Lantern Pharma Inc (LTRN) 2021 Q4 法說會逐字稿

Good afternoon, everybody, and welcome to the Lantern Pharma Fourth Quarter and Fiscal Year 2021 Earnings Call. (Operator Instructions) I am Nicole Leber with Investor Relations at Lantern Pharma, and I will be your host for today's call. I will be joined by CEO and President, Panna Sharma; CFO, David Margrave; and CSO, Kishor Bhatia.

We issued a press release after the market closed today summarizing our financial results and progress across the company for the fourth quarter and fiscal year 2021 and a copy of this release is available through our website at lanternpharma.com and where you can also find a link to the slides that management will be referencing for today. Following the safe harbor statement, Panna will provide an overview of Lantern Pharma's operational highlights, after which David will discuss our financial results, which will be followed by Dr. Bhatia, who will provide an update on our development programs. Finally, Panna will offer some concluding comments and then we'll open the call to the Q&A.

I would like to remind everyone that remarks about future expectations, claims and prospects constitute forward-looking statements for purposes of safe harbor provisions under the Private Securities Litigation Reform Act of 1995. Lantern Pharma cautions that these forward-looking statements are subject to risks and uncertainties that may cause actual results to differ materially from those anticipated. A number of factors could cause actual results to differ materially from those indicated by forward-looking statements versus the impact of the COVID-19 pandemic, results of clinical trials and the impact of competition.

Additional information concerning factors that could cause actual results to differ materially from those in the forward-looking statements can be found in our Annual Report on Form 10-K for the year ended December 31, 2021, which is on file with the SEC and available on our website. Forward-looking statements made on this conference call are as of today, Thursday, March 10, 2022, and Lantern Pharma does not intend to update any of these forward-looking statements to reflect events and circumstances that occur after today, unless required on law. The webcast replay of the conference call and webinar will be available on Lantern's website.

And with that, I would like to turn the call over to Panna, President and CEO of Lantern Pharma. Panna, Please go ahead.

Thank you, Nicole, and thank you all for joining us on our Zoom earnings call and webinar today. I'm really happy to be here with my colleagues David and Kishor in person and we have a significant amount of upgrades, progress and activity to share with you all across virtually every measure of our business. During 2021 and 2022, we've had a very productive and very fruitful time for our team. And I'm very proud of the efforts and achievements our focused team has made over the past 12 to 15 months.

Before I begin them, I'd like to take a moment to something more serious enough and share our concerns and voice our support for the people and families in the country of Ukraine. Violence and destruction in any form has no place in the economies and societies today. And I personally am joining with many other biopharma CEOs and companies in voicing our concern to the aggression in Ukraine from Russia.

Coming back to Lantern Pharma, I'm extremely proud, as I mentioned, of our team's efforts and execution in the fourth quarter and throughout 2021. We made meaningful progress in multiple fronts, clinically, technically, operationally and also on a regulatory front. Our proprietary RADR AI platform also has grown, it's now surpassed 18 billion data points and has grown by more than a 1,000% in the last year, significantly exceeding our growth expectations from earlier in the year and we've now up our target to 25 billion data points this year.

We've also grown a number of algorithms to powering the analysis and grown the classes of algorithms and our ability to manage the algorithms. Algorithms and data are critical pieces of driving insights that power our portfolio and help us develop new drugs faster and cheaper. This increase in the power of our platform and data points provides us with several long-term portfolio advantages.

First, it accelerates our drug development timelines by giving us ideas about the feasibility of different drug candidates or combinations and allows us to uncover new therapeutic opportunities like we did with ATRT that allows us to look at potentially in licensing new compounds with some level of derisk and allows us to find new uses for existing drugs in our portfolio that we've done now with LP-100 as we looked at additional tumor types.

It also allows us to develop insights in terms of how we can create combination therapy programs and my colleague will show a top order medicine of those first data we have and some combinations that we're approaching. Finally, very importantly, one of the biggest advantages, it expands our ability to collaborate with some biopharma partners. We believe that the platform is now to save, work and to use not only for our existing portfolio, but for many other drug development portfolios in oncology. This presents us with lots of new opportunities for value creation in the near term.

Obviously, the goal is to reduce the cost, reduce the risk and accelerate the timeline to develop oncology medicines by uncovering insights on drugs from interactions and developing companion diagnostic type approaches, potentially signatures that can be used, that are essential in understanding which patients are most likely to respond and which tumors are most likely to be sensitive to our drug programs, either mono or combination therapy.

