Lantern Pharma Inc.

Good afternoon and welcome to Lantern Pharma's fourth quarter 2020 conference call. As a reminder, this call is being recorded and all participants are in listen-only mode. We will open the call for questions and answers after the presentation. I would now like to introduce your host for today's conference, Malrick Teshefsky with Investor Relations at Lantern Pharma. Malrick, please go ahead.

Thank you very much, Christy, and thank you for joining us for Lantern Pharma's fourth quarter 2020 conference call. On the call today are Prana Sharma, Lantern's President and CEO, and David Margrave, Lantern's CFO. A press release was issued this afternoon with our fourth quarter financial results that we will be discussing here today. Following the safe harbor statement, Pana will provide an overview of after which David will share our quarterly financial results. Pana will then offer concluding comments after which we will open this call to questions. Please also note that we have provided our link on our IR website to the slide that we will be referencing in today's call. I would also like to remind everyone that remarks about future expectations, plans, and prospects constitute forward-looking statements for purposes of safe harbor provisions under the Private Securities Litigation Reform Act of 1995. Lantern Pharma cautioned that these forward-looking statements are subject to risks and uncertainties that may cause actual results to differ materially from those anticipated. There are a number of important factors that could cause our actual results to differ materially from those indicated by the forward-looking statements, such as the impact of COVID-19 pandemic, the results of our 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 and be found in the risk factors section in our annual report on Form 10-K for the year ended December 31st, 2020, which was filed with the FCC on March 10th, 2021. Any forward-looking statements made on this conference call speak only as of today's date, Wednesday, March 10th, 2021. And Lent and PhRMA does not intend to update any of these forward-looking statements to reflect events or circumstances that occur after today. Please refer to today's press release for replay information. And now, I turn the call over to Parna Sharma, President and CEO of Lent and PhRMA. Parna Sharma, President and CEO of Lent and PhRMA. Parna Sharma, President and CEO of Lent and PhRMA.

