Lantern Pharma Inc. (LTRN) Earnings Call Transcript & Summary

Good afternoon, everyone. I'm Nicole Leber with Investor Relations here at Lantern Pharma. And welcome to our second quarter 2023 earnings call. I will be your host for today's call. As a reminder, this call is being recorded. [Operator Instructions] A webcast replay of today's conference call will be available on our website at lanternpharma.com shortly after the call. We issued a press release after the market closed today summarizing our financial results and progress across the company for the second quarter ended June 30, 2023. A copy of this release is available through our website at lanternpharma.com, where you will also find a link to the slides that management will be referencing on today's call. I would like to remind everyone that remarks about future expectations, performance, estimates, 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, including results of clinical trials, and the impact of competition. Additional information concerning factors that would 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, 2022, which is on file with the SEC and available on our website. Forward-looking statements made on this conference call are as of today, August 9, 2023, and Lantern Pharma does not intend to update any of these forward-looking statements to reflect events from circumstances that occur after today unless required by law. The webcast replay of the conference call and webinar will be available on Lantern's website. On today's webcast, we have Lantern Pharma's CEO, Panna Sharma; and CFO, David Margrave. Panna will start things off with an overview of Lantern's strategy and business model and highlight recent achievements in our operations, after which David will discuss our financial results. This will be followed by some concluding comments from Panna and then we'll open up the call for Q&A. I'd now like to turn the call over to Panna Sharma, President and CEO of Lantern Pharma. Panna, please go ahead.