The likelihood of bringing a drug to market is, on average, 5x higher by those that are developed with a biomarker signature than those that are not, which is a study done by Dr. Jason Parker from University of Toronto. Ultimately, RADR gives us the ability to potentially benefit and select patients that have the best option for our drug therapies or the combination therapies that we are uncovering at a fraction of the cost of traditional drug development. We plan furthering our data expansion and the curations data moving forward, but in very specific areas.

Let me talk a little bit about those areas. One of them was in hematologic cancers. We started campaigns and growing the number of blood cancer data points. We'll continue that focus here in 2022 and Kishor will talk a little bit about some of our insights into the blood cancer space. We'll also enrich our platform in pediatric and rare cancers.

As you know, we announced a collaboration recently with University of Texas, San Antonio with the Greehy Children's Cancer Center. We also plan on focusing on immuno-oncology related studies in trial this year where we expect to uncover potential new combination opportunities for 184, 284 and 100. In addition to the data points and data sets to RADR, we're also focused on the growth and evolution of our library of algorithms. Algorithms are critical because they are giving us new ways to correlate the data, finding new insights that allow us to automate the collection of data, automate the structuring of the data and it gives us ways to make decisions in a derisked and faster time frame.

These algorithms also allow us to rapidly identify cancer subtypes that may have gone unnoticed or have been fully understood and they provide insight into potential drug target interactions. These algorithms can also help further our ability to uncover patient groups that can respond to specific drugs, not only initially, but perhaps even over the course of treatment. Now with such an incredible assortment of both data and algorithms as it grows, we've also embedded in our management of the algorithms, a DevOps environment, machine learning, development and operations environment.

This is important because the management of algorithms becomes much more complex, especially when you're using multiple algorithms with thousands of potential parameters and you're using what we're beginning to use increasingly, which is an ensemble approach where algorithms are used together. So, we multiply our ability to get into greater precision or make up for weaknesses that certain algorithms have by using other algorithms. All of this is critical because it helps us define and develop the strategy of bringing a drug to market and develop a potential combination approach of any diagnostic and this allows us to have a higher chance of approval and a faster route to getting to the patients.

We think this will be a long-term strategic advantage as we deepen our capabilities in 2 very important areas, both antibody drug conjugates and combination therapies. We believe that this will help an increasing number of patients and ultimately add significantly more value for our investors. Now turning to our biomarker signatures. We think this is an area of real importance.

As I mentioned, there was a recent study about a year ago that was conducted but published a year ago by Dr. Jason Parker at University of Toronto. He had reviewed -- he and his team reviewed over 10,000 clinical trials across about 745 drug programs. And this study show that biomarker-based trials have success rates that were 4x to 12x higher than those clinical trials that did not use biomarkers. Study came also concluded that there is clear evidence of biomarkers increase clinical trial success rates in multiple indications, many of those, which we're going after. And this is a hallmark of our development process.

This further encourages us at utilizing our RADR platform with our drug candidates and potentially with other drug candidates, again have a very meaningful way of reducing costs and accelerating our ability to get our drug candidates to patients. As you know, we've begun to witness firsthand growing industry interest in AI and machine learning solutions, especially ones that help innovate or derisk the development of precision therapies and combination therapies. We believe that there is a growing appetite for these kinds of solutions. Many of these solutions are data powered or powered by AI approaches or machine learning techniques. And we think these techniques will increasingly be adopted by bigger biopharma companies and ultimately yield greater investor value for us.

Now before passing the call over to David to discuss our financial results, I want to briefly talk about some of the highlights in 2021 and into this year of our drug development candidates. During 2021, we have multiple areas where we advanced our drug programs. We reported positive preclinical data for LP-184 in pancreatic cancer, in glioblastoma and also in a rare pediatric cancer ATRT.

We also advanced LP-300 for a Phase 2 clinical trial, the Harmonic trial for never smokers in non-small cell lung cancer. This will be a 90-patient randomized Phase 2 clinical trial with 2 arms, where LP-300 will be co-administered along with a chemo doubling to patients that have failed or stopped responding to TKI therapy and we will be looking at the co endpoints of overall survival and progression-free survival. The Harmonic trial is actually looking at sites today. Again, one arm will be 60 patients to 2:1 ratio, one arm would be 30, the control arm.

We've began an assessment also of the next phase of our other Phase 2 program, LP-100 in metastatic, castration-resistant prostate cancer. We've actually also found that there are several other cancers that would be -- that could be very sensitive to this drug and we'll talk about that little bit later and also share more of the data from that trial. The trial has dosed 9 patients in a target of 27% and the median overall survival for that initial cohort has been 12.5 months, which is higher than other fourth and fifth line trials that have been done in metastatic castration-resistant prostate cancer.

