Champions Oncology, Inc. Price & Performance (CSBR)

Good afternoon. I am Ronnie Morris, you of Champions Oncology. Joining me today is David Miller, our Chief Financial Officer. Thank you for joining us for our quarterly earnings call. Before I begin, I will remind you that we will be making forward looking statements during today's call and that actual results could differ materially from what is described in those statements. Additional information on factors that could cause results to differ is available in our Forms 10 Q and Form 10 ks. A reconciliation of non GAAP financial measures that may be discussed during the call to GAAP financial measures is available in the earnings release. Q3 marked a transformative quarter for Champions Oncology underscored by our record revenue of $17,000,000 and the successful closure of our inaugural data deal. Our core services business remains at the forefront driven by our industry leading PDX bank and its precisely characterized multi omic data, which has become the foundation for the pharmacology studies that have been used broadly by the biopharma industry. Throughout the year, we have dedicated ourselves to strengthening our teams and refining our processes, resulting in enhanced quality, increased efficiency and scalability, which in turn have led to improved cost management and profitability.

As we look ahead, we maintain a cautiously optimistic outlook for a rebound in our industry sector with customers beginning to expand their R and D budgets and a slight recovery in the capital raising environment for biotech industry. Despite the mild improvement in the sector, the environment remains tight leading to potential performance volatility. However, the overall trend suggests promising opportunities for long term growth. A significant differentiator for Champion has always been our PDX Bank, offering pharmaceutical and biotech companies invaluable insights for drug development. By consistently expanding our collection of unique tumor models and enhancing their characterization, we have developed a robust multi omic dataset with substantial potential for both drug discovery and development. This dataset serves as a vital resource for our pharma partners who gain access to model specific data. With the rise of AI, which can extract deeper insights from the biological data, the demand for our dataset has notably increased in both breadth and depth. Recognizing the shift, we are actively exploring ways to extract greater value from this data. The recently closed data deal exemplifies our strategic vision where we licensed our existing deep multi omic dataset, while also acquiring prospective omic datasets from our unique bank of tumor models.

This continued expansion of our dataset aligns with our mission to create the world's most comprehensive biological dataset from a clinically relevant tumor population. Such a dataset aims to bridge the gaps in existing data using used for AI and ML mediated discovery workflows, ultimately transforming how the biopharmaceutical industry approaches target and biomarker discovery as well as pipeline management. Over the past few years, we have worked diligently to enhance this data platform, pioneering the use of the multi omic datasets in oncology discovery. The biopharmaceutical sector is now recognizing the immense untapped value within this type of dataset, shifting away from classical datasets that offer broad insights, but lack depth. We are well positioned to take the lead in this evolving landscape, generating significant traction and enthusiasm for our initiative to build the world's deepest clinically relevant multi omic dataset. However, I must caution that while we are excited about the initial validation of our strategy and continue to engage with other potential customers to build our opportunity pipeline, it remains premature to forecast the number of deals, their average size or the frequency with which they will occur. Consequently, we are not yet in a position to project the data revenue contribution to our overall results or its impact on our bottom line.

In the coming quarters, we hope to secure additional deals that will provide clarity on these important questions. Regarding the Karelia, our wholly owned drug development subsidiary, we are highly optimistic about the targets and compounds we have developed using our proprietary data. Our team is actively engaged in discussions to raise capital for the company, while carefully weighing the impact on our bottom line results. Despite the challenging funding environment, we have partnered with experienced bankers to bolster our capital raising efforts and both we and our advisors remain hopeful about the outlook. In summary, as highlighted during this call, Q3 was a groundbreaking quarter for us. We are excited about the potential of our core business and although we face some challenges, we believe we are on a path towards long term growth. The successful completion of our first data deal represents an initial validation of our strategic vision signifying that our data asset is poised to evolve into a transformative data business for Champions. Now I will hand the call over to David Miller for a more detailed review of our financial results.

