Lantern Pharma Inc.

Hi, everyone. Good afternoon. We're going to give everyone a couple of seconds to join. Okay. We'll get started here. Good afternoon and welcome to Lantern Pharma's third quarter 2021 earnings call being brought to you today as a Zoom webinar and conference call. As a reminder, this call is being recorded and all of the attendees are in a listen-only mode. I am Nicole Lieber with Finance and Administration at Lantern Pharma and I will be your host for today's call. I will be joined by our CEO, CFO, and CSO. During the call, if you have a question, please type your answer in the Q&A box. We will open the call for questions and answers after the presentation, which will be managed by our CEO, Panna Sharma, where he will be supported by our CSO, Kishore Bhatia, and our CFO, David Margrave. A press release was issued today after market closed with Lantern's third quarter 2021 financial results that management will be discussing during the call today, as well as providing a corporate update. Following the safe harbor statement, Ponna will provide an overview of Lantern's business highlights, after which David will overview Lantern's quarterly financial results, and Dr. Bhatia will provide an update on our R&D efforts. Ponna will then offer concluding comments, after which we will answer questions. Please also note that we have provided a link on the investor relations website for the slides that management may reference in today's earnings call and webinar. I would also 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. Antrin Pharma cautions that these forward-looking statements are subject to risks and uncertainties that may cause actual results to differ materially from those anticipated previously. A number of factors could cause actual results to differ materially from those indicated by forward-looking statements, such as 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 quarterly report on Form 10-Q for the third quarter of 2021, and in the risk factors section in our annual report on Form 10-K for the year ended December 31, 2020. Both of these documents are on file with the SEC and available on our website. Forward-looking statements made on this conference call speak only as of today, Monday, November 1, 2021, and Lantern Pharma does not intend to update any of these forward-looking statements to reflect events or circumstances that occur after today unless required by law. A webcast replay of the conference call and webinar will be available on the Lantern Pharma website. And with that, I'd like to turn the call over to Pana Sharma, President and CEO of Lantern Pharma. Pana, please go ahead.