We also presented positive data late last year at ASH for our new drug, LP-284 in hematologic cancers, including several rare blood cancers such as mantle cell lymphoma and double-hit lymphomas. We plan on sharing additional data on this drug program later this year and also announced research collaborations in that program.

As a result of the encouraging results in 184 in regards to glioblastoma and pancreatic cancer, we were granted orphan drug designation in both and also in ATRT, where we additionally got rare pediatric designation. This not only allows us to have cash credits for the trials being done here in the U.S., waiver of marketing registration, application fees, reduced annual product fees. But these are all massively important because they reduce our burden of development, they give us increased commercial protection and they potentially gives us a voucher that upon approval, we can actually sell for $100 million to $110 million.

Also, these orphan drug designations give us validation of our AI-driven approach. Both these were -- all 3 of these orphan drug designations were achieved quite rapidly based on the data and insight driven from our machine-learning algorithms and our AI approach. We also submitted an abstract with Fox Chase Cancer Center Research of Dr. Igor Astrosoft, he is an established NCI-funded physician scientist who is also a co-leader of the Greenberg Pancreatic Cancer Institute at Fox Chase and it was also presented for a virtual conference at AACR.

The data showed that LP-100 showed -- was very effective and potentially is a synthetically lethal agent in pancreatic cancers that have DNA damage repair deficiency. This is an area that we're particularly excited about and we believe gives us a road map for prioritizing additional cancers where we can develop first-in-class solutions and show significant improvement over the existing standard of care outcomes.

We also showed that in GBM, we also had very good responses, work was done in conjunction with Kennedy Krieger and Johns Hopkins University. This is a multi-billion dollar indication. And in both pancreatic and for GBM, we're now in IND-enabling studies, which are already quite long. And these IND studies will allow us to file the IND for this year and then get into Phase 1 human trials, hopefully, later this year.

We also believe that another development that was important for us were our technology collaboration. We announced 2 very important technology collaborations. Last year, one with Deep Lens in order to accelerate our ability to find patients that suited for our treatment in our Harmonic trial. That's the trial for never-smokers, and we announced a collaboration with Code Ocean that allows us to scale up more securely and containerize our AI platform. So both Code Ocean and Deep Lens we believe are best-in-class technology partners and they both offer us ways to scale up our ability and more importantly they align with our philosophy of using data and technology to accelerate the development of medicine.

More importantly, it allows us to do this in a cost-efficient environment. As David would walked you through our financials, we've been financially very disciplined, not only internally, but also in the types of studies that we launch and types of collaborations we generate. And these collaborations will have quite a bit of data coming out this shift. So our current cash resources will give us a great runway for our development programs well into 2025, not only in part because of the good financial discipline that we show, but also in the way that we're actually developing our programs and designing our trials.

To shed more light on that. David, our CFO, will provide an overview of the fourth quarter and the full year financial results. David?

Thank you, Panna, and good afternoon, everyone. I'll now share some financial highlights from our fourth quarter and the full year ended December 31, 2021. I'll start with a review of the fourth quarter. Our R&D expenses were $2.2 million for the fourth quarter of 2021, up from $1.4 million in the fourth quarter of 2020. As was the case throughout the year, the increase in R&D expense was primarily attributable to increases in manufacturing-related expense for product candidates and to research studies and R&D payroll expenses.

General and administrative expenses were $1.4 million for the fourth quarter of 2021, down from $1.6 million in the prior year period. We recorded a net loss of $3.5 million for the fourth quarter of 2021 or $0.31 per share compared to a net loss of $2.9 million or $0.47 per share for the fourth quarter of 2020. For the full year 2021, our R&D expenses were $7.6 million, up from $2.2 million for 2020. As mentioned a moment ago, this increase was primarily attributable to increases in manufacturing-related expenses for product candidates, research studies and R&D payroll expense.

Specifically, for the full year 2021, our product manufacturing-related expenses increased by approximately $2.7 million, while research studies increased approximately $0.8 million and R&D payroll expenses were up approximately $0.7 million. Additionally, for the full year 2021, we recorded a nonrecurring expense of $1 million related to the upfront payment to Allarity Therapeutics in July with the global rights to LP-100, our Phase 2 asset for the treatment of metastatic castration-resistant prostate cancer.

Our general and administrative expenses for 2021 were $5 million, up from $3.7 million for 2020. The annual increase was primarily attributable to increases in business and corporate development expense of approximately $0.4 million, increases in corporate insurance expense of approximately $0.6 million and increases in legal and patent-related expenses of approximately $0.4 million.