Thanks, Ronnie. Our full results on Form 10 Q will be filed with the SEC by Monday, March 17. As Ronnie highlighted, we had a record breaking quarter with total revenues surpassing $17,000,000 and adjusted EBITDA hitting a record high. Research service revenue was $12,500,000 compared to $12,000,000 in the year ago period and our data revenue contribution was $4,500,000 reinforcing the early traction of our new platform. On a GAAP basis, our income from operations for the third quarter was $4,500,000 compared to a loss of $2,600,000 in the prior year. This included $600,000 in non cash expenses related to stock based compensation and depreciation. Excluding these items, adjusted EBITDA was a record $5,200,000 compared to an adjusted loss of $1,700,000 in the prior year. Turning the focus to our cash based results. Total cost of sales was $6,600,000 compared to $7,800,000 in our third quarter last year, a decrease of 16%. The decrease was primarily due to a reduction in salary expense, other lab costs and outsourced lab services. Our gross margin for the quarter was 61% listed by the high margin data revenue. Our research service margins also improved, increasing to 48% compared to 35% in the same period last year.

Our research service margins will fluctuate over the next few quarters with some expected volatility in revenue and cost of sales, but we anticipate long term margin expansion exceeding 50% as long term revenue grows. Our operating expenses reflected our commitment to disciplined cost management. Our R and D expense declined $500,000 or 21% to $1,700,000 as we optimize spending while maintaining key investments in our core business. Our sales and marketing expenses remained stable at $1,800,000 and our G and A expense declined $200,000 to $1,800,000 primarily due to reductions in salary expense. Summarizing our year to date results of fluency quarters, flu revenue was $45,000,000 compared to $36,000,000 for the first three quarters of twenty twenty four, an increase of 22%. Total cost of sales was $21,000,000 compared to $21,900,000 a decrease of $900,000 or 4%. Total gross margin was 53% compared to 40% for the same period last year with improvement coming from the high margin data revenue along with the operational efficiencies implemented which enabled us to improve on our revenue conversion and maintain our costs. Research service margins were 48% compared to 40% for the three quarters ended 01/21/2024. And total operating expenses were down approximately $3,800,000 compared to last year, primarily from reductions in R and D expense.

There was a total adjusted EBITDA of $8,300,000 compared to adjusted loss of $4,800,000 through the nine months of fiscal twenty twenty four. Now turning to cash. We ended the quarter with $3,200,000 of cash on the balance sheet and no debt. For the quarter, cash generated by operating activities was $900,000 and cash used in investment activities was approximately $500,000 The net $400,000 quarterly increase in cash was primarily from an improvement in operational results offset by an increase in accounts receivable. Our balance sheet is solid and our cash position is poised to increase in the coming quarters as our long term operational results continue to improve and we collect on our new data revenue stream. To summarize, Q3 was a milestone quarter with less than financial performance and successful execution of our First Data licensing agreement. While we anticipate short term volatility in research revenue, we remain confident in our long term growth trajectory. We have reaffirmed our full year revenue growth guidance of 10% to 15% and continue to focus on expanding our data business, enhancing profitability and driving shareholder value. We look forward to updating you on our progress during our near end earnings call in July.

We'll now open the call to Q and A. Thank you. At this time, we will be conducting a question and answer session. The first question comes from Matt Hewitt with Craig Hallum. Please proceed.

Hello. This is Tolf Korn on for Matt Hewitt. So I don't know if I missed this. You guys kind of cut out there for a little bit. But regarding the licensing deal, could you please indicate like how it's constructed? And are there any other opportunities in the pipeline? Thank you.

Yes. So the licensing deal that we signed was for a portion of our data, and it was a one time fee. And in terms of the pipeline, we are actively talking to multiple partners and customers from the biotech and pharma industry about the power and the value of our data. And that's something that we hope to continue to discuss over the next coming quarters.

And then given the uncertainty we've seen in the past few weeks regarding tariffs budget cuts, do you see any impact on your conversations with customers about those?

Yes. I don't know if the tariffs themselves necessarily have impacted us, but certainly it continues to be a tighter environment out there. And it's something we watch carefully, I think, to a certain extent based on our superior reputation as well as that we work with many, many companies. I think it's shielded us a little bit from the environment, but it still remains a tight environment out there, especially in the biotech sector. And so I don't know if the tariffs have had any specific effect and it could be too early to see those effects. But certainly with regard to the biotech sector in general, I think it's still not as strong as we had seen it a couple of years ago and as strong as we would like it.

Okay. So then I would take it with the weakness you're seeing in the biotech sector, how is that directly translating to the implementation of these early studies and the demand from customers there? Or is that not as direct as I'm thinking?