Mark, thank you. And good afternoon to everyone on the call today. Thank you for joining us for our fourth quarter and year-end 2020 conference call. For those of you that are new to the Lantern Pharma story, we are a unique company, an oncology biotech that leverages the power of artificial intelligence and machine learning to both rescue and develop oncology therapies. We do this through our internally developed proprietary AI platform called Radar. We are one of the few AI-based biotechs that has multiple clinical stage programs in development as well as a rapidly growing proprietary platform. for accelerating our understanding, modeling, and prediction of patient and tumor response to cancer therapies. In this regard, we are a very unique company at the forefront of the data and machine-enabled transformation happening in drug development and drug discovery today. Our team has been working very hard this past quarter, advancing our collaborations, developing meaningful lab data, advancing our manufacturing, onboarding new team members, both employees and consultants, while also hitting major new milestones for our platform and for developing insights for new indications that'll power future therapies. Shortly after we began trading last June of 2020, we announced that our proprietary AI platform for precision oncology drug development radar surpassed 450 million data points. That was roughly six months ahead of our plans. Now we plan to cross the three billion mark during 2021. We closed 2020 with a little over 1.1 billion data points. These data are highly curated data sets specifically for oncology drug development and drug response prediction. Our team has made tremendous progress in this front and has recently announced a publication in BMC Bioinformatics which showcases some of the processes that our platform enables for drug development, in particular preclinical work for selection of indications, and the development of a biomarker-enabled signature that can be used for both patient selection and prediction of tumor response. Our process for selecting, cleaning, curating, and tagging the data has gotten significantly more efficient and powerful, and this will allow our company and particularly our partners to develop cancer therapies and better understand where and how certain compounds work with even greater precision, reduced risk, and a much more rapid pace. We will be seeking and developing select partnerships with biopharma companies where our radar AI platform can help in the development of their programs and generate rewards and upside for Lantern and our investors. Beyond merely the sheer amount of data, the quality and relevance of our data and functionality continues to grow, as evidenced by the increase in the number of indications and programs we have developed since our IPO. In June, it was three, and now it's seven programs. And this is all in the span of the last nine months. Our radar AI platform stands at the core of our business model alongside a targeted and accelerated drug development path. The growth in the quantity and quality of our data and also our functionality is an important driver of the value of our franchise. Radar's growing genomic drug sensitivity and patient outcome data sets combined with our AI and machine learning enable us to streamline the drug development process while also identifying patients and patient populations that will benefit from our oncology therapies. We are confident the power of radar will enable us to add at least one additional biomarker or genetically defined program or indication to our pipeline every 12 to 18 months. During previous calls, I've spoken extensively about how we are now beginning to experience and live in the beginning of a golden age of artificial intelligence, an era where the availability of relevant data, computing power, cloud resources, on-demand sequencing, talent, and the acceleration of AI and large-scale data analytics and algorithms, along with shifting economic and investor demands, have aligned to make large, data-driven, highly responsive, machine-driven approaches to solving complex, sometimes unknown problems a reality. This is especially true in drug development. We are harnessing the trends and capabilities of this golden age to accelerate our pipeline and, most importantly, to benefit cancer patients and to bring down the costs associated with the risky and lengthy process of cancer drug development. For those of you that are still new to the story or learning about Lantern, our pipeline of small molecule oncology assets and an antibody drug conjugate asset includes new compounds that we have identified through our biomarker discovery efforts, as well as potential therapies with extensive prior clinical experience that we acquired after previous owners abandoned development efforts following phase three setbacks. In all regards, we own the therapeutic rights or developmental rights to all the assets that we're developing. Our radar AI platform underpins each development or rescue efforts, and we are confident that this will help us achieve a scale and transformation to the oncology drug development process. 2020 was a pivotal year for Lantern Pharma, marked by a series of financial, operational, and drug development achievements, many of which are highlighted in the press release that was issued earlier this afternoon. But these achievements validate something that's very unique about our business. Not only are we capital efficient, and leveraging the power of AI, but we also are combining that with the knowledge and experience of our scientific team to rapidly take these insights and march forward in our drug development programs. In the short time since our June 2020 IPO, we've more than doubled the number of programs that we have in active development. This increases the number of opportunities for accretive licensing deals, partnering opportunities, and generating upside for our investors. We also initiated a highly differentiated antibody drug conjugate program. This leverages some very unique linker technologies developed by Califia, and we also grew the number of data points that fuel our AI platform by over 5x this past year. We initiated manufacturing, research, and development collaborations with leading cancer research institutions. These include Johns Hopkins and Glioblastoma. Georgetown University in prostate cancer, Fox Chase Cancer Center in pancreatic cancer, and also other solid tumors where nucleotide exclusion repair mechanisms can be exploited. These are all very targeted programs, and many of these programs and collaborations are now entering their second stage, including the one with Georgetown. The first stage of joint research activities began in the fourth quarter of 2019. and generated compelling evidence of efficacy of LP184 in solid tumors, but in particular solid tumors that overexpressed PTGR1. This anti-tumor activity was linked in a dose-dependent fashion, and we validated it in very specific subtypes of prostate cancer where PTGR1 is naturally overexpressed as a form of it becoming metastatic. This research has helped us guide specific development of that signature and more importantly, correlates to increased response among certain subtypes of cancer, including cancers that are DNA damage repair gene deficient. The next phase of collaboration will focus on a larger set of PDX models. It'll pinpoint the specific mechanism, seek confirmatory validation on the role of PTGR1 and potentially other genetic mutations, and the research will complete the acquisition of detailed genomic information in prostate cancers and potentially other related urogenital cancers. The second phase goal is to create a biologically relevant, robust gene signature that we can take into clinical trials and will prepare us to select patients with the objective of allowing future prostate cancer patients to experience the benefit of a more personalized cancer treatment approach. Ultimately, we believe that our AI-driven approach could save millions of dollars in drug development costs, perhaps tens of millions, while significantly accelerating the path to commercialization, but more importantly, personalized treatment towards select populations that are most likely to benefit from the therapy. The work that we're doing at Georgetown is being led by Dr. Partha Banerjee, a world-renowned expert in molecular oncology and prostate cancer. We also have collaboration research agreements with Fox Chase Cancer Center for the development of LP184 in pancreatic cancer, And this collaboration advances the targeted use of LP184 in genetically defined subtypes of pancreatic cancer. Again, those with the right gene signature and, of course, to be able to use that gene signature biologically relevant and occurring naturally in pancreatic cancers to guide the development of clinical trial. If successful, we