Thank you, Nicole. Good afternoon, everyone, and welcome to our third quarter earnings call. Thank you for joining us today. We're also live streaming this call through a Zoom webinar, which many of you investors have asked for and feel that this format can potentially bring you more information or insight about our business. Thank you for your feedback and requests. And bear in mind, we'll always work in improving facets of our operations, both internally, but also our communications with investors externally. This past quarter, third quarter, has been a very exciting and very busy quarter for Lantern. We've made meaningful progress on multiple fronts, clinically, operationally, on our radar platform, which many of you read about this morning. and also with our ongoing discovery efforts. I'd like to highlight that we have exceeded our growth expectations that we set out earlier this year regarding our proprietary AI platform, Radar. We just surpassed 10 billion data points this past month, and this represents a 10x increase in the number of data points since November of last year and approximately a 37-fold increase since our June 20 IPO. The increase in data points, which many of you have asked about in the past, provides Lantern an important long-term advantage. First, it accelerates our drug development timelines by giving us ideas about indications or the feasibility of certain indications. It allows us to uncover new therapeutic opportunities and potentially in-license new compounds or find new uses for our existing portfolio. It also allows us to develop insights into how we can create combination therapy programs with our drugs and existing approved therapeutics. And we'll talk a little bit about that today as well. And most importantly, it expands our ability to collaborate with additional biopharma partners. We believe that the platform has gotten to a stage where it can be used not only for our existing portfolio, but for many other drug development portfolios in oncology. Radar uses vast amounts of data from the transcriptome, from the genome, from expression data, methylome data, drug sensitivity data from a wide range of curated sources, both human, animal, cell line, PDX, 3D spheroid, and even cell line. All these data are analyzed, monitored, scored, and constantly updated. And ultimately, the goal is to reduce the cost reduce the risk, and accelerate the timeline to get drugs developed by uncovering mechanistic insights on drug-tumor interactions and developing companion diagnostic biomarker signatures. Biomarker signatures are essential in de-risking drug development, and as I'll talk about later, have proven to increase the likelihood of bringing a drug to market on an average of five times higher than those developed without such signatures. Ultimately, our goal is to potentially benefit and select patients that have the best option for our drug therapies or our combination therapies that we uncover. Now, corresponding with this growth in data points, we also focus our resources and the technology on a very important area, which is the growth and constant improvement evolution of our library of algorithms. Algorithms are critical because they are constantly evolving. giving us new ways to correlate the data, automatically sift through the data, and more importantly, give us new ways to rapidly identify correlations we may or may not know about that are critical to making decisions in cancer drug development. They also allow us to rapidly identify rare cancer subtypes that may have gone unknown or unnoticed or misunderstood. And they provide insight into potential drug target interactions. They also can help uncover patient groups that can respond to specific drugs, not only at one time, but over the course of their treatment. Now, with such an incredible assortment of algorithms and as it grows, what we've done is also embedded a machine learning development operations environment. This is very important because it allows us to then pick and choose and select and compare different algorithms and how they perform or algorithms being used together. When algorithms are used together, this is called an ensemble-based approach, where we use multiple algos and methods, and we can rapidly and with higher accuracy understand what the response is going to look like in a patient or a group of patients to our drug or drug candidates. All of this is critical because it helps define and develop the strategy to bring this drug to market and develop combination strategies that we think have a higher chance of approval. We plan on continuing further data expansion. Many of you have always asked me how much data is enough. The answer, really, there is no enough in data. 10.4 billion data points is a wonderful and very meaningful milestone for our team. But there are tens of billions of additional data points to collect, hundreds of additional cancers to further explore, and additional data sets being generated globally every single month. Our job is to bring in these data sets, score them, understand them, and more importantly, do this in an automated way where we can evolve radar, but mostly now is turn our attention to the library of algorithms that we're evolving. Lantern will continue to augment the 10.4 billion data points, but in a very specific sets of areas. One area that we looked at last quarter was in hematologic cancers. A major chunk of our growth came from blood cancers because of our own focus on blood cancers going into 2022. Additionally, this coming year, we'll be focusing on immuno-oncology-related studies and trials. Data from these studies and trials will include antigen, immunomic, and protein data, and also robust multi-omic analysis that's out there. As many of you know, there's a wealth of methods and algorithms already in development for IO drug response prediction and IO drug response combination creation. Our team will review many of these, they'll improve them, they'll incorporate them, and this will make our platform even stronger. We think this will be a long-term strategic advantage as we deepen our capabilities in two very important areas, antibody drug conjugate development and combination therapies using IO agents. We already have significant reason to believe that certain IO agents, especially those that show high sensitivity and TMB high, TMB meaning tumor mutation burden high, is as marked in certain cancers. And they may have the potential to work synergistically with either 184 or 284, especially in intractable and more challenging tumors. Turning my attention out of the biomarker signature, we think this is of real importance, but in a recent multi-year study, done by Professor Dr. Jason Parker from University of Toronto. He and his colleagues reviewed over 