[Audio Gap] To hear about our second quarter results and corporate progress. As you know, this is truly a golden age for AI medicine and it really is just beginning. It's being powered by large-scale, highly available computing power, massive data storage. Additionally, it's being fed by healthcare patients and cancer data, which is more widely available and at increasing levels of quality than ever before. Companies that harness these capabilities in the biotech and tech bio industry and make them core of their business will be long-term leaders that create massive value for patients, for investors and for our industry. Lantern Pharma is among the leaders in this transformation of the pace, risk and cost of oncology drug discovery and development. This transformation has a promise to not only make medicines faster, cheaper and with increased precision for patients, but also to help change the direction of R&D productivity and output in the pharma industry. I'll touch on this critical element later in our call. Our proprietary AI platform RADR continues to have a meaningful growth in its size, scope and capabilities, and is at the center of this paradigm shift towards AI-driven drug development. Just 3 years ago when we went public, we had only 3 drug programs, addressing markets we had estimated to be about $5 billion to $6 billion in potential annual therapy sales. Today, we have over 14 drug programs, many with orphan drug designations and additional commercial protections. We're addressing markets today estimated to be approximately $14-plus billion in annual therapy sales. We also diligently are assessing several additional promising programs and molecular candidates for future development. Our growing pipeline of oncology drug candidates is a real-world demonstration of a rapid AI-driven machine learning-enabled identification and validation of new cancer insights, insights where we can understand and accelerate the focus of specific molecules towards a more targeted and more effective oncology medicine. Importantly, RADR has empowered us to compress the timeline of early-stage drug development so far by impressive 70%, while concurrently achieving about 80% reduction in the costs when benchmarked with traditional drug development in the pharma industry. We think we can continue to improve upon this. With our cutting-edge AI platform, RADR, and also our adoption of leading technologies and innovative approach, we are eliminating the path for the next generation of oncology drug discovery. In the past 2 years, we have successfully developed and launched 11 additional programs, a testament to the agility, efficiency and groundbreaking nature of our approach. On average, these programs are advancing from initial AI insights to first in human clinical trials in just 2.5 years at an average cost of approximately $2 million per program. Some have actually even been below that. These are metrics that are previously unheard in oncology drug discovery. In fact, in a recent study published in Drug Discovery Today and also in Nature, it was reported that nearly half of the 16 largest pharma companies had negative R&D productivity for the last 20 years. And they had spent collectively an average of $6.2 billion per drug approval. The number was slightly less than smaller pharma companies. But these startling figure served as a stark reminder of the traditional model of big pharma R&D is not a sustainable or effective strategy, and it is not the right approach to improve drug pricing or drug availability. With escalating economic and political pressures over drug prices, it's clear that our industry -- especially cancer drug prices, it's clear that our industry needs to rethink its approach fundamentally, and we believe that big pharma will increase adoption of AI and computationally driven approaches to elevate above this current issue. As we have demonstrated, our RADR platform has an impressive predictive accuracy of 88% in identifying which patients are most likely to respond to our drugs -- to respond to drugs in clinical trials. We showcased this in a real-world study presented at ASCO with our collaboration partner, Actuate, for their Phase II trial. This is not only a good technical feat, but really a game changer for patient stratification and selection by reducing the cost of trials and enrolling those patients who can ultimately benefit most from these targeted therapies. By combining our unique cutting-edge AI with robust clinical genomic and drug response data, which we do in our platform, we believe that we have increased our ability to derisk our programs and increase the odds of success by a significant factor. Multiple studies by academics, including ordered by Dr. Jason Parker, who I've quoted before, at University of Toronto and industry analysts, have shown that the use of biomarker signatures can increase the success factor from 5 to 12x in oncology clinical development. This reduction in risk and cost comes also with the compression of the timeline, especially in later-stage trials. So this underscores our technology's immense potential to produce insights that leads the development of targeted cancer therapies. Currently, our AI-driven pipeline consist of 14 drug programs, including those under RADR collaboration and our Phase II clinical trial called Harmonic for lung cancer in never-smokers. Our team's unwavering commitment to harnessing the power of AI for drug discovery has also led to the formation of a partnership with Bielefeld University in Germany to develop the next generation of antibody drug conjugates. These are conjugates that are being designed and advanced with our RADR AI platform. This collaboration has the potential to pave the way for therapies with higher efficacy, a faster development timeline and significantly reduced cost of early-stage development. ADCs are a rapidly growing and excitement treating modality that is still in the early stages of commercial growth. Globally, ADC drug programs are one of the fastest-growing drug development segments and are projected to grow from $4 billion as of last year to over $14 billion by 2027. There are many in specific instances of value creation that we've talked about, but also we've also developed an entirely new company, Starlight Therapeutics, whose sole focus will be on CNS and brain cancers. This demonstrates that Lantern continues to be at the forefront of a transformative and aggressive approach to oncology drug discovery and development. As we continue to accelerate the pace at which we're developing and validating insights -- these insights can lead to meaningful drug assets -- we are well positioned and then partnered these drug assets out with larger companies. At this time -- sorry, at the same time, as David will cover, our CFO, shortly, we have a strong cash position. It's been carefully utilized to make more meaningful progress in a disciplined manner. We believe our approach is the future of developing cancer therapies, where data can be used to accelerate programs, derisk the identification of issues and progress these potentially life-changing medicines. Now let's turn to some of the more specific highlights of our progress during the second quarter. During the second quarter, we received FDA clearance of our IND application for LP-184 and we subsequently activated the initial clinical sites of the program. Now we're also identifying several potential patients for this Phase I basket trial. This basket trial will serve multiple solid tumors and brain cancers, categories that have significant unmet clinical need. We also completed the IND-enabling studies for LP-284. LP-184 and 284 are part of our franchise of synthetically lethal agents. We anticipate submitting the IND to the FDA by the end of August and will set the stage for a first in human Phase I trial for LP-284 in advanced non-Hodgkin's lymphomas in the second half -- actually in Q4 of 2023. Data demonstrating LP-284s in vitro and in vivo anti-tumor potency for mantle cell lymphoma, double hit lymphomas and other non-Hodgkin's lymphomas were published in Oncotarget in the quarter, further supporting the advancement of this potentially powerful therapeutic option for a range of blood cancers. We also dosed additional patients in the Phase II Harmonic clinical trial with LP-300 in non-small cell lung cancer for never-smokers and expanded patient recruitment and enrollment to several additional trial sites. As I mentioned a moment ago also, we entered into a collaboration with Bielefeld University in Germany during the second quarter. This is to develop breakthrough new antibody drug conjugates that we believe will set the stage for a new generation of novel ADCs that offer higher efficacy, faster development timelines, and significantly reduced cost to market. Our intellectual property was also strengthened and furthered in the quarter with the receipt of notice for allowance for a U.S. patent covering the composition of matter totally new drug LP-284, extending commercial protection for this asset into early 2039. We also, during the quarter, filed 5 new patent applications for LP-184 and 284 that cover the use of these drug candidates in combination regimens and also specific tumor subtypes where we think the potential is highest for these drugs. Very importantly, we continued fiscal discipline with our cash, we have a balance of $48 million in cash, cash equivalents and marketable securities at the end of the second quarter, which provides us a strong cash runway into 2025. I'll now turn the call over to our CFO, David Margrave, who will provide an overview of the second quarter financial results, and then I'll come back with additional comments on our programs. David?