believe that we can develop a more personalized therapy option that has the potential to improve survival and go after one of the cancers that has very poor overall survival. The program at Fox Chase Cancer Center is being led by Dr. Igor Astyashirov in the molecular therapeutics program at Fox Chase. Igor is an internationally recognized researcher in GI cancer specializing in investigating signaling pathways that inform the choice of biomarkers and innovative therapy combinations in clinical trials. In the fourth quarter, we announced another collaboration and research agreement with Johns Hopkins at the Sidney Kimmel Comprehensive Cancer Center. This program is focused on further development of one LP184 in glioblastoma. Johns Hopkins is a leading research center for brain cancers and one of the largest brain tumor treatment and research centers in the world, and they focus on treating an extremely large number of patients affected by all types of brain tumors. In fact, after finding that LP184 cross the blood-brain barrier exquisitely. We've been at the forefront of enriching our RADAR database with several dozen million data points in brain cancers. And again, the collaboration today with Hopkins is focused on defining the subtypes of GBM, but also clarifying the most promising clinical application for the drug candidate, LP184, especially as monotherapy. The goal of this collaboration is to develop a clinically ready program that has characterized the drug candidate with the most biologically relevant and robust biomarker signature and using that signature to identify the patients that have the highest potential for response. This way we can shorten future trials and bring the drug to the benefit of this needed population. This kind of research we believe is the forefront of translational cancer medicine and very importantly allows us to develop physiologically relevant models using patient-derived material and then understand the biology of what is actually happening inside the cancer tumor and use that to feed our radar engine. The radar engine allows us to generate more precise biomarker signatures that provide data-driven insight into additional mechanisms. So we believe this is a very essential, very important feedback loop as data from physiologically relevant experiments feeds back into our AI engine. Our AI engine generates signatures, those signatures that are used to do additional work. And this process is continuing now across several cancers and several cancer areas at Lantern, and this feeds millions of data points of additional insight, proprietary data-driven insight, into our radar platform. Our GBM program is being led by Dr. John Letera, an internationally recognized researcher in neurology, oncology, and neuroscience. During our last call, we talked about how LPA-184 has demonstrated high nanomolar potency and the ability to cross the blood-brain barrier, something that very few small molecules can do. But more importantly, as it crosses the blood-brain barrier, it keeps neuronal cells intact and viable while really focusing the damage on the cancer or the glioma cells. This opens up potentially a high-value opportunity to help patients in many other brain cancers. and the ability to cross the blood-brain barrier is of critical importance in treatment outcomes for CNS and other brain cancers. Our AI platform, along with algorithms tuned to predict blood-brain barrier permeability, played an important role in helping determine which CNS cancers and which genomically defined subtypes of CNS cancer should be prioritized for development. Using in silico tools and also in vitro data from neuronal cell plates, neuro spheres, LP184 demonstrated permeability that was in line with TMZ and other therapies while also demonstrating nanomolar potency. This data is extremely significant. Building on this data, we believe we can identify, well, we have identified several additional brain cancers where LP184 can play a major role as a potential therapy, and we're pursuing one of the validated indications in atypical teratoid rhabdoid tumors. This is an ultra-rare tumor. brain cancer that occurs primarily in children, especially children under the age of four. And there's typically between 50 and 70 or 80 cases a year, so very ultra rare cancer without any therapies today. And so we believe we can compress the timeline to bringing LP184 as a potential therapy in this ultra rare indication. and have a potential treatment for these patients. So we're working now that we validated this both in the lab as well as in Silico. We're seeking collaborators to further sue this indication. So do we believe with the franchise now that 12 months ago was just beginning where we observed the potential for 184 to target GBM? And after GBM, we now also have found ATRT, validated blood-brain barrier permeability, identified several additional indications that were in the process of validating, and we've really developed a very unique portfolio of brain cancer indications for LP184. We believe this basket of brain cancer indications can be a very important tool to then partner with the right biotech or pharma provider. Looking to other development programs, LP100 is currently being managed by our partner for the treatment of genetically defined metastatic castration-resistant prostate cancer, while LP300, a small molecule candidate, also is preparing to enter a phase two trial in non-small cell lung cancer as a combination therapy for non-smokers. For LP300, we have made significant progress in better understanding the mechanisms involved in LP300 activity and in aligning the usage of LP300 with the chemotherapy that is more commonly used today, namely carboplatin and pemetrexid. This was accomplished through a recently completed non-clinical bridging study that showed that LP300 with carboplatin and pemetrexid is as safe as cisplatin and Paxitaxel and doesn't cause any additional toxicity or adverse events. We plan on sharing this with the FDA as part of a process to re-enter Phase II clinical trials later this year. Most recently we also announced something that is very unique and that is the launch of our antibody drug conjugate program. This was developed by leveraging the AI platform by understanding where L184 could potentially work best by synergizing with other optimal targets. And many of these targets were antibody targets and we also then were able to work with Califia Pharma to leverage a patent-protected linker library that we can conjugate with our unique DNA-damaging compounds like LP184 and potentially other payloads. According to industry analysts, the global ADC cancer therapy market is expected to exceed $10 billion by 2026, $15 billion by 2030, and it's driven by innovations in protein targeting, which is what our platform does. We're really targeting linker technologies, which we now have access to through Dr. Kalanur and Kalifia, and conjugation processes. So ADCs bring together the ability to target specific antibodies on very specific types of cancer cells and then link that antibody targeting capability to delivering our potent molecule or payload to that cell. ADCs are an emerging class of highly potent drugs that have seen several approvals over the last two years and a lot of interest from big biotech and pharma in partnering. The portfolio of technologies and library linkers at Califia has meaningfully progressed with a specific focus on our class of drugs and we believe this optimization coupled with the identification of cancer subtypes and molecular targets has allowed us to save several quarters if not years in the development process and allows us to enable targeting very specific cancers. This way we can enter the clinical trials at a speed that we believe has not been achieved in the ADC category. So again, we believe this is another major franchise portfolio of value with the agency program. Working closely with innovators and world leading drug developers is an essential part of our strategy to leverage and develop new platforms that can transform the timeline and effectiveness of cancer drug development. By implementing antibody drug conjugate approaches, we aim to offer cancer patients an additionally highly targeted platform that can make meaningful contributions and also benefit from the synergies of our AI drug development or data-driven approach. Together, our current portfolio of drug candidates and our Radar AI platform has the potential for multiple shareholder value milestones in 2021 and 2022. In addition, our Radar platform has matured to the point where we're going to begin to focus increasingly on collaborating with other biotechs and pharma companies to further develop Radar and to develop opportunities through RADAR for our investors. Now, I'll hand the call over to David Margrave, our CFO, for review of the fourth quarter and year-end results. David?