I think it certainly had an effect. I think we have done as we've talked about many years, we've done a lot to weather that both on trying to be more careful with our customer base and focusing more on some of the larger biopharmas over the last year and a half, as well as on the operational side, just making sure where our processes are in place and we're much more efficient and scalable. So I think we've attacked the tough environment both from a customer acquisition as well as an expense perspective. Having said that, it is still a challenging environment out there, but I think we've been handling it well. Have you seen anything that gives you hope coming up in maybe starting this year that there will be a turnaround in customer demand, specifically in biotech?

I think that it's sector specific. I think that there is certainly still a lot of investment in the pharma and biotech. There is still certainly a lot of investment in oncology. There are definitely pockets of certain types of targeted therapies that continue to be exciting. So while I would say it's definitely still a mildly challenging time, I think there's still a lot of activity. And I think it's certainly slightly better than it was, let's say, a year and a half ago. So there are some silver linings, I just don't think that it's gotten back to the place where we saw it a couple of years ago and where we all wanted to get to.

Okay. That's all for me. Thank you. Welcome.

The next question comes from Maj Sabin with GEO Investing. Please proceed.

Hello. Hi. Thanks guys. It's Maj Swayedan by the way from GEO Investing. Relatively new to the story, although I saw the company for a long time but never really got into it much and we started covering the company recently. And this whole data thing really is very intriguing. So I have two questions right now. The first question being around forgive me too for my ignorance regarding that subsidiary you talked about that you might have to raise some capital for that subsidiary. Can you give me some color in terms of are you raising money through subsidiary, the company's parent company? And what does it mean for capital structure for the company? So that's what are the common capital raising mechanisms you're looking at to do that? And as an investor, how should I think about that? So I'll pause for that answer and then come back with our next question.

Yes. So a couple of years ago when we decided that our data and we had become profitable and we decided that we really wanted to focus a little more on our data, we had a couple of different kind of vectors that we were looking at. One was just the raw data and the value of the data and one of the others was we had this data, we had a lot of deep biological data, a lot of response data and we felt like that would be a great place to see if we could find some targets and start to develop some novel drugs against these novel targets. And that's kind of what we set out to do. We're really excited about that effort. It's a separate company. It's a separate team. Legally, it's been separated from champions. It's a true spin out wholly owned because we're right now have been the only one funding it. But we got to the point now where Champions can't continue to fund it because we really wanted to get to Phase one, Phase two trials and that requires a lot of capital. So we're out there raising capital. Our expectation after we raise the capital is that champions will retain a percentage of those businesses.

It will be an asset. It will have a different investor base and which is a different type of investor base than Champions Oncology investor base. It's more of a drug discovery investor base. And that's kind of how we're thinking about this and that's what we're out there trying to raise money for.

Excellent. So you guys aren't good out there raising equity for this. You're looking for just capital now outside CSBR's capital structure to help kind of fund this.

So this isn't going to affect our ownership interest in C and B R's cash flow.

Right.

Yes.

It's not going to affect the cash flow and it's only going to be an asset that hopefully if we raise money at attractive valuation is going to be additive to the value of a Champion's shareholder.

Excellent. Excellent. All right.

So on the data side, this new what you're doing now, I think is very awesome. And I think it's where a lot of the industry is going or an opportunity that I think others are kind of exploring. Jens has talked about it a little bit. I think even the administration has talked about using AI to kind of help with cancer research. But the question I have more here is, I mean, I know this is kind of a new model for you and you're kind of maybe, I'm assuming kind of exploring how you're going to price the model. So this was sold like, I guess, a licensing fee. So are you exploring other ways of maybe selling this data as you move through this and understand it more and what your customers want? I'd like to understand maybe before I have my third question, what that might look like in the future?

Yes. We're exploring all aspects of so if you think about we have an asset that we believe is valuable, it's our data. And then there are customers, and customers come in different sizes and flavors and there's a couple of different ways you can license that data. You can license it out for a fee, for a license fee, you can license it out for a fee plus some type of royalty or milestones and there's all these different levers. And so we're certainly having discussions to certain smaller biotechs that they're obviously much more interested in potentially giving royalties and milestones for some of the larger pharma. They're more interested in just paying for license fees. So everyone's a little bit different. We're looking at different models. Right now for us the most important thing is to understand the value and to speak to enough customers to really get them to understand the value of our data and to use some of our data and play with our data so they can understand why this is so valuable. So that's the first step and that's kind of the step we're in right now.

Okay. So over time, you would anticipate potentially if this works out that you'll have a mix of licensing like large licensing data, but also this may be a recurring revenue component to some of the type of ranges you might get into depending on the biotech company, right, or on the company?