Thank you, Panna, and good afternoon, everyone. I'll now share some financial highlights from our second quarter ended June 30, 2023. Our general and administrative expenses were approximately $1.6 million for the second quarter of 2023, up slightly from approximately $1.4 million in the prior year period. R&D expenses were approximately $3.6 million for the second quarter of 2023, up from approximately $3.0 million in the second quarter of 2022. Our increased R&D expenses were in line with expectations and primarily driven by increases in research studies and R&D-related payroll and compensation expenses, which were partially offset by a decrease in product candidate manufacturing expenses. We recorded a net loss of approximately $4.7 million for the second quarter of 2023 or $0.44 per share compared to a net loss of approximately $4.5 million or $0.41 per share for the second quarter of 2020. Our loss from operations in the second quarter of 2023 was partially offset by interest income and other income net, totaling approximately $444,000. Our interest income and other income net increased by an aggregate of approximately $541,000 for the second quarter of 2023 compared to the second quarter of 2022. This increase was attributable to an increase in interest of approximately $63,000, increases in dividend income of approximately $168,000, an increase in unrealized gains on investments of approximately $150,000, and an increase of approximately $109,000 in research and development tax incentives related to our Australia subsidiary. As of June 30, 2023, we had approximately 10.86 million shares of common stock outstanding and outstanding warrants to purchase approximately 177,998 shares and outstanding options to purchase approximately 1.1 million shares. These warrants and options, combined with our outstanding shares of common stock, give us a total fully diluted shares outstanding of approximately 12.1 million shares as of June 30, 2023. Our cash position, which includes cash equivalents and marketable securities, was approximately $48.0 million as of June 30, 2023, and we expect this balance 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. Our team continues to be very productive under a hybrid operating model. This hybrid model also removes geographic restrictions to our hiring initiatives, which has given us the ability to recruit extremely high-caliber team members that otherwise might not have been available. We currently have 22 employees focused primarily on leading and advancing our research and drug development efforts. We see this number expanding slightly in coming quarters as we add additional experience -- additional experienced and talented individuals to help advance our mission. I'll now turn the call back to Panna for an update on some of our development programs. Panna?