David Margrave Thanks, Akana, and good afternoon, everyone. I'm now going to share some of the financial highlights from our fourth quarter and the full year 2020. It's important to note that we incurred added expenses in 2020 as a result of becoming a public company And with our lean operating structure, these changes resulted in substantial differences for purposes of our 2020 to 2019 period-to-period comparison. Starting with highlights for the fourth quarter of 2020, when the quarter ended December 31, 2020, we had a net loss of 2.9 million, or 47 cents per share, compared to a net loss of $675,000, or $0.34 per share, the quarter ended December 31, 2019. The net loss for Q4 2020 included non-cash expense items of $1,024,904 related to employee stock option compensation. Research and development expenses were $1.3 million for the quarter ended December 31, 2020, compared to $177,000 for the quarter ended December 31, 2019. The increase was primarily attributable to increases in research studies and non-cash research and development related stock option compensation expense, as well as the expansion of the company's research team. The Q4 2020 non-cash R&D expense related to stock option expense was $470,401. General and administrative expenses were $1.5 million for the quarter ended December 31, 2020, compared to $498,000 for the quarter ended December 31, 2019. The increase was primarily attributable to an increase in expenses associated with operating as a public company, along with increases in non-cash general and administrative related stock option compensation expense. The Q4 2020 non-cash G&A expense related to stock options was $554,503. In terms of fiscal year 2020 financial highlights, As of December 31, 2020, we had working capital of approximately $19.7 million, primarily driven by the net proceeds of our IPO that closed on June 15, 2020. For the year ended December 31, 2020, we reported a net loss of $5.9 million or $1.37 per share compared to a net loss of $2.4 million or $1.23 per share for the year ended December 31, 2019. Research and development expenses increased $1.3 million or 135% from $953,000 for the year ended December 31, 2019 to $2.2 million for the year ended December 31, 2020. The increase was primarily attributable to increases in research and development labor and research study expenses, as well as an increase of approximately $470,000 in non-cash research and development related stock option compensation expense. General and administrative expense increased $2.2 million or 149 percent from $1.5 million for the year ended December 31, 2019 to $3.7 million for the year ended December 31, 2020. The increase was primarily attributable to expenses associated with transitioning to and becoming a public company, including increases in corporate insurance expense and general and administrative labor expenses, as well as an increase of approximately $604,000 in non-cash general and administrative related stock option compensation expense. We expect we will continue to increase our R&D spend as we further advance our portfolio and recently initiated ADC program and move towards the commencement of additional clinical trials and research studies. Currently, we have 15 employees, 11 full-time, four part-time, as well as four consultants who are primarily focused on leading and advancing our drug development, biology, and data science efforts. Our cash position at December 31, 2020 was $19.2 million. As a result of our 2020 development and operational progress, as Pana discussed earlier in the call, we were able to significantly strengthen our balance sheet subsequent to year end with the closing of a $69 million follow-on public offering in January 2021. This additional cash extends our anticipated cash runway through mid 2025. We believe our solid financial position will fuel continued growth and evolution of our Radar AI platform, accelerate the development of our portfolio of targeted oncology drug candidates, and allow us to introduce additional targeted product opportunities in a capital efficient manner. I'll now hand the call back to .