Yes, it's certainly something we think about a lot and we're looking at different models and we're not reinventing the wheel. These have been done before. And so we're trying to learn and we're trying to understand what the market will bear. And it's going to be a little bit different for different customers, but we're early on and right now we're just so we're excited about the first deal, which is proof of concept and we have a couple others in the pipeline. And as we continue to go, I anticipate like the rest of our business, we will continue to evaluate other opportunities and other possibilities of how we structure deals. Okay. And in regards to what you did, this is definitely a very high margin high gross margin business that was right to the bottom line. Okay. Just depending on licensing or recurring. All right. So on the now in your last conference call, you kind of mentioned and you mentioned it today kind of little bit that a lot of this kind of data movement this movement to go data licensing model, a lot of it came from actually customers were asking you, right? There was a lot of inbound kind of inquiries from your customers.

So I'm wondering how that is that where most of the interest is coming from? Was this new contract, for example, from a existing customer or new customer? So I guess there's two things. What opportunity do you see within your own customer base, right? And do you see this as an opportunity to expand your customer base? That's a long way from now. Yes, I think it's both. You have to remember, we work with between 405 of the pharma and biotech companies. So we work with a large number of the biopharma companies within oncology. So we're fairly well known and we work with a lot of them. So it's not like so yes, we certainly have a large audience. We're out there talking to them about our data. Clearly, still the bread and butter and the core business is the largest part of our business where people send us their compounds and we do studies for them and we give them a lot of valuable insights on their drugs. But the plan is to both for our customer base and for our non customer base to be going out there and talking to people about the value of our data and why we think it's important.

Okay. And then when the customer maybe, let's say, like you said, like this time, has a buys a licensing arrangement with one big one big type of data, I'm assuming. Do you see the opportunity is this one and done with the customer? Is there reason for them to keep coming back? I'd like to understand that a little bit. I know there is an option for them to come back with $3,000,000 a year, but maybe talk about that a little bit.

We see data and this is I think a little bit of the difference between us and a lot of other groups. We've always seen data as something that continues to grow. So we have a hundred I'll give you an example. We have a hundred lung cancer patients and our first layer of data many years ago was a genomic profile and then we went to a transcriptome profile and then we went to and then we added a layer of proteomics and phosphoproteomics and then we added other layers. So we continue to add layers so that the deeper understanding of the interactions of all the pathways within that tumor and also the interaction with different responses that that tumor has had both in the clinic and in the PDX model. So we keep enriching the data and that's the beauty of kind of our bank and our data. So as there's more opportunities to get more refined with the characterization, we keep characterizing these tumors and understanding the biology deeper and deeper. And now with the advent of AI, before it was much more complicated because we created a ton of data. But now with the advent of AI, these datasets just become more and more important and there's a lot that can be generated and learned from it.

So yes, our plan is to continue to generate more data from these data sets and that seems to be resonating well with our customers.

Okay, great. Great. And just can you give me an idea I guess an idea in terms of the competition you're seeing out there? I think you said you wanted to be like a leader in this. Are you seeing a lot more companies that you compete against do the same thing right now? Or you think you are like one of the first ones really to kind of embark on this whole thing?

Yes. So I think a lot of companies have been selling data for a long time. I think for a long period of time, most of the companies have been selling very, what I would call, longitudinal data with hundreds of thousands of patients with a small amount of data on each patient. We're one of the first who are doing it a little bit differently, where not as many patients, but with each patient and each tumor, we're going very deep and really understanding the interactions at a very deep molecular and a biological level. So from a discovery standpoint, from understanding the effect of a drug on the biology of a tumor and looking for new targets, I think we have a very unique approach and I think it's the right time for it because the capabilities with AI and machine learning really avail this type of a data set to be able to unearth some of the deeper insights. So that's kind of a little bit of a different approach that I think is the right time for this right now. And that's our goal.

Okay. And my last question, going back to your legacy business, are you seeing AI helping you in your own kind of legacy business do your research for companies?

Not so much yet. We haven't really seen that effect yet. It doesn't mean it's not going to come. It's just right now we haven't really seen the impact of that on kind of the core business.

The next question is from Edward Gilmore, private investor. Edward, please proceed.

Just had a couple of questions. On the AI side of things with the data, do you see a potential for the data to be used outside of drug discovery and research, for example, maybe more in a clinical setting with identification and evaluation of tumors?

You mean in terms of like a biomarker approach?

Yes.