Our R&D expenses continued to exceed our G&A expense by a strong margin, reflecting our focus on advancing and expanding our product pipeline. Net loss for the full year 2021 was $12.4 million or $1.13 per share compared to $5.9 million or $1.37 per share for 2020. As of December 31, 2021, we had approximately 11.1 million shares of common stock outstanding and outstanding warrants to purchase approximately 274,000 shares and outstanding options to purchase approximately 891,000 shares.

These warrants and options, combined with our outstanding shares of common stock, gave us a total fully diluted shares outstanding of approximately 12.3 million shares as of December 31, 2021. Our cash position, which includes cash equivalents and marketable securities at December 31, 2021, was $70.7 million. This balance is expected to carry us into 2025. Importantly, we believe our solid financial position will fuel continued growth and evolution of our RADR AI platform, accelerate the development of our portfolio of targeted oncology drug candidates and allow us to introduce additional targeted products and collaboration opportunities in a capital-efficient manner.

Lantern Pharma implemented a share repurchase program in 2021, whereby the company is authorized to repurchase up to $7 million of common stock. Through March 1, 2022, the company has repurchased approximately 430,000 shares for a total of approximately $3.1 million, including purchase fees. This includes approximately 122,000 shares purchased in 2021 for a total of approximately $940,000. We believe these purchases will be accretive to shareholder value.

We are migrating to a hybrid work environment and I'm proud to say that our team continues to be very productive under this operating model. The hybrid model also removes geographic restrictions to our hiring initiatives, which gives us the ability to recruit extremely high-caliber team members that otherwise might not be available. We currently have 16 employees who are primarily focused on leading and advancing our research and drug development efforts. We see this number expanding slightly in coming quarters as we add additional experience and talented individuals to help advance our mission.

I'll now turn the call over to Kishor for an update on some of our development programs. Kishor?

Thank you, David. Good afternoon. I'm going to start by just recapping some information we discussed in our last call and as some of you may recollect, in the last call, we updated you about some exciting advances of our molecule LP-184. Just to recap, FDA granted LP-184 with orphan drug designations for 3 indications, including glioblastoma, pancreatic cancers and ATRT. In addition, we received rare pediatric drug designation for ATRT.

LP-184 is moving steadily towards initial clinical studies. The final data from toxicology and pharmacology studies are due soon. We have begun discussions with multiple sites for the initiation of Phase 1 studies and these discussions are ongoing to refine the details of the correlated studies, so that they will best inform the Phase 2 clinical studies in cancers, which are either homologous recombination deficient or nucleotide excision repair deficient.

In the preclinical space, looking forward, we are also completing studies to identify synergies with standard of care drugs that might guide future applications of LP-184. We have seen excellent results that provide good synergy of LP-184 with drugs like gemcitabine, for example. Among the clinical indications, one important need that LP-184 could potentially meet is therapy for cancers metastasized to the brain. As many of you are aware, cancers of lung, colon, kidney and skin often spread to the brain.

The activity of LP-184 in tumor cells of these organs, coupled with the ability of LP-184 to cross the blood brain barrier and endorse this molecule with the necessary properties for such brain metastatic cancers. This week, we are presenting a poster at AACR, providing evidence of LP-184 efficacy in 3D models of brain, metastatic lung and breast cancers.

Today, I wanted to spend some more time to share with you information on our other molecules, LP-284. Both LP-184 and LP-284 are acylfulvenes. And acylfulvenes,, like many other small molecules are chiral. Unlike many other small molecules that target DNA, the different chirality of the derived tumor targeting agent, LP-184, generically also known as hydroxyurea methyl acylfulvene uniquely demonstrates differential activities in tumor cell lines. So one isomer has very specific tumor killing properties and other isomer has a different set of tumor killing properties.

These data, therefore, enable the independent development of the positive isomer of hydroxy methyl acylfulvene, which we designate as LP-284. And these are particularly for the indications in hematological cancer space. Our RADR data analysis highlighted a key difference in LP-184, a negative isomer and LP-284, the positive isomer. In that, 184 is obligately dependent upon the activity of the enzyme PTGR1. LP-284 on the other hand is not. Since PTGR1 is expressed at levels below the threshold required to activate 184. LP-184 is not potently cytotoxic to blood cancer cells, 284 on the other hand is.