Thank you, David. I have a few more comments before we open up for Q&A. Moving forward, we expect to make additional progress on the development of our existing programs while also strategically focusing on new opportunities that we are uncovering or that we can create in collaboration with others. As seen from our growth in programs from three to seven just over the last several quarters, we believe that our data-driven, genomically targeted and AI-driven approach is really a transformational way to do drug development for oncology and allows us to identify and rescue and develop candidates that we believe can be done at a fraction of the time and cost associated with more traditional methods of development. Our dual approach to developing both de novo biomarker-guided drug candidates and also having the potential to rescue historical drug candidates by leveraging the data sets and other work inside of RADAR, we believe is a massive advance in genomics, computational biology, and cloud computing. We believe this is emblematic of a new era of drug discovery and development that we are proud to be a leader in. In this context, we are focused on building a portfolio of high-value oncology drug candidates, each of which can be potentially partnered for pivotal registration-directed trials or sold or licensed off. We believe this provides a very clear and defined path for potential significant value creation for our shareholders, and establishing Lantern Pharma as the leading AI-driven oncology drug discovery and drug development franchise, we believe is something that we're well on the path to do. So with that, I'd like to go ahead and make sure people understand that the key goal of our company and franchise is to transform oncology drug development to the use and power of AI and build true enduring value by doing that. We think the golden age of AI and drug discovery and development is here today and will have significant repercussions throughout medicine. We believe we're one of the leading leaders in this paradigm shift to change the pace, risk, and cost. of oncology drug development and that we are proving that our platform can provide significant efficiencies in the time and cost. More importantly, our growing pipeline of drug candidates shows that the rapid identification and validation of molecular drivers of cancer allows for a more targeted and more effective pathway to developing new drug candidates, identifying drug combinations, and potentially new constructs such as antibody drug conjugates. So we look forward to sharing our ongoing progress with you in future updates, and hopefully more of these in person as the year progresses. I would also be remiss not to take some time to thank everyone who's been on the front line or knows people on the front line of all the work that's being done, especially with healthcare workers and advocates, and of course all the millions of people that are helping to care for and put an end to this COVID pandemic. We should all take time to be thankful each day for the efforts they have put forward to bring society and business back toward normalcy. They've oftentimes done this in a hostile and oftentimes under accepting umbrella of being misunderstood. So with that, I'd like to really put my hat and say thank you for all the work that everyone has done. to make a change and bring this pandemic to an end. And I look forward to meeting more of you in person throughout the year and resuming more normalcy to business and society. And with that, I'd like to open up the call for questions.