10,000 clinical trials from 1998 to 2017 in four solid tumors across 745 drug programs, and they showed that biomarker-based trials had success rates that were 4 to 12 times higher than those that did not use biomarkers. Actually, Dr. Parker's team concluded that the inclusion of biomarker status as a covariate significantly improved the fit of his Markov models that they used to describe the drug trajectories through the clinical trial testing stages. So the hazard ratios on the Markov models reveal that the likelihood of a drug approval with biomarkers had an average of 5X increase across all four solid tumors. And it was 12X, 8X, and 7X, respectively, in breast cancer, melanoma, and non-small cell lung cancer, all diseases that are highly related and driven now by biomarker analysis. Markov models, even with exploratory biomarkers, outperform Markov models with no biomarkers by a major factor. So his team's conclusion? Well, first of all, we just know this is one of the first systematic statistical case reviews done. But we showed clear evidence that biomarkers clearly increased clinical trial success rates in multiple indications in oncology. And very importantly, exploratory biomarkers, long before they're properly validated in many labs, appear to improve success rates in the drug development process. This supports one very important thing, early and aggressive adoption of biomarker-based signatures and biomarker-derived signatures in oncology clinical trials. This is a hallmark of our development process. This further encourages us that utilizing our radar platform with our drug candidates and also independently across cancer drugs to derive biomarker signatures has a unique potential in addressing the $200 billion global oncology drug market. and it has a long-term place in the future of cancer drug development and discovery. We've witnessed firsthand now that the growing industry interest in solutions that innovate the development of precision therapies and combination therapies and reduce the risk and cost. We believe that these kinds of solutions will pave the road, this kind of appetite for solutions will pave the road to new partnerships and ultimately greater investor value. We remain committed to achieving our goal of building the world's largest AI platform for precision oncology drug development. We believe we're significantly on our way there already. Our goal next year is to get to over 20 billion data points, deepen our focus on blood cancers, add several additional rare cancers, and add valuable data that will aid in IO and ADC development. We believe that our AI platform will be pivotal in uncovering potential new therapeutic opportunities and also opportunities both internally and with third-party collaborators. Now, getting into our drug candidates, during the quarter, we reported positive preclinical data for LP184 in pancreatic cancer and GBM, glioblastoma multiforme of brain cancer patients. We also advanced LP300 toward a phase two clinical trial for never smokers and non-small cell lung cancer. We began assessment of the next phase of our LP100 program in metastatic castration-resistant prostate cancer and potentially other cancers that we'll talk about later. And we prepared LP284 for further development in blood cancers as we have some exciting data coming out later this quarter and also LP284 next year in 2022 will be a significant area of focus. Now, first, as a result of the encouraging results in 184 in GBM and pancreatic cancer, we were granted orphan drug designation. Now, receiving orphan drug designation gives us several benefits, which many of you know about, market exclusivity for seven years, eligibility for tax credits for qualified clinical trials done here in the U.S., waiver of marketing registration application fees, reduced annual product fees, and assistance in the clinical protocol, as well as review applications. hopefully in an expedited manner. These are all massively important because they reduce our burden of development and they give us increased commercial protection. Two very important areas that investors should look for as positive early validation. We've accomplished both in this past quarter. We continue to look at orphan designation as an important milestone, but also validation of our novel AI-driven approach. We also submitted an abstract with Dr. Igor Astrosov, an established NCI-funded physician scientist. He's also co-leader of the Marvin and Conchita Greenberg Pancreatic Cancer Institute at Fox Chase Cancer Center, and that was accepted for presentation. at the AACR virtual conference in pancreatic cancer. We released data about the abstract and about the work that was designed that showed the efficacy of 184 in multiple mice models, and it showed increased efficacy potentially as a synthetically lethal agent in pancreatic cancers that also harbored some kind of DNA damage repair deficiency. And our chief scientific officer, Kishore Bhatia, will talk about that later. This is an area that's particularly unique, and we're continuing further development because it provides us a roadmap for prioritizing additional cancers where we can potentially develop first-in-class solutions or show significant improvement over the existing standard of care outcomes. LP184 also showed potentially best-in-class efficacy in pancreatic cancer with a unique mechanism of action. The study that we did observed that LP184 not only had very good effect in pancreatic cancers, but also pancreatic cancers that were resistant to standard of care drugs. We also showed very importantly using CRISPR and gene editing, that the biomarker that we had predicted through radar does actually directly link to the anti-tumor activity of 184. This is PTGR1, where we saw not only just really exquisite activity once PTGR1 was there, but we saw really no activity. It was almost a black and white scenario if you look at the charts. And we believe we can exploit this biomarker mechanism in various tumors beyond pancreatic cancer in the future. And very importantly, again, take a biomarker-driven approach to selecting and developing the trials. We are now in discussions in the design of the first in human clinical studies for 184 in collaboration with Fox Chase and other KOLs in the pancreatic cancer treatment landscape. We plan on, as Dr. Bothell will tell you, we've initiated IND enabling studies, and those will then inform and guide our phase one human trials next year once we finish the IND application. I'm also very pleased to announce that we'll be hosting a virtual KOL event for LP184 in pancreatic cancer with Dr. Igor Astrosov and Kishore Bhatia on November 18th, World Pancreatic Cancer Day. We'll announce the details of this event later this week. We also reported, very