Earnings Call Transcript - LTRN Q2 2020

Operator, Operator

Good day, and welcome to Lantern Pharma's Second Quarter 2020 Earnings Conference Call. I would now like to introduce your host for the conference call, Director of Investor Relations at Lantern Pharma, Marek Ciszewski. Please go ahead.

Marek Ciszewski, Director of Investor Relations

Thank you, Ashley, and thank you all for joining us for Lantern Pharma's Second Quarter 2020 Conference Call, our first as a publicly traded company. Our Q2 financial results and earnings press release was issued this morning and can be downloaded or viewed from the Investors section of our website. Also on this page, you will be able to find a slide deck with other financial and operational highlights that will be discussed on today's call. On the call today are Panna Sharma, Lantern's President and CEO; and David Margrave, Lantern's CFO. Following the safe harbor statement, Panna will provide an overview of our business, after which David will share our quarterly financial results. Panna will then offer concluding comments, after which we will open this call for questions. I would also like to remind everyone that our management will be making remarks and statements about future expectations, plans and prospects that constitute forward-looking statements for purposes of the 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 their actual results to differ materially from those indicated, including risks described in the company's filings with the SEC. These will include statements related to the potential advantages and development plans of our AI platform, our strategic plans, and plans to advance our collaborative and internal drug development programs, risk related to the COVID-19 pandemic, our expectations related to the use of our cash and cash equivalents, as well as our future operating expenses. These forward-looking statements reflect our current views about our plans, intentions, expectations, strategies and prospects, which are based on the information currently available to us and on assumptions we have made. Actual results may differ materially from those described in the forward-looking statements and are subject to a variety of assumptions, uncertainties, risks and factors that are beyond our control, including those risks detailed under the caption Risk Factors and Elsewhere in our most recent SEC filings and reports. Any forward-looking statements made on this conference call speak only as of today's date, Thursday, July 30, 2020, and Lantern Pharma does not intend to update any of these forward-looking statements to reflect events or circumstances that occur after today. A webcast replay of the conference call will be available on Lantern Pharma's website at lanternpharma.com. With that, I'd like to turn the call over to President and CEO, Panna Sharma. Please go ahead, Panna.

Panna Sharma, President and CEO

Thank you, Marek, and good morning everyone. I appreciate you joining us for our first quarterly call as a publicly