At this time, if you would like to ask a question, please press the star and 1 on your touchtone phone. You may remove yourself from the queue at any time by pressing the pound key. Once again, that is star and 1 to ask a question. And we will take our first question from Kyle Bauser with Collier Securities. Go ahead. Your line is open.

Great. Thanks for taking the questions and appreciate all the updates here. Certainly a lot going on. I know you talked about the current cash balance being able to get the company to mid 2025, Could you talk a little bit about how we should think about the quarterly burn with the most recent updates on the ADC program and other opportunities like ATRT? Just want to make sure I'm thinking about the burn correctly over the near term here.

Yes, absolutely.

Great question.

I'll let David walk through. I'll let David kind of walk through this. the burn and how we see that progressing. But we do see it progressing upwards over the years. So, David, do you want to walk Kyle through that?

Absolutely. So it's a great question, an important question for us. You know, we are in a much stronger financial position now, and this allows us to execute on a lot of things that we had brought online and positioned for since the time of our IPO. But this really allows us to accelerate that We will see a substantial ramp up as we move towards the launch of LP300. Additional clinical trials we have planned related to 184 as well as our ADC program. And over the course of the next two to three years, we see our quarterly burn increasing substantially. A higher and higher proportion will be associated with R&D. We see that increasing in particular as we start the phase three for LP300 and then in 2021, end of 21 and start of 22 as we move towards starting additional clinical trials for 184.

Got it. That's helpful. And just curious, regarding the ATRT opportunity, it sounds like this ultra-rare condition could allow for a much faster timeline, but given the small prevalence of the addressable patient population, would pricing be able to offset the small number of potentially treatable patients? I'm just trying to understand the ROI on this opportunity, given the prevalence size. Thank you.

I think you're right. The prevalence, again, it's an ultra-rare cancer. I think for us, we're more interested in benefit to that patient population initially, but also once we have the drug in market, there are a number of other tumors that are similar to ATRT. These rhabdoid tumors also occur in certain forms of kidney cancers and sarcomas, and they're oftentimes marked by a certain biomarker that makes them sensitive to our drug. You'll see that we'll publish a little more about that later, but it relates to the gene SMARCB1. So when SMARCB1 is mutated, it tends to then not produce a downstream protein, also SMARCB1, which is a tumor suppressor. And it occurs in a few percentages of cancer, but mostly in ATRT and certain kidney cancers, synovial sarcomas. And so our goal is we know there's a need in this patient population. We know there's clear ability for this across the blood brain barrier. We believe we can get fast track. And then we can introduce LP184 and some of the other cancers that I talked about, which will increase the size of this market significantly, but also since we'll have our drug in market, we can then pursue other combination indications. So it's really not just the ATRT market alone that we're looking at. We're also looking at once this drug is in market and being used clinically, that opens up a lot of other opportunities that we would not have by not having a drug that's being routinely used.