Further examination of LP-284 in a wide range of blood tumors demonstrated strong support for efficacy in diffuse large B-cell lymphomas, chronic myoloid leukemia, Burkitt's lymphoma and mantle cell lymphoma. The latter stands out as an exceptional indication for several reasons. First, the pre-clinical data was was very excellent because all the 6 lines tested showed potent loss of viability when exposed in nanomolar levels of 284 in vivo.

Additional laboratories also suggest that like 184, 284 efficacy is enhanced by the presence of deficiencies in DNA repair pathways. And this brings the second point that I wanted to talk about why mantle cell lymphomas might be a great indication. Mantle cell lymphomas frequently carry a mutation of the ATM gene, a gene critical to DNA damage repair. Other blood tumors also, either intrinsically carry mutations in DNA repair genes or depict a phenotype of such deficiency.

This phenotype often described as (inaudible) could come from the down regulation of the function of genes like BRCA1 because of the lesions carried by hematological cancers, such as the BCR-ABL translocation. The ability of LP-284 to damage DNA and the need of transcription coupled repair for the repair of this damage, also indicates that 284 is able to block transcription. This property of 284 is likely to render blood cancers, which carried oncogenic translocations.

Since many of these translocations are driven by a deregulated transcription of the oncogenes, the starting of these oncogenes, which are necessary for the survival of these blood cancers can halt the ability of the oncogenes via 284 blocking of the transcription to sustain the tumors. At this time, we are focused on developing 284 for mantle cell lymphomas. Our next step in ongoing studies are to extend the efficacy studies to in vivo models, complete the toxicology and pharmacology studies of the molecule and begin to design a Phase I trial for treating mantle cell lymphomas that have relapsed following targeted therapy.

I'll hand it over to Panna.

Sure. Thank you. Before I open it up to questions, I'd like to provide a brief recap and also discuss some of the upcoming milestones. As you know, we're very confident in the launch of multiple human clinical trials this year for our drug candidates LP-300, LP-100, LP-184. We're also looking at the ongoing growth of our RADR platform and we remain committed to moving our ADC program into IND-enabling studies. We also believe that with our network of strategic collaborators that -- and we'll also be adding additional collaborators that will be able to generate exciting new data that will help us launch new programs that we can license -- that we can develop and then license out.

We believe RADR is essential to this in terms of building our existing drug portfolio, but also generating new opportunities. We remain committed to achieving our goal of building the world's largest AI platform for precision oncology drug development and we believe we're significantly on our way to already. Our goal this year is to surpass 25 billion data points, move our late-stage candidates into trials and continue to add valuable data in targeted areas such as neuro-oncology, rare cancers and pediatric cancers where there is a significant need for improved therapies.

We believe that our AI platform and our collaborative business model will be pivotal in uncovering new opportunities for cancer patients, but also for investors. We believe that we're well positioned to take advantage of the wide scale availability of data and the ability now to do large-scale genomic and machine learning analysis in the cloud. We've built a great team internally that has multiple interdisciplinary capabilities and we have collaborators that are helping drive the development toward patients faster and faster.

So with that, I'd like to now open the call up to some questions.

Okay. Great. We have a couple of questions coming in here. One is from [Ted Yu]. Have the COVID-related issues in sourcing equipment needed for clinical progress been addressed?

Thank you, Ted, for that question. As you pointed out, we've had delays in manufacturing, mostly due to COVID with our LP-300 molecule. Those have been addressed. In fact, just recently, we finalized the batch of drug products. So now -- it's now being tested for final stability. And so, yes, we cross that had definitely delayed our time line of manufacturing by 3 to 4 months. We also had delays to omicron, due to staffing capabilities into our manufacturing partners and those are now also passed.

So we believe that clinical trial sites are beginning to open back up, probably not at the same level of openness as pre-pandemic, but we are beginning to see sites open back up and take on new cancer trials. So yes, COVID did impact us, impact us by at least 3 to 4 months in manufacturing and definitely slowed down clinical trial site selection any moment.

The next question, can you please detail the biomarker screening you were planning for LP-184. Do you plan combination therapy for 184? And will the combination be guided by biomarkers as well?

We'll have to unpack that question. It's a great question. We do plan on having a biomarker strategy and we've already talked a little bit about it. PTGR1 is essential and basically mechanizing 184 into an active cancer killing agent. So, we are looking at cancers that overexpress PTGR1 that's an essential biomarker. Additionally, as Kishor pointed out that there are certain DNA damage repair deficiencies that make LP-184 synthetically lethal to many tumors.

And so when we have that presence, such as efficiencies in BRCA, ERCC potentially other DNA repair genes, typically either in 2 paths. There's the nucleotide excision repair pathway and then the homologous repair pathway. And we find deficiencies in either, what we've seen is that the tumors tend to be extraordinarily more sensitive to the drug by a factor of anywhere from 2x to 8x we've seen, depending on the tumor type.