importantly, in another what we feel is a multi-billion dollar global indication against an intractable cancer, GBM, glioblastoma. LP184 was able to significantly improve survival in animal models in a statistically meaningful way. This study was done with Kennedy Krieger and Johns Hopkins University, and results of this study are expected to guide the clinical application and focus of this drug candidate. Now, our next phase, as we expand to the next phase of the work with Johns Hopkins and Kennedy Krieger, is to look at a very important observation. And that is that we've looked at in silico that LP184 can be an effective treatment in glioblastoma, which we now have seen in the lab, and we've proven that in mice. And we plan on taking this into humans next year. But one important observation is that we think that it can be an effective treatment in GBM regardless of MGMT status, a DNA repair enzyme that gives you not only a status of the cancer, but potentially... actually gives information about its ability to respond to TMZ. We believe that this has significant potential to provide a much-needed alternative to the standard of care drug, temzolomide, especially in GBMs that overexpress MGMT, which is about 50% of GBMs. So this is a major population that needs a new drug choice. These patients that are overexpressing MGMT are generally unresponsive to TMZ, and they need new therapy options. So development of an agent with efficacy in GBM, regardless of MGMT status, would be an important advancement towards addressing this critical gap, and we believe is a molecular pathway that can be exploited elsewhere. Our current in silico analysis actually shows that LP184 should work regardless of the status, but actually, interestingly enough, actually shows increased sensitivity in many MGMT cancers. Now, we also plan on launching additional studies for the ADC program in Q4, and we expect to have data during the second quarter of 2022 for our ADC program in a few specific designations. So unlike conventional cytotoxic agents or chemotherapy or even some targeted therapies, that can damage healthy cells or have toxic side effects, ADCs are targeted medicines that can deliver the chemotherapy or targeted molecular agent to a very specific cancer cell through the ADC. Connecting the ADC and the right molecule is a little bit of a science and art to the linkers. Now we've been working this year on perfecting this, and we believe we can take advantage of the high potency of our molecule and the superior specificity of some of the antibodies that we've selected. We believe our ADC program represents a huge market opportunity, as two out of the four largest oncology licensing deals last year were in ADC assets. And it's clear that ADCs will continue to be a critical part of the therapeutic armamentarium against cancer in its area where our AI platform is only becoming more relevant and more powerful. Turning now to LP300 candidates. We've entered into a strategic collaboration with Deep Lens. It's a digital healthcare company enabled on one thing, and that's faster recruitment of the best suited cancer patients that meet our protocol. So we're leveraging their AI clinical trial technology, Viper, to basically create a unique end-to-end solution where we're using AI to basically develop the drug, but then we're using AI to actually find the patients. So their technology is able to comb through thousands and thousands of records, electronic medical and health records, to understand the criteria that allow us to match the right patients. In our case, never smokers, with non-small cell lung cancer that are chemo naive and are relapsing from TKI. Now we have experienced some supply chain and sourcing issues caused initially by COVID-19, then eventually seeking into global shipment and equipment availability, and then sourcing some backup equipment. So we're delayed in finalizing our manufacturing, But we are planning to launch a 90-patient Phase II clinical trial in the U.S. in the near future, meaning later this quarter, early Q1, in non-small cell lung cancer focused on the never-smoker population. There are no other trials focused on this population, and we believe we have a unique protocol with a very clear selection list for the patients. So we're now planning on enrolling about 20 sites in the U.S., and we believe we can select four to five patients at each of these sites, never smokers, and fairly quickly. Our existing AI platform allows us to predict drug outcomes, and the Viber platform allows us to use AI to find the appropriate patients and proactively suggest patients that can match to our treatment. We think this will reduce the timeline next year and, more importantly, reduce the cost. We'll always enter into really exciting collaborations with like-minded companies or with companies that are leading leaders in their industry. One such was Code Ocean. They're a leading computational research environment for sharing scientific discoveries. So not on the patient side, but in the internal operations side to very different areas. But Code Ocean allows us to share scientific discoveries in a more secure, more transferable manner. and allows us to do it internally and externally with our network of collaborators. It allows us to manage our external data and our code with simple ease in a much more cost-efficient environment, and it already takes our radar platform and adds new efficiencies in terms of development time and cost. So we think this powers our platform for faster, more collaborative discoveries, not only internally as we have distributed teams, but also with our collaborators at major research institutions. As evidenced by our progress this quarter, again, not only clinically, but also across any number of measures, we remain very excited and committed. We've announced some exciting and positive data as well, and we believe that these advancements are the types of advancements that are needed to change the cost and the risk associated with cancer therapy development. I'm also pleased to to report this quarter that H.C. Wainwright Investment Bank has initiated research coverage on Lantern, and we remain committed to growing awareness of Lantern within the investment community, especially with the number of upcoming milestones that we have. We have a lot of progress in our ATRT program, which for sure we'll talk about progress in the IND enabling studies for our ADC program. And also we'll have results in 184 in a number of indications, including pancreatic bladder and GBM in the coming months. So we have a lot of data to share, but also we have continued to show good financial discipline. And I'll ask David Margrave, our CFO, to provide an overview of our third quarter financial results. David.