That's helpful. Great. Well, thanks for taking my questions and for providing all the updates here.

Thank you, Kyle.

And we will take our next question from Daniel Carlson with TW Research Group. Go ahead. Your line is open.

Yeah, thanks for taking my question, guys, and congrats on all the progress. Just a couple questions, Tana. You talked about the ADC program a little bit, and it certainly seems like an attractive space to be in. Can you provide any additional insights into what is going to happen exactly in your program and timing around that?

Sure. Thank you, Dan. Good question. So we've done some more progress on the ADC work. We probably will host a conference call or a broader update later this year. But we've really narrowed in on certain antibody targets specifically targets where the antibody can be internalized into the cancer cell. And as a result of the changing environment, release the payload. So this cleavable linker, we've kind of identified, we've identified a few of the antibodies, specifically antibodies that can be internalized. So we have some initial data on that. So we've continued to narrow down the program in terms of how we would approach it. We also have kind of a backup category. We also have some initial indications in a heme cancer as well that we might pursue. But the key for our drug to work is for the drug to be internalized into the cancer cell. And so that has narrowed down the way that we're thinking about the antibody that we're conjugating it to. So it gives us a pretty small window of the antibodies that we're most likely to look at. So I feel like we have a pretty focused program on this. And, you know, again, we're going after some solid tumors where there really hasn't been notable improvements in overall survival. So we think that there's potential for partnering this asset out for a significant amount quickly.

That would be excellent. Thanks. Second question for you here. There was a paper published on BMC bioinformatics last week that really seemed, in my opinion, to help validate exactly what you've been saying about radar. And I wonder if you can provide any more insight into that. And then a second part of this question, you talked about the platform, radar platform. I'm wondering how you can really leverage that. Is it through bringing in more drugs onto your platform, or is there potential to, as you build it out and it gets bigger, to take it out to a broader audience through partnerships, et cetera?

Yeah, great question, Dan. So the interesting thing is that the paper, you know, it's already dated, but, yeah, it's a great paper because it showcases how we're using it to make decisions about the indications that we're going after, and the types of genomic information that it's zeroing in on. And, again, this is for a fairly small group initially when this work was started. You know, our group has increased as, you know, we were six people when we went public. We're 15, so still not huge, but, you know, we have more talent, and we can crunch through more data and more numbers and do more with the platform. But, yeah, the BNC Bioinformatics paper is a great example of how we can use radar processes on one specific drug to unlock multiple potential indications. In terms of we developed a signature, we selected preclinical indications that we went into the lab with that really bore out a lot of fruit. And actually now the platform has actually grown significantly since we started working on that paper. And because of that, we do think that we'll be able to start generating what I call time to indication. typically takes six months to a year, and we're able to bring that time to indication down to a matter of weeks. And so at that level, we'll come up with more ideas than we can possibly develop completely on our own. So we do think it's getting to the point, especially as radar gets to two and three billion data points, which should be fairly quickly this year, that we will seek more partnerships using the platform. It will make the platform more powerful and we think be able to potentially give our investors upside in other programs. So yes, that is part of our strategy that we're beginning to unfold now is to take some of our time and interest and take a look at how we can leverage this platform to get access to other programs, other indications, other molecules. And there are a lot of companies that have approached us and we've had some discussions with. So that's something that we will selectively pursue this year.

Great, thanks. And then just one quick follow-up on this ATRT and maybe a little naivete on my part, but would this qualify for a priority review voucher?

David, do you want to talk about what we know about the priority review program?