So, yes, we will definitely use biomarkers to help select not only the tumor types that we go after, but also potentially the patients that are most likely to respond. The second part of that question, I believe, was in combination. We have some slides in the combination, but Kishor, do you want to talk about this, some of the combinations that we've already uncovered.

Yes. So, our strategy to look at combinations because, again, with our RADR platform, using DepMap and gene correlation studies to identify which pathways together would synergize. Our next step then is to ask the question, are there drugs in that pathway, ones that are being used for indications where we are pointing LP-184 in. Once we arrive at that answer, then we conduct wet lab studies to actually get evidence, real-life evidence of synergistic activity. So, based upon these kind of study designs, we have identified several drugs that have shown very good synergy with LP-184. And so we believe that we will have the potential to use LP-184 in a thoughtful and irrational way in drug combinations.

To give you some more clarity, we have seen significant synergy with gemcitabine in pancreatic cancer. We've had an exceptional Bliss synergy scores, that's one of those scores that's use to look at synergy drug. So Bliss score about 10 typically shows that there's a very promising synergy. But we use different synergy algorithms that's one that's used. We also saw synergy with spironolactone, which is very promising. spironolactone is already a drug that's used widely today. We've seen that spironolactone in certain tumors generates a mutation of deficiency in ERCC3?

Yes, that's a very exciting story. And it's an amazing story because what spironolactone combination could allow us to do would be to basically convert almost any tumor into a nerd tumor, making it exclusively sensitive to LP-184. We are focusing on this area quite aggressively and we do find that the results we get back make us more and more confident that this combination is going to be a winning combination for LP-184.

Again, we also -- many of our patents that we filed last year were for combination approaches that we think are very promising. So, we'll continue to look at those and we think spironolactone and potentially even other prototypes will be a very useful combination with 184. Good question.

The next question comes from Michael King. Any update on whether bladder cancer remains on the radar for 184. Yes, it's on our heads, definitely on the radar for 184 in multiple ways and potentially also even 100. So bladder cancer is a target. There's several subtypes of bladder cancer, as you know. And maybe we can talk a little bit about an abstract, the next phase of work that we're doing looking at bladder cancer.

Yes. So, we have designed studies to position LP-100 and also do strategic studies with LP-184 in different types of bladder cancer. These would include bladder cancers that are localized, non-muscle invasive bladder cancers, that have become refractory to things like BCG, for instance. We are also looking at metastatic bladder cancers. About 10% to 12% of metastatic bladder cancers have deficiencies in DNA repair genes, particularly in those genes that are essential for survival following damage with LP-184.

Obviously, bladder cancers would be great indications for LP-184 and some of our in-vitro data already shows us that if we create in the laboratory a knockdown of those genes, the efficacy of LP-184 can increase 10% to 34%. So, yes, we are focused on bladder cancers and we are in discussions with several leading authorities in bladder cancer to develop further studies with collaborations.

Great question. So you'll definitely see news in bladder cancer this year from us.

Next question comes from [Michael Samuels]. How do you see yourself compared to other small cap bios in terms of pipeline and talent among other things?

Well, that's a great, but loaded question. I mean I think the biotech obviously has been a challenging sector underperforming and less included. But I think unlike many biotechs, I believe we have the ability to generate new potential wins for investors on a continued basis. That's why we believe in our platform. I think we have a very good cash position, but also a good financial discipline in terms of where we're investing and how we're investing in our programs.

So, for our relative burn rate, which has been last quarter was $3.5 million, we do expect that it will increase slightly this year, closer to $4, $4.5 million per quarter, especially as we finalize manufacturing, launch sites. So, the burn increase. But we have cash that allow us to get into 2025 and we have programs that could be worth several billion dollars. And we have a platform that continues to turn out new ideas and an AI platform that actually can do collaborations on its own.

So I think relative to other small cap biotechs, I think once biotech is -- I think it will be in favor again that the need for innovative new medicines and understanding the disease is not going to go away. So as things shift, I think we'll be more cream rises to the top. And I think we're part of that kind of company because we have a pipeline that can be continually growing and we have a platform that also is continually growing and we have drug programs that are derisked and very targeted. So I think we'll be one of the long-term winners in the biotech space.

Next question also comes from Michael King. A question about RADR. What can your view with 25 billion data points that couldn't be done with 18 billion? When do you hit a diminishing rate of return? Can you discuss how you're leveraging Deep Lens and Code Ocean to increase efficiencies and data analysis?