Thank you, David. As many of you know, we received FDA clearance for our IND application for LP-184 in June and have already activated the initial clinical trial sites for our Phase I basket trial. The clearance of the IND application was a significant milestone for our LP-184 program validating our approach of leveraging AI and machine learning to advance our pipeline of novel drug candidates. Insights from our AI platform RADR were instrumental in our development of LP-184 and aided in discovering its mechanism of action, identifying and prioritizing the ideal cancer subtypes to pursue and generating biomarker signatures that we can use in future clinical trials to help us with patient stratification and selection. We developed these signatures literally sometimes in weeks or months, a process that normally would have taken half a year to 18 months. We believe that LP-184 has blockbuster potential for patients with multiple types of advanced solid tumors and CNS cancers, many of which have no or limited effective therapeutic options. We're more excited today about the opportunity for this drug than even 2 or 3 years ago. Globally, the aggregate annual market potential for LP-184 is estimated to be over $10 billion, consisting of about $5 billion in solid tumors and another $5 billion to $6 billion for CNS cancers, both primary and those arising as a result of metastasis. LP-184 is the first of our drug candidates to be developed entirely internally and with significant use of our AI platform to uncover the subtypes where we believe we can meet highly underserved needs or in areas where there's no therapeutic options. This molecule has been advanced now to a first in human face Phase I basket trial and the trial is designed to evaluate 35 patients, and will assess the safety and tolerability of escalating doses using a buoyant design. We also believe that we have seen exceptional results in cancers that have DNA damage response deficiencies, and that will be also an additional target for later phases of the trial. The initial trial sites have been open and we are actively screening patients for dosing with LP-184. We anticipate completing the trial sometime in 2024. Another very promising new molecule is one that we developed from whiteboard to a first in human clinical trial in under 2.5 years and with an estimated cost of under $3 million. This drug was not even on our pipeline when we went public. It's a very exciting molecule. The initial insights around the specific mechanism of synthetic vitality we derived from large-scale comparative data using our RADR AI platform. We then leverage our GMP manufacturing process for it sister molecule LP-184 to efficiently ramp up and develop 284 while continuing to refine the implications and mechanisms. Ultimately, these studies also led to an orphan designation in mantle cell lymphoma. Today, we are preparing for our first in human clinical Phase I trial, which we expect to launch in the fourth quarter of this year. As I mentioned earlier, with IND enabling studies now complete, we anticipate submitting the IND to the FDA by the end of this month. And we also have already received orphan drug designation in mantle cell lymphoma. The market, we believe, for this mantle cell and double hit lymphoma -- these are very aggressive non-Hodgkin lymphoma subtypes -- is currently about $1.2 billion in the U.S. and Europe, and we think that the number globally is about 2 to 2.5x that number. LP-184 and 284 represent our synthetic lethality franchise, which has shown significant potency in a wide range of cancers, both as monotherapy and also in combination with other agents. LP-184 has selective preference for solid tumors that have high levels of PTGR1 expression or deficiencies in the DNA repair pathways, while LP-284 has shown [ code ] efficacy in a wide range of hematologic malignancies, namely non-Hodgkin's lymphomas. And we also have seen the LP-284 shows ability to effectively regress mantle cell lymphoma xenografts after they become refractory to both ibrutinib and bortezomib. Both drug candidates have also shown promising activity in a range of pediatric tumors, which will be pursued in the research centers focusing on children's cancers such as University of Texas Health and Greehey Children's. And we believe that those will be into Phase I trials once the dosing and safety have been established from LP-184 and 284 early trials. We also know that LP-284 has demonstrated a significant impact on a wide range of sarcomas, including Ewing sarcoma and rhabdomyosarcoma, both pediatric cancers largely. Additionally, LP-184 was granted a rare pediatric disease designation in ATRT, atypical teratoid/rhabdoid tumors, an ultra-rare cancer which has no approved standard-of-care agents and largely reflects children under the age of 5. We published with the National Cancer Institute, pretty unique publication, where we uncovered the mechanism of pointing this drug toward these products in modeling deficient tumors, namely looking at SMARCB1. We plan on reporting on more details from these studies and the potential emerging indications later this year. Now moving on to our Phase II clinical trial of LP-300. Initial patients in our Phase II Harmonic trial of LP-300 for never-smokers in non-small cell lung cancer have been dosed, and we have 5 additional active trial sites that we're adding. We expect to add additional trial sites throughout this quarter and also multiple patients. We're also screening and increasing the -- we're also increasing the number of patients we are screening. This comes as a direct result