Good afternoon, everyone. I’m Nicole Leber with Investor Relations here at Lantern Pharma. 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 and all attendees are in a listen-only mode. We will open up the call for all questions and answers after our management’s presentation. 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 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 could cause actual results to differ materially from those in the forward-looking statements can be found in our Annual Report on Form 10-K for the year ended December 31, 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 Margave. 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.

[Indiscernible] to hear about our second quarter results and corporate progress. As we know, this is truly a golden age for AI in 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 patient 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 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 three years ago when we went public, we had only three 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 the rapid AI driven, machine learning enabled identification and validation of new cancer…

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 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 I’ve already activated the initial clinical trial sites for our Phase 1 basket trial. The clearance for 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 within 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’ve 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 two and three 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 Phase 1 basket trial, and the trial is designed to evaluate 35 patients and will assess the safety and tolerability…

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

Great question. I think that’s from John, but yes, we’re in the middle of the first stage of the trial. We will report out results as they get reviewed and -- but we’d expect to report out the first stage. Yes. Thank you.

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. I think -- yes, for that question, I think from John also we can pivot into a registrational trial from this trial design. 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’ve 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 the 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 [ph], we can design a signature that we can use potentially for a registrational event. And big pharma likes signatures, right, if they don’t have to 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, I see your hand raised. You should now be able to speak. Can you hear us?

Yes. Can you hear me?

Yes.

Yes.

Yes. Thanks very much. Panna, thanks a bunch for the opportunity. 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 3 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 one. Question two 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.

Thanks, Tony. So in regards to the ratio, I don’t think the trial really represents the ratio of female to male in the real world. It’s about two-thirds to one-third of the never smoker population that comes down with non-small cell lung cancer. Adenocarcinoma is two-thirds of them roughly 60% to 66% are female. So there’s no magic or reason why females, what is over index, it’s just that’s the actual disease epidemiology. And that’s pretty consistent across races and continents. It tends to skew more females get -- more females get some of these TKI driver mutations 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 lining of the lungs, and that’s cancerous. So that 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. I -- 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, I’d 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.

Yes. 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 are aware of that could 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. I’m -- 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 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 tends to have in general PD-L1 low. That’s been seen in a lot of studies where they’ve looked at never smokers or they’ve looked at characteristics of PD-L1 low or a low tumor mutation burden. I can send you some of those studies that was -- 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 six different cohorts and 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 -- we -- its 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 get chemo and sometimes they’ll -- if they do harbor at TKI, they’ll go 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 in that we have been thinking about is and a TKI plus 300. We think it could enhance the TKIs long-term impact because we’re denaturing some of those TKIs. So it could be an added bonus for a TKI like an EGFR, an ALK based TKI, where we have X-ray 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 a TKI plus 300, but would rather see chemo plus 300, because that’s standard of care as they go to chemo doublet after failing to respond to TKIs.

bio age:

Yes. From [indiscernible] there are examples, like you said, that a lot of 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 still have to manufacture the molecule as under GMP. You still have to have some really exquisite preclinical studies to really isolate that mechanism or insight that you garnered on the computer. You have to get KOLs excited. You have to write the IND and do the animal studies. So there’s a lot of work. I mean, we’re -- it’s not a fact that, we did this with LP-284, which is a molecule that didn’t even exist when we went public, three years ago to now we’re about to launch into a trial. I mean, that’s like a -- and again, the 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 there are companies like Recursion that are in trials companies like Axantia [ph] that are in trials. They are larger companies significantly than ours by a factor of like $20 million, 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. And so we’ve kind of really built Lantern to being a really fit for purpose in oncology, and that’s why we have a focused team, we work with a lot of KOLs and outside experts. So everyone at Lantern believes in a multi-disciplinary 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.

I appreciate that very thoughtful response.

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.