Thank you, Pana. And good afternoon, everyone. I will share some of the financial highlights from our third quarter of 2021 ended September 30, 2021. We had a net loss of approximately 4.1 million or 36 cents per share for the quarter ended September 30, 2021 compared to a net loss of 1.7 million or 27 cents per share for the quarter ended September 30, 2020. Research and development expenses were approximately $2.96 million for the third quarter of 2021 compared to approximately $0.6 million for the third quarter of 2020. The increase was primarily attributable to increased manufacturing related expenses and expenditures to advance and expand the company's product portfolio. General and administrative expenses were approximately $1.2 million for the third quarter of 2021, compared to approximately $1.1 million for the third quarter of 2020. The nominal increase was primarily attributable to increased business and corporate development expenses, legal and patent related fees, and general and administrative related stock option expenses. Our R&D expenses for the third quarter of 2021 were approximately 2.5 times the amount of our G&A expenses for this same third quarter 2021 time period. This reflects our continued focus on advancing and expanding our product pipeline. Our team continues to be very productive, especially as we migrate to a hybrid work environment. We currently have 16 employees who are primarily focused on leading and advancing our drug development, biology, and data science efforts. We see this number expanding slightly in coming quarters as we add additional high caliber multifaceted individuals to help advance our mission. To date, we believe we have effectively managed the impact of the COVID-19 pandemic on our operations. Recently, the timing of manufacturing for our LP 300 and LP 184 candidates has been impacted by supply chain delivery issues, as Pauna mentioned, which has extended the time to launch our planned phase two clinical trial for LP 300 and extended the time to commence IND enabling studies for LP 184. Nevertheless, we are making continued progress despite these hurdles. As of September 30, 2021, we had approximately 11.2 million shares of common stock outstanding. This includes approximately 4.9 million shares that were issued in our January 2021 follow-on offering. At September 30, 2021, we also had outstanding warrants to purchase 298,204 shares and outstanding options to purchase 801,588 shares. These warrants and options, combined with our outstanding shares of common stock, give us a total fully diluted shares outstanding of approximately 12.3 million shares as of September 30, 2021. Our cash position, which includes cash equivalents and marketable securities at September 30, 2021, was 73.8 million. $73.8 million. This balance is expected to carry us into 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 and collaboration opportunities in a capital-efficient manner. Thank you, and I'll now hand the call back to Pana. Ana?