of increased awareness among patient advocacy groups, greater investigator interactions and briefings. Additionally, Dr. Joseph Treat of Fox Chase Cancer Center has been appointed as lead principal investigator for the Harmonic study. Dr. Treat brings with him a stellar focus and background of serving not only the lung cancer community, but also a background in clinical trials in the never-smoker population. He was recently leading 100-plus patient Phase II interventional trial focused on never-smokers in Stage 4 disease who had never smoked but irrespective of their driver mutation status. So it's an ideal backdrop and an experience and also the clinical network for the Harmonic trial. And we welcome his active leadership in Harmonic and with Lantern. We're also exploring the potential to expand the Harmonic trial into Asia, specifically countries that have a higher incidence and never-smokers in lung cancer patients. Overall, we anticipate enrollment of this 2-arm open-label randomized trial, which is targeting 90 patients, should last between 14 and 18 months. The Phase II trial is designed to investigate LP-300 in combination with standard of care chemotherapy with the key measured endpoints being overall survival and progression-free survival. In a previous multicentered Phase III clinical trial, what we saw was a subset of never-smokers in non-small cell lung cancer that received LP-300 with chemotherapy showed a significant increase in overall 2-year survival, overall survival of 91% increase in the never-smoker population that were given LP-300 and 125% increase in progression-free survival in that same group of never-smokers versus the standard of care of the chemo doubling. I discussed also earlier our exciting collaboration with Bielefeld University to develop breakthrough antibody drug conjugates. This partnership signifies an exciting stride forward in the development of next-generation ADCs using our RADR AI platform. The initial focus of the collaboration is to synthesize and evaluate novel ADCs like the cryptophycins. This is a promising class of anti-tumor molecule due to their potency of ultra-low picomolar concentrations. We believe we can attach several of these molecules to the ADCs to the antibody of interest using a fairly unique linker strategy. The cryptophycin-based ADCs would undergo rigorous testing across multiple cancer cell lines, both in vitro and in vivo models, and we anticipate sharing initial results in the coming months. We also plan to leverage our ADC development module that has been fully integrated now into RADR to launch multiple ADC opportunities through Lantern and also through our partners and also through our cryptophycin based collaboration with the magic with University of Bielefeld. We believe the ADCs are a very promising treatment modality with significant opportunities for partnership and also to license with larger pharma companies. Our AI-guided strategy holds immense potential to derisk the ADC development process while simultaneously enhancing the creation of effective and targeted ADCs. Given the rapidly growing global ADC market currently valued at over $4 billion but is projected to reach $14 billion in the course of the next several years by 2027, we're eager to expand our footprint in this important and burgeoning space. Under the terms of our collaboration, the team at Bielefeld University under the leadership of Dr. Sewald will synthesize, optimize and provide initial testing of the cryptophycin-linked ADC, and Lantern has exclusive worldwide option to license intellectual property from this collaboration from Bielefeld University and this IP will be generally -- this includes IP generally directed from our joint efforts. We anticipate sharing the results of this work probably during the fourth quarter. Leveraging more than 34 -- we're now up to 34 billion data points, oncology-focused data points, and we are on pace now to surpass 50 billion data points by year-end. Our RADR platform excels an automated large-scale biological analysis and response network analysis, yielding core relations that can be leveraged both for target identification, drug response prediction and tumors and patient selection. But it's not just about the quality of data, our RADR platform also continues to evolve in terms of its capabilities. During the second quarter, we launched some pretty unique groundbreaking predictive models that enable us to assess blood-brain barrier permeability of any compound. We can do this for tens of thousands of compounds a day now. The capability is crucial for developing therapies, targeting neurological disorders where processing the blood-brain barrier is often challenging. By accurately predicting the permeability and availability of that compound, we can optimize the design and delivery of potential treatments, and more importantly save massive amounts of time and money that are involved in targeting and understanding blood-brain barrier permeability in early-stage development. Furthermore, our platform's predictive power now extends to patient response and combination usage for immune checkpoint inhibitors. We'll talk about -- more about later this quarter. But the immune checkpoint module now harnesses the power of the AI and machine learning modules, and now RADR can analyze vast amounts of data to predict how patients may or may not respond to these inhibitors, and this data includes both antigen data, proteomic data, mutation data, and RNA data. And this allows us also to identify potential combinations for a more personalized treatment strategies, but also very