Yes. I've always felt I mean, we've always felt that there's two real best uses for our data, for the deep data of understanding these tumors. And one was from a discovery perspective and the other was from a kind of a biomarker perspective. The discovery perspective is kind of a is a better path right now. The biomarker path is still a super interesting path. It's just that for whatever reason, most of the biopharma over the last ten years have not been that interested in finding the right biomarker for the drug. A lot of reasons for that. And I know they talk about biomarkers a lot, but we really haven't seen that much interest in really understanding what is that super patient population that they should only go for in a trial. I think it's important to them to kind of figure out the trial to make sure the trial is successful, but I don't know that they're super keen on finding that very specific biomarker that's going to restrict or just kind of narrowly pick out the patients in the clinic that are only going to work for that drug. So it certainly could be a super good, it's certainly a super smart way to use our data to also look for clinical biomarkers.

But as of yet, that I don't think has been the driving force for people to use our data as much.

Okay. Thanks. We'll stay tuned for that. And then the second question, a couple of weeks ago, you guys put out a press release about the upcoming Association for Cancer Research meeting and announced that you had a number of abstracts that were accepted for presentation there. I wonder if you could just from your perspective, do investors kind of give a little bit more color on that and how excited you are and what you kind of expect to come from that? Because I know there's AI is going to be a heavy topic that's mentioned and talked about there.

Yes. We have always been an organization that's kind of not so much like a CRO, but more of a scientific leader and that's the way our partners see us. I think it was important for us to show that we continue to be on the cutting edge doing a lot of R and D and just continuing to be innovative and thinking about how do we develop the assays to just help the pharma partners that we work with just to develop the best drugs and get the best preclinical package is going to give them the best chance in the clinic. So we're excited about the continued number of posters because it shows that we just we continue to innovate, we continue to think of ourselves as an R and D organization to a certain extent, and we're excited about it. And certainly those abstracts will become available and you'll be able to read them.

Okay. Thank you. And sorry, one more quick question. On the PDX data side, do you have a team set up now internally that's leading that as far as like how you do customer acquisition or what's kind of the go to market strategy there? And then I'll drop off.

In terms of what? In terms of what? I'm not trying to understand the question.

In terms of how you're communicating to prospective customers about how they can find out that they have access to be able to license the data if they're a pharma or biotech company, just how they're discovering that they can find out?

In terms of the data side, yes, we have a separate team that handles we have separate team that handles the data side, we also have a team that handles just the core business, but there's a lot of crossover between because it's a lot of the same customers. So there's a lot of crossover between the regular sales team and the business development team as well as the team that's handling the data strategy.

The next question is from George Marimba with Pareto Ventures. Please proceed.

I had a question on this $5,000,000 license deal. Kind of roughly speaking, of all your data, the entire pie, how big a slice of the pie representatives feel? Is it 100%, five %? How much data did they buy for $5,000,000 out of the total data?

Yes, that isn't something that we have publicly announced. We don't really talk about kind of how much people pay for different data. Different people have different deals depending on early late. So that isn't something that we have spoken about publicly. Okay.

And on your kind of go to market on this internally, do you have a dedicated salespeople for this? Or how exactly are you marketing and selling this, these data licenses currently?

Yes, we have a dedicated team. We have a general manager, Matt Newman, we brought in the head of our data sciences. We have a couple of business development people who have a lot of experience in this area. So, yes, we have a team now assembled. It's a fairly new team over the last six months to a year, but we have a dedicated team that's out there talking about our data.

And did I hear earlier in the call that you do have a couple few that are in the pipeline in 2025 here so far?

I am sorry, can you repeat that? You cut out for a second.

Yes. Did I hear it right that you have two or three deals that are in the pipeline currently on data licensing deals?

I believe what you heard was we have a pipeline and we continue to talk to people and we didn't mention the number of deals that are in the pipeline. And again, I think that I'll just add that some of the deals will be large, some of the deals will be medium, some of the deals will be small. And I think the goal is to get people to utilize our data and continue to make them a believer and use more and more data over time.

Okay. All right. Thank you, Ronnie.

You're welcome.

We have no further questions in the queue. I'd like to turn the floor back to management for closing remarks.

Thank you very much. As we mentioned, this is an exciting quarter for Champions Oncology. We look forward to having our fiscal year end call mid July. So until then, stay tuned and we're excited about the progress that we're making and we look forward to following up with everybody. Thank you for joining.

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