David, thank you very much. I'd like to now invite our Chief Scientific Officer, Dr. Kishore Bhatia, to provide some detail on the growing data and excitement on some of our early stage programs. Also, we'll be sharing data for the first time on several of our programs and some insights during this call. So, Kishore, please go ahead.

Thank you, Panath. I'm excited to report the initiation of our IND enabling studies for LP184. Our first animal, dog, and rat toxicity and dose range finding studies are expected to begin in the next couple of weeks. These studies are projected to be completed by April, paving the way for us to take LP184 to the clinic. We continue in addition to build on more evidence supporting the uniqueness of our molecule, LP184. Moving forward with data from the previous quarter that showed efficacy in pancreatic cancers, we now have direct evidence of enhanced efficacy in pancreatic cancers with specific mutations that affect the transcription-coupled nucleotide excision repair pathway. The transcription-coupled nucleotide excision repair pathway is a specialized pathway that cells use to repair DNA from damage that blocks transcription. Our drug exhibits heightened sensitivity to cancers that have damage in such genes that are part of the nucleotide excision repair pathway. An example of the correlation between the TC-NER pathway is provided in this slide. What you can see in this slide is that if a cell is a wild type, that is, it has no mutations in any of these pathways depicted by the blue horizontal line on the top, the cell survives well. If there are mutations in specific genes in the pathway, and here we have interrogated three genes that are part of this pathway, XPD, ERCC1, and CSP. The presence of LP184 in these cells make LP184 synthetically lethal to these cells, and these cells die. Very recently, using a CRISPR-based ERCC4, again, ERCC4 is a part of the NER pathway, using a CRISPR-based ERCC4 cell line xenograft model, we demonstrated a doubling of the efficacy of LP184 in these tumors. So these data merge quite well with other data that I'm going to show you in the next slide, which we obtained in prostate cancer models. And here what we have done is we have taken prostate cancer models and down-regulated BRCA2 by using SHRNA. So these cells are slightly different than the cells that I was showing you earlier. Here we have created homologous recombination deficient cells versus previously I was showing you nucleotide excision repair deficient cells. Nonetheless, in cells that are homologous recombination deficient, as you can see in the left-hand panel, the downregulation of BRCA2 by shRNA increases the potency of LP184 tenfold. This is significantly greater than the effect Olaparib has on these cells, where the increase is roughly about 1.7 fold. The uniqueness of LP184 lies in these two aspects. Not only does it target cells that have nucleotide excision repair deficiency, but it also targets cells that have homologous recombination repair deficiency. This dual targeting of pathways by LP184 is very unique and does not lie either with known alkylating agents or known PARP inhibitors. We are very excited because this allows us to utilize LP184 for a wide variety of tumor systems. During this quarter, we further strengthened LP184 positioning for a very rare central nervous system tumor. called atypical tetroid rhabdoid tumor. We got a sense that this tumor would be an indication from our radar data. It suggested to us that Lb184 would be very sensitive in those cell lines that have a deficiency of SMARC. Now, ATRT happens to be a tumor that is driven by a deletion of SMARCB1, which is a chromatin protein. We followed these clues and were benefited by this amazing data. And as you can see in the graph in the panel on the left, which shows you tumor growth in presence or absence of LP184 in mice implanted with ATRT. The blue line shows you how the tumor would grow without the drug. And the red and the green line shows you the regression of the tumor when LP184 was injected, either at a dose, at a very, very low dose of 2 milligrams per kg or 4 milligrams per kg. The right-hand panel basically gives you a sense of the size of the tumor attains when it is not treated, roughly to about 5%. 1.5 to 2 centimeters. And in mice that are treated, there is barely any tumor, much less than 0.2 centimeters. Our GBM story also continues to gather strength. And at this time, I'm very excited to report that when we look at LP184 and compare it with TMZ, For each of the criteria that can be used to score the bioavailability, the CNS bioavailability of the drug, LP184 compares quite well with DMC. Either we use an ADMETS R2 in silico analysis or we do a 3D cell culture permeability assay or directly go into the mice, inject LP184 and ask what amount of LP184 reaches the brain Each of those criteria give us confidence that LP184 would be an excellent candidate for CNS bioavailability. And knowing that it affects orthotopic models of GBM, we are very excited to move ahead with LP184 in the clinical areas of GBM. Obviously, these data allowed us to move forward and obtain ODD designation, orphan drug designation for GBM, and the previous data I discussed allowed us to obtain an orphan drug designation for pancreatic cancers. But the data that I showed you about ATRT has now allowed us also to move forward and apply for orphan drug designation as well as pediatric rare disease drug designation for ATRT indications. During this quarter, we have further delineated, based upon in vitro studies, some very exciting combinations of LP184. Again, this is driven by a lot of clues. We get both from our wet lab studies as well as from radar. And basically, we have identified approved compounds that we can combine LP184 and allow LP184 to affect tumors, even tumors that don't have NER mutations, in the same way as if the tumors were NER deficient. Our molecule, LP184, continues to progress through a better clinical understanding of these combinations. I will now turn to our new molecule 284, and we are obtaining additional indications where we can fill unmet clinical gaps. In the next month, we will begin an advanced collaboration with a well-known hemato-oncologist from Duke University, where we will begin animal studies on a range of hematological cancers, including mantle cell lymphoma and diffuse large B cell lymphomas, and others in in order to further fine-tune and define the most interesting cancers that we will proceed with 284. This will give us greater confirmation of the subtypes of the blood cancers that radar and preliminary lab studies have predicted efficacy for. Additionally, this data will also provide us safety and efficacy in dosing studies, allowing us to move quite rapidly in the 284 program. During this past quarter, results from our studies were accepted at several scientific conferences, including the AACR Pancreatic Cancer Conference, where we presented data from the pancreatic cancer We will be presenting data on the glioblastomas at the Society of Neuro-Oncology conference later on in November. And our 284 data will be presented at ASH early in December.