importantly for larger pharmas to actually manage the downstream long-term value of their investments into these immune checkpoint inhibitors. And as I already discussed, we also made significant strides for designing the templates for next-generation ADCs using our ADC module, and we think this has the potential to revolutionize the ways ADCs are created and have better high-potency therapeutic payloads while minimizing damage to healthy tissue and systems. So RADR continues to advance its capabilities, both in size and scope, but also in functionality. And we believe that this will secure -- continue to secure Lantern's position at the forefront of leading-edge AI-based drug discovery and personalized cancer therapy development. So 2023 is shaping, it being a pivotal year for Lantern, where our insights are now entering to patients and have started their journey to becoming meaningful therapies in cancer, and at the same time increasing the functionality of our AI platform. Our collective efforts and dedication of fostering transformational shift for our company, setting us on an exciting trajectory towards the future, where we're touching and improving the lives potentially of cancer patients with effective and hopefully more precise therapies. One of our primary focus during the second half of this year will be to further advance enrollment in Harmonic. It will be also to advance the enrollment for our Phase I trial LP-184, we've opened up -- where we've opened up the initial sites and we're actively screening patients today. We also expect our Phase I trial for LP-284 to launch in the coming months, most likely in Q4 of 2023. These trials marked significant milestones in the pursuit -- marks significant milestones in our pursuit of advancing AI-powered drug discovery into the clinic. Additionally, we plan on progressing LP-184 known as STAR-001 towards Phase I/II clinical trials in CNS and brain cancer under Starlight Therapeutics, and we think this underscores our commitment to addressing unmet needs in a focused manner. And we think this is a massive upside for our investors and our patients through Starlight. So in our portfolio side, we believe that our AI platform will reach over 50 billion data points, and will further progress the key modules for immune checkpoint inhibitors and for ADC development. These milestones have set a new standard for data-driven drug discovery, but also established new RADR-based collaborations with companies and with research partners. We also intend to actively explore licensing and partnership opportunities with biopharma companies to accelerate the path to patients for our therapies and to showcase how our AI-driven approach can generate results for investors and drive the future of our franchise. While we ambitiously drive forward our R&D efforts, we'll continue to uphold disciplined fiscal management to create further value for our shareholders. As we have pointed out, we are accelerating the pace at which we are developing and validating insights, but we're also at the same time managing our cash and managing how we position these assets for partnering with larger companies. As we continue to advance our diverse portfolio, we'll be presenting new data and findings in very important several notable scientific conferences over the coming months. We have one coming up on August 10 at the Society of Neuro-Oncology and the American Society of Clinical Oncology, the CNS Cancer Conference in San Francisco where we will share findings related to LP-184's ability to inhibit adult and pediatric CNS tumor cell growth and especially in new data related to ATRT. We also will be at the international conference on Drug Conjugates for Directed Therapy in Darmstadt, Germany on August 24, where our Chief Scientific Officer, Kishor Bhatia, will be presenting new details about our innovative AI-driven approach to identifying ADC targets with improved tumor selectivity. And in fact, we will be showcasing kind of our whole tumor selectivity in antibody drug modules there. We'll also present at the Society of Hematologic Oncology's Annual Meeting in Houston, Texas on September 6, where we'll be sharing new research related to LP-284 and its ability to target genetic deficiencies in non-Hodgkin's lymphoma. So, we have a lot of exciting scientific and clinical data that will be presented over the coming months, which will set the groundwork for even more improved opportunities for Lantern Pharma. In closing, I want to really express my gratitude to our team, our partners, our collaborators, and also our investors and stakeholders for their unwavering support and dedication to helping us transform the oncology development process. I think together, we're lighting the way towards a brighter future in oncology drug development and solving real-world problems with unique proprietary AI solutions that allow us to develop these precision oncology therapies at significantly reduced costs and timelines that have been unheard of. We think this places Lantern at the forefront of a new era of, as I said, a golden age of medicine in -- due to AI. With that, now I'd like to open up the call to any questions or for clarifications. But also I'd like to take a moment to personally thank our colleague, Dr. Drew Sturtevant, who has been focused on our communication efforts, both for the press and scientific community, for helping in our last 5 earnings calls. I know the team will miss his involvement and his upbeat dedication to Lantern, but we wish him well in his new scientific endeavors. So again, let's take questions from our audience.