Yes. Those are great questions, Michael. So we're 18 now. I think we'll get to 25 this year. But in that 18 billion, we don't have, I believe, enough data on certain rare cancers or pediatric cancer. So, we want to suck in all that data, so that we can better understand what pediatric cancers can be responsive to the kinds of compounds that we're interested in developing. That allows us to have another shot at or 2 or 3 on goal.

Also, one of the things, as we mentioned earlier, is that we are very interested in exploring combinations with approved therapies. Many of those combinations can be I/O therapies. So again, on our road map to getting to beyond 25 billion as we go for 50 and 100 billion, we want to suck in a lot of immune data, Immunomic data, antigen data, and there's a lot of algorithms that predict immune response, combination and immune response plus other cytotoxic agents. And so we'll be able to model that.

We're in a very early phase of that. I think we'll be better at it by the end of the year. And so the platform's ability to do things that are relevant in cancer will only grow. And so I don't think we'll hit the law of diminishing returns because there's so much new data that's being generated in new classes of drugs, new medicines, new tumor subtypes. And I think we will have a lot of return on the road map to 100 billion. After that, I think then we'll take a deep breath after 100 billion and see what's next.

But also don't forget that new generations of machines are coming out, the sequencing machines and aren't transcriptome machines, ways to look at the genome that we didn't do before, the way to collect biomarker data and that's now spatially organized, it gives you different types of ideas about how the cancer is evolving or not. And so we haven't even scratched the surface of that. So I think as we get more advanced ideas about drugs and drug classes, we're going to start throwing away or adding to that data.

So, I think -- I don't think there's a law of diminishing returns right now, in general, if you know what kind of data to suck in for what problems. Now if I wanted to describe and get 1 billion more data points for some chemotherapy that was launched 30 years ago, yes, that may be -- that may not give us any more value than we already have. We already have enough data on most of the chemotherapy regimens.

So, I don't need more cisplatin data. So, we don't go after that. I definitely don't need more cisplatin data in breast, ovarian and lung. So that's the prior times. But I do need it in certain rare and pediatric cancers that haven't been in the study. So that all accept. So all -- not all data is equal. The value that data and data types is all different. So you have to think about those data sets as we curate it and we make our list and think about what the campaigns are. So hopefully, that answers your question.

In terms of the collaboration, Deep Lens, the important for Deep Lens is our ability to find patients faster. And that's going to be evident in the 300 trial that we're launching now. So, we have sites and potential patients. And so if we can reach patients and we know how they're going to potentially come off of TKI therapy and they are chemo naive and we know a little bit about their history, we can be more aggressive about trying to bring them into our track. It's being proactive. I think it's essential part of clinical trial design going forward.

In terms of Code Ocean, great company that allows us to scale up RADR in a way to allow us to do collaborations with external partners. In fact, we're now using that with some of our partners that we announced in the collaboration with Dana-Farber and the Danish Cancer Research Society, so they can plug into our containers at Code Ocean, use our algorithms, share the data, share our data and it's a scalable and it's a highly secure way. And there's no passing around of files and DevOps environments.

And so it just makes the essential ingredients of doing collaboration in an AI age one easier and allows us to have a lower burden of managing the infrastructure and managing the environment because we can't hire one tech stack manager for every 3 or 4 programs we hire. It's just not a scale of the solution. So, the great thing about technology today is there's some really great cloud-based container solutions that are scalable and secure and Code Ocean is one of those. So both companies allow us to do things faster, cheaper and more scalable. And that's part of, I think, adopting these tech forward solutions.

The next question is about 284. Could you expand on how you plan to leverage the ERCC3 degradation mechanism for LP-284 in ways that may be independent of spironolactone? Or do you envision that spironolactone treatment would your requirement for LP-284?

A good question. Who asked that question?

(inaudible).

It's a very good question.

Yes. So spironolactone is not required for efficacy of 284.

So for, there's a chart that we have, we see nanomole potency across the wide ranges.

And in that chart, there's a result of spironolactone. To answer the question about ERCC3 and spironolactone, the background behind this is that -- when we looked at 284 in different tumor cell types and cell lines, which were debilitated for specific genes such as CSD, ERCC3, so on and so forth, we found not surprisingly since 284 is a cousin of 184. We found that 284 efficiency increases dramatically if a tumor cell does not have the ability to repair the damage caused by 284.