Thank you, Kishore. Before I open it up to questions, I'd like to provide a brief recap and also discuss some of the anticipated milestones. As you know, we're very confident in the launch of multiple human clinical trials over the next 12 months for 184 and 300 and 100. We're also looking at the ongoing growth of our radar platform, as well as committed to bringing the ADC programs further along through IND enabling studies. We also believe that with our network of strategic collaborators that we'll be adding additional KOLs and collaborators to, that we'll be able to generate positive new data and, more importantly, generate new programs through licensing opportunities, both with radar and also our existing drug portfolio. We believe that 2022... will be a fairly transformational year for Lantern. We do expect that the platform will grow, that the trials will initiate, and most importantly, we'll continue growing our very experienced team that is committed to bringing these drugs and more importantly, doing it faster and cheaper. So with that, I'd like to now open up the call to any questions.

Thank you, Pana. We received some questions from analysts. Our first questions come from Kyle Bowser with Colliers. What are your new goals for Radar in terms of number of data points and what sort of visual demonstrations might we see during the upcoming investor day?

Thank you, Kyle and Kayla from Colliers. Great question. We had set out to reach Initially, when we came into 2021 with 1.2 billion data points, we thought we'd get to five or six by the end of the year. We updated that middle of the year to eight to 10. Now that we're at 10.4, we're thinking next year we'll get to 20, maybe slightly north of that. But we're also looking at new types of data, as I mentioned, and we're also looking at the complexity of our algorithms. That's one of the big areas of focus is the machine learning development environment. So in terms of numbers, I believe we'll be at 20 plus next year and maybe even faster. In terms of the We do have some really exciting visualizations of the output of the platform. We call these radar insights internally. We routinely review these during our team meetings. We expect to have an analyst day. We're trying to figure out the right time and the right kind of environment for that. So sometime in December or January. where we'll showcase many of these radar insights and also a peek at the kind of development environment. So, yeah, we'll have some looks at what radar looks like and feels like, but also in terms of what is the data and what are the nature of algorithms. That's probably the most important thing. So thank you for that question.

Next question. Are you still evaluating new partnerships that you can take equity stakes in? And how is the Act to Lead therapeutic partnership progressing?

Great question. One of the most important reasons for making the 10 billion announcement was to showcase that we continue to develop a platform for much wider use than just our own. And so we think that now is the right time for us to even be more aggressive. We've had very good experience with our first partner, Actuate Therapeutics. It's given us a great template to think about how to approach additional partnerships with both emerging companies. And we've had actually some interactions with some bigger biopharmas. It gives us very good ideas on the process that we need. So part of today's announcement was really to get onto people's radar, so to speak, that we're going to be much more aggressive in seeking radar-driven biopharma collaborations where we can take equity or milestones as part of our growth.

The next question is, how much faster do you anticipate enrolling the phase two trial now that you've inked the collaboration agreement with DeepLens?

That's a great question. I know that David probably won't want me to commit to any number, but I can tell you what we learned in the process, which we believe is a template for what we're trying to do with deep lens. So we spoke to many people in the biopharma industry as part of our reference checks for not only the deep lens technology, but other patient recruitment technologies that sift through patient data. And we found that the People who use the deep lens technology were able to talk about enrollment rates that were two times higher, faster than they expected. So if you imagine an 18 month enrollment, you're looking at nine months, 12 month enrollment, looking at six or seven months. So we're hoping that we can be in that same ballpark. But to be honest, since we're going after probably a group that has less competition, which is the never smokers, I think once people know about it, I think there is a very high likelihood if they meet all the clinical criteria that we can see very good acceleration because of that. Thank you.