[Operator Instructions] We already have a couple of questions coming in here. The first one is, has the first stage of the Harmonic trial been enrolled yet and will Lantern report on the first stage of the trial before completion of the full study?

Great question. I think it's from John. But yes, we're in the middle of the first stage of the trial. We will report our results as they get reviewed and -- but we'd expect to report out the first stage, yes.

Another one here from an analyst. How will the genomic and transcriptomic data collected in the Harmonic trial help guide the second stage and potentially a registrational trial?

Yes, for that question I think from John also, we can pivot into a registrational trial from those trial designs. So we expect to get both mutational and transcriptomic data from liquid biopsies that we're taking, and we'll be able to see -- I think we'll see some differences in response based on the prior TKI or the prior therapy of these patients. And so we can probably tune in to some specifics based on the data that we get from the liquid biopsy data. And that could actually pave the way for a number of really unique things that we already have seen in silico. we've seen that PD-L1 high does not respond well potentially to these types of therapies. So we could actually go after something that's maybe even PD-L1 low. We could go after signatures that showcase certain types of signatures that correlate to a never-smoker signature plus high response to resetting redox cycle-plus response to a chemotherapy reset. So yes, there's a couple of ideas. But again, once we have the patient data from the LBX, we can design a signature that we can use potentially for a registrational event and big pharma like signatures, right? If they don't pay for signatures and they can get machine learning-derived signatures that makes the asset always more attractive. Thank you. I think Tony has a question, is that right?

Yes, Tony has your hand raised. You should now be able to speak. Can you hear us?

Yes. Can you hear me?

Yes.

A couple of questions. One is related to Harmonic and you alluded to it just a minute ago. But first, let me ask in the previous data, the previous Phase III trial, at least -- I'm not going to put a percentage on it, but certainly a good bit of the data responding to LP-300 was really driven by females. And so the question is, what's novel and clearly less driven -- substantially less driven by males? What do you think biologically is going on between genders in this study? That's question 1. Question 2 is, this is really related to checkpoints, but in particular, pembro. And do you have any preclinical data that actually tells you regardless of PD-L1 high or low that the combination actually could work better in these particular types of patients. So that's really related to Harmonic. I'll come back and ask my second question in the end because it's very, very different than the first.

Thanks, Tony. So in regards to the ratio, I don't think -- the trial really represents the ratio of females to male in the real world. It's about 2/3 to 1/3 of the never-smoker population that comes down with non-small cell lung cancer, carcinoma, is 2/3 of them, roughly 60% to 66%, are female. So there's no magic or reason why females quite is over indexed. It's just that's the actual disease epidemiology. And that's pretty consistent across races and continents, that tends to skew more females get -- more females get some of these TKI-driver imitations in some cases or more females -- it's supposedly some research has shown that females also can have lung cancer arise as a result of metabolism of estrogen that collects the linings of the lines, and that's cancerous. So obviously that's also something that's been observed. But no, I expect our trial to be the same, it'll be more females than males. Right now, it's not -- we don't have enough patients to show, but I do expect that to be -- if I look at the screening data, it also is more females than males. I don't know the biology of that. I don't know if that's something that we need to worry about. But if you look at the response, the response both in males and females was similar. It was slightly better in some females. But even if you take out male or female, you saw nearly 90% to 91% increase in overall survival in the never-smoker population and doubling in the progression-free survival regardless of the gender.

And the pembro combo thoughts as it relates to regardless of whether or not it's PD-L1 high, is there any preclinical data that you're aware of that get support that, that actually may be a good place to have a cohort of patients?

You mean PD-L1 low.

Yes, it doesn't matter. And what I'm suggesting is what the data are telling you would be that may be different, but the combination may actually -- it could be irrelevant to whether it's PD-L1 low or high. That's what I'm alluding to. Do you have any information that says that's the case?