In parallel, it turns out that spironolactone has the ability to very specifically degrade ERCC3. Now, ERCC3 is an essential component of the repair machinery required if the cell needs to repair damage by 284. By removing away that ability from the tumor cell, we give it no other choice except to that. And therefore, the combination of 184 and spironolactone allows us several things. It allows us to focus on those tumor cells that are a little bit more resistant to 284 and require -- might require higher levels of 284, but using spironolactone, we could reduce the amount of 284 required to kill the tumor cell.

So you enhance the function in indications where it might already have strong ability, but you also open additional indications beyond what you had otherwise -- and of course, if we can keep the -- at some point, you want to make sure you want to give a little of a drug to get the maximum effect. And so when we look at dose finding and dose range, we might say, hey, we're getting to a point where we have some concern that we can back off of it if the person will be...

So those studies are something that we...

Also one other thing it opens up also that there are people that are taking spironolactone now.

So, it's different. So, I mean, the function of ERCC3 is important when DNA is damaged. Of course, all of us consistently have some DNA damage or the other. But the synthetic lethality of LP-184 and spironolactone combination comes and there's so much tremendous damage because of the insult of the DNA by 184. In absence of that, in a few cells of -- a few molecules of ERCC3 that consequence run is advance. Spironolactone has been used for hypertension and so many other...

Water retention and fluid et cetera. Very good question. Any other questions today, Nicole.

We have time for one more. This one comes from Kyle Bauser. As you prepare for the Phase 2 trial for LP-300 and evaluate sites, how are you finding and connecting with sites? How many have signed up? And how many more would you like to have before commencing enrollment?

What was that for how many?

How many are signed?

How many are signed? I don't think we're in the process of talking to the sites, getting NDAs in place, et cetera. So we would like to get for the first launch about 5 sites now. We're pretty close to that now. How we're finding it? I think it is in part through Deep Lens, in part through our CRO, but we have, as Panna described earlier, we've seen improvement, but there have definitely been impacts from COVID in terms of shortages -- staffing shortages at clinical trial sites and the delays getting on the phone calls and delays in getting the physician teams briefed.

So there have been delays. But I think we're just beginning to -- I would say in the last few weeks, we've begun seeing some changes, certainly isn't as bad as it was a month or 2 ago. But because of the unique focus on never-smokers and the fact that the control arm get standard of care drugs anyway, it's a very attractive clinical drug trial design perspective. And because of our ratio of 2:1 that's also a good evidence with 60 patients who we are going to get the LP-300 in combination with standard of care agents. So we have a higher chance that patient getting potentially new grade therapies.

So the design is, I think, very appealing and the fact that the history of the drug is very safe and historical trials is also very appealing. I think it's now that we're hopeful at the end of the pandemic, we can get people to start clearing out the hospitals and centers and making new room from one of the oncology trials. But there definitely have been delays and I'd like to get 5 of them going up front to then start initiating patient enrollment gets in.

Okay. We can maybe squeeze in one more question here also from Kyle Bauser. I know you definitely do not want to sacrifice the quality of the curated data points, yet you've significantly accelerated pace at which you're adding to RADR. Can you talk about how you've been able to streamline this process without sacrificing quality?

Well, actually, I think -- in many ways, we've actually increased quality. We're doing things much more automated or scripting is getting better. We're going after bigger chunks of data, a little bit more disciplined in which chunks we're going after. But a lot of that really just comes down to automating the scripts and automating the analysis and putting it into the data lake.

And so as we go after more of them, we have more experience, and so we can deal with all the different data sets with bigger and bigger bites each time. And I think, as I mentioned, we'd like to go to 25 billion, but we do have a road map for 100 billion. So that is going to be some -- that will have -- push our limits for maybe our current generation in automation. We have to look at some new things too. So, it will continue.

Okay. And with that, I believe that is all the time we have for questions today. I will now turn it back over to Panna for some closing remarks.

Thanks, Nicole. So we believe 2022 will be a transformational year for us. We've laid the foundation last year in 2021 in terms of advancing our drugs for trial and getting orphan designation, advancing the platform, maintaining financial discipline, announcing a share purchase reprogram to show that we have a lot of confidence in our programs and in our stock. We ended the year with over $70.7 million in cash and cash equivalents and marketable securities. We've also increased our intellectual property with over 12 new patent applications and actually have some great ideas for combination approaches. So I think that this year, we'll continue growing our platform, we'll advance our portfolio and also our team is very committed to bringing these drugs to patients. not only doing it faster and cheaper, but with better insight. And so our strong cash position, along with our history of accomplishment, I think, bodes well for our pipeline and also potentially for investors. So thank you for joining our call today and we hope you continue to follow and track our accomplishments and what our team is doing. Thank you.

Thank you.