Thanks. Our next questions come from Michael King with H.C. Wainwright. What day is Lantern presenting the poster on Ash and what will be the topic?

That's a good question from H.C. Wainwright. Thank you, Michael and Raniero. We're not allowed yet to give the date and title. Is that right, Kishore? That's still under embargo, I think, till the end of this week. So at the end of this week, we'll be lifting that and talking about the presentation. Thank you.

Next question. Any progress on resuming the LP100 clinical trial after the buyback?

Yes, great question. So we have some very good promising data in the 100 trial, not only about the median overall survival improvement that we've seen in the nine patients that were dosed to the LP100, but we also have seen publications now that support the role of LP100 in DNA damage repair pathway deficient tumors like bladder cancer, namely bladder cancer, actually, with ERCC2-3 mutations. We're thinking about some modifications to the trial to allow us to attack both groups of patients. but also to refine and simplify the signature that was used to potentially guide their enrollment. So we're in the process now of doing the modifications, but also now exploring bringing the drug substance in the trial to the U.S. for some of the indications, including in bladder. So we'll have more timing on that, I think, in Q1 of next year.

Last question from H.C. Wainwright. Any progress on the trial for LP 300?

Yeah, so I think we're hoping to submit the protocol and the final manufacturing dossier separately, but after under advisement and because of the manufacturing delays, it's been advised that we submit both together. So we're hoping that over the next 30, 45 days, We'll have clarity on the submission, but we're already gone ahead and beginning to look at clinical trial sites and the types of patients. So really the supply chain issues around manufacturing have really held up the final submission to the FDA. And so I'm hoping that happens during this quarter or early January at the latest.

Thank you. Our next question comes from John Vendor, mostly with Zach's. How will CodeOcean be used to improve the R&D progress?

That's a great question. So CodeOcean is, again, a development environment that containerizes the code, the data and. the environment that you use whether it be r python or something else and it puts it in a secure package and more importantly time stamps what you're doing so if we can go back and we can take a look at who's doing is doing or was doing what whether it be internally or externally people don't have to manage the creation of like pipelines, the instantaneous security that might be required to go from one institution to another. So a lot of these things are simplified. So with collaborators, we expect a pretty significant increase in the efficiency of doing work. Internally, we also expect efficiencies that allow our team to focus more on the code and the analysis and less on the management of the development environment. And so this container type approach, I think, increases one of the most important things that's needed in machine learning, which is reproducibility. Reproducibility can be very challenging to know what the algorithm was, exactly what language it was run on, what the input datas were, what the hyper parameters were or were not, and what was the raw data that was used ultimately. So all that now is handled in an automated fashion. So it reduces the IET burden and staffing burden on us. And it also reduces the expense. So it's an important development internal operations type of collaboration. But we do think it's a competitive advantage. We don't see many of our peers having a sophisticated or as mature as a development environment for machine learning as we as we have.

We will. Thank you. This now concludes our questions and answers session. I will turn the call back to Connor for closing remarks. Connor?

Thank you, Natalia. Thank you for the great questions. So as we mentioned, we're very excited for the outlook for Lantern. We think we'll make significant progress next year and throughout this quarter. We've got a lot of data coming out this quarter at the Society of Neuro-Oncology at ASH with our ATRT program. And we believe that this data and the progress will translate into biopharma deals where we can partner or license our portfolio for several hundred million or billions. And ultimately, that's really the way to generate value for our investors is to take our programs and to partner or sell or license them out. So we look forward to providing further updates as the developments unfold and also to meeting many of you in person in the coming months or in 2022. So thank you all. And with that, I'll turn it over to our host, Nicole, in finance.

This concludes today's earnings call and webinar. We look forward to hosting you on our next corporate webinar, which will be on Thursday, November 18th on World Pancreatic Cancer Day. This webinar will be co-hosted by Drs. Igor Asaturov from Fox Chase Cancer Center and Kishore Bhatia from Lantern Pharma. We will release additional details in a press release later this week. Thank you so much, everyone, for joining and have a great rest of your evening.