No, we do not have information. We just know that never-smokers tend to have PD-L1 low in almost all instances. So PD-L1 high tends to be really indexed for people who have what's called heavy tumor mutation burden, which is what drives the PD-L1 expression. So people with high tumor mutation burden tend to be smokers, 90%-plus of them. And so we know that when tumor mutation burden is high, it's less likely to respond to 300 and to chemo doublets. And so we know that this population of never-smokers tend to have, in general, PD-L1 low. And that's been seen in a lot of studies where they've looked at never-smokers or they looked at characteristics of PD-L1 or low or low tumor mutation burden. I can send you some of those studies that were done. The most interesting one was like a meta study done out of Taiwan that was just published, I believe, last year. I circulated that internally. And it looked at like 6 different cohorts, looked at both proteomic and genomic analysis of PD-L1 high-low, TMB high-low, smoking status, et cetera, and I can send that to you. But we don't have -- it's a conjecture. We think PD-L1 low is probably going to be shared with most of these never-smokers. We also know anecdotally that PD-L1 low keeps these patients oftentimes from getting pembro plus chemo in the first-line setting and sometimes they'll just skip chemo and sometimes if they do hardware TKI but the right to a TKI.

And so there's no thought around perhaps using a cohort of patients to actually test the combination?

Which combination?

Pembro plus 300?

We do not have an arm currently designed for pembro plus 300. I think right now, our thinking is the best potential design that we have been thinking about is a TKI plus 300. We think it could enhance the TKI's long-term impact because we're denaturing some of those TKIs that could be an added bonus for a TKI of an EGFR ALK based TKI where we have actual crystallography data to showcase that we are denaturing the receptors. And so that can give an added boost potentially. We've seen some synergistic effect in preclinical studies of TKIs plus 300. But, again, a lot of these people will stop responding to TKIs. So our feedback from KOLs and clinicians was that they were not that excited to put them on to TKI plus 300, but would rather see a chemo plus 300 because that's standard of care as they go to chemo doublet after failing to respond to TKIs.

The second question really is around the larger picture here from AI discovery and the RADR platform -- not so much the RADR platform, but just higher level. When we look across the landscape at other companies that have AI as a premise to their discovery engine, be it Calco or say Insitro or even BioAge, just randomly naming 3, I'm just not aware that they've been able to move any program forward. And I don't think it's not for the computing power. Maybe it's a lack of biology or directionally where they may wish to go. But do you have any view about that?

Yes, there are so many love there are examples, like you said, like companies that are more, I would say, AI only or AI first, and they haven't seen the same movement. So it's not easy, right, even if you have an AI answer, you start to manufacture the molecule as under GMP, you still have to have some really exquisite or preclinical studies to really isolate that mechanism or insight that you've garnered on the computer. You have to get KOLs excited, you have to write the IND and do the animal study. So there's a lot of work. I mean, it's not a fact that we did this with 284 which is a molecule that didn't even exist when we went public 3 years ago to now about to launch into a trial. I mean that's like a -- and again, with total cost of less than $2.5 million. So it's a challenge. I think there are companies that are in trials though, I mean so not just Lantern but other companies like Recursion that are in trials, companies like Exscientia that are in trials. They are larger companies significantly than ours by a factor of like 20 burning $50 million, $60 million, $70 million. But the benefit of AI is really to reduce the time and cost, but there's still -- you need biology and manufacture knowledge and CMC to then really advance it into humans. So we kind of really built Lantern to being a really fit for purpose in oncology. And that's why we have a focused team and we work with a lot of KOLs and outside experts. So everyone at Lantern believes in a multidisciplinary approach. So whether it be our CSO or even our data scientists, they're not just data people. They also understand cancer and even the cancer biologists really try to understand the data science. And so it's a -- we're kind of fit for purpose specifically in oncology. A lot of the larger companies are going after lots of disease states and I think that kind of focus or lack of focus can keep them from advancing into human trials as quickly as we have.

Thank you, Tony. And that's all the time we have for questions today. Thank you so much for tuning in and we hope you have a great rest of your day.