we don't yet have, but which are coming up, are pH control, which means whether the environment for the cells is too acid or too base. A thing that you can't even do in a bioreactor is something called real-time glucose. Those two additions will be coming in the next year. We think that that's going to be really the rocket fuel that propels our revenue dramatically higher and shows people what the real potential is of the $30 million we've invested to date in this platform. That's very helpful. I appreciate the detail on that. Shifting gears to Torbal, how does the VIVID's cloud-based approach enhance scalability, security, or compliance in a regulated pharmacy environment? Joe, I'm glad you asked that question because I think, as a matter of fact, I'd like to take a minute or two just to talk about that a little bit because I think it's that important for us to understand. VIVID's cloud-based architecture transforms scalability by enabling pharmacies to seamlessly share and synchronize data across multiple machines within a single account. This is important because it means that users can monitor all data transactions centrally, regardless of how many VIVID units they have and regardless of where they are. Other things such as updates are deployed instantly to every machine. This is also important because it ensures that all users always have access to the latest features, our security enhancements, and compliance requirements without any manual intervention. Our cloud model also unlocks real-time insights. We gather usage data on dispensing volumes, time cycles, and pharmacy activity, which not only helps us improve the platform itself, but also opens opportunities to provide value-added services in the future. Things like predicting and supplying pharmacies with consumables like vials and labels, all based on this usage data that we're collecting. VIVID is the only pill counter to make Medispan drug data available in real time to all the connected machines the moment it was released. Likewise, newly trained drug data is instantly distributed through the cloud to all the users. Finally, just looking ahead, the cloud makes it possible to rapidly deploy advanced machine learning algorithms to all customers at once. While machine learning engines can technically run locally, they do require constant retraining to stay accurate, something only practical at scale in the cloud, if that makes sense. Yeah, that's impressive. I guess since we're just about out of time here, we've got time for one last question. Looking forward, what are the priorities for the second half of 2025 and the keys to success that investors should be looking for in 2026 and beyond? In the second half of 2025, we're really focusing heavily on the new product development of our bioprocessing business. We have a product roadmap that John spoke about. That is our key focus because that is what our investors, our shareholders, are looking to see. We are keen on requiring ourselves of those deadlines to be met. We're also concentrating on the VIVID, and some of the proceeds that we received from the Genie portfolio sale are also being invested, likewise, in the VIVID product line so that we can, in the first quarter of calendar 2026, as John mentioned, introduce our newest addition to the line. Great. Before we wrap up, do you guys have any final comments? I would compare what we're doing to the invention of the PC. When the PC was first invented and Steve Jobs went to Don Valentine of Sequoia, you know, he was a great technology investor. Don Valentine didn't know what a personal computer could do. He said, "Why would I need a personal computer?" Things like VisiCalc, word processing, and the internet made PCs essential to everyday life. Essentially, what we're doing is we're bringing a device that the research community understands why it's important. As new things like miracles of personal cell and gene therapy come to fruition, our devices are going to become as essential to everyday medical processing as the PC is to everyday life for all the rest of us. Right. Again, thank you, John and Helena, and thanks everyone for watching. If you have any questions or would like to schedule a meeting with Scientific Industries, send me an email at dorame@lythampartners.com. Lastly, if you'd like to learn more about Lytham Partners, please visit our website at lythampartners.com. We hope you all enjoy the conference and have a great day. Thank you, Joe. Thank you.