Sure, right. We think there is potential for that. And the voucher program, as many know, is something that has just been re-extended with recent legislation, so that's encouraging in terms of further incentivizing companies to pursue pediatric indications. The vouchers are able to be used by the sponsor, or they could also be purchased by another company. So there is potential value in the rare pediatric disease voucher program, and we're learning more in terms of the details with respect to ATRT and that indication, but from what we are aware of right now, we believe that it would be potentially eligible for the voucher program.

Great. Yeah, those have been traded for like $100 million, so that would be awesome. That's it for me. Thank you. Keep up the great work.

Thank you. Thank you, Dan.

And once again, if you would like to ask a question, that is star and 1 on your touchtone phone. We will take our next question from John Vandermosten. Go ahead. Your line is open.

Hey, good afternoon, Pana and David. How are you guys doing? Let me start with a question on 184. It seems like the potential for that is fairly broad. You've named a number of areas there, including CNS, which could be a number of indications there. How are you going to use the data that comes up to narrow that down further and, you know, when you probably get to perhaps phase two or something like that to know what you're going to try to take all the way to the end?

Well, we are looking at what, you know, is there a subset or what subset of glioblastomas will this work in best? And so that's something that we're hoping in the next few months we'll better understand. And I do think that also in the other indications that we're pursuing won't be the entire indication, but again, it'll be a subset or some genomically defined group. And so that's typically how the trials will be organized or structured.

Okay. And I guess, you know, sometimes there are trials that have multiple indications in them and they're adaptive and you move forward based on what's working. Is that something that you try?

Oh, yeah, we've been looking at that quite a bit, absolutely.

Okay.

We look at those adaptive as well as basket trials for some of these indications across. Right, right. So we'll definitely look at those. It's a little too early to pin one of those down right now.

Okay. No, that's a great way to do it because it seems like there's a lot of opportunity, and you obviously want to focus on what's most promising. Okay. And you mentioned a bit about talking to other companies, and that seems like a great way to help some collaborations going forward. You know, you bring the radar platform to the table and your portfolio as well. How do you go about doing that? Do you reach out to maybe smaller companies? Because larger companies probably have their own AI system that they use. But maybe smaller companies and say, hey, you know, share some of your data with us. You know, we'll see if there's any opportunity. Is that how you do it? Or what's the process there to find potential?

I think there are definitely certain drug classes that are better. And so I think it'll be in certain drug classes where we know we have some interest, where we know we have some unique data. We'll also, of course, look for areas where there's been a clinical failure where we believe we can add value. And, of course, because of the ADC, we have identified some antibody targets, too, that people own, and that combined with 184 or one of our other drugs could be really unique. So I think there's some... natural areas where either we have inside data or knowledge that we'll try to exploit first, and then after that it's just, you know, traditional BD efforts.

And do you get sharing from other companies? You know, they share their data with you in an effort to, you know, see how the radar platform works and how it might help them narrow down an indication.

Yeah, that's the hope is that we would get a percentage, that's right, of the success of that drug or that drug in the indications that we helped them outline and develop.

Okay. And wanting to move on to LP100, I mean, I know that's an external asset, but what should we expect in the near term on that? What is the next milestone that we should see on LP100?

We're having discussions with the hilarity on the program, and the next stage is that. So I think we'll keep people updated as soon as we have details on the progress on the molecule and the progress of the trial.

Great. Well, thank you. All my other questions were answered. Appreciate it. Thank you, John.

And this does conclude today's question and answer session. I will now turn the program back over to our presenters for any additional or closing remarks.

Thank you. And thank you, everyone, for participating on our quarterly call. We look forward to visiting many of you in the near future. And again, we believe that we really are a leader in the transformation of oncology drug development using machine learning and AI. And we believe that many of our programs can be worth significantly more than our market cap today. So we think there's a lot of upside for investors as we grow and meet milestones. Thank you for listening to our call today.

This concludes today's program. Thank you for your participation. You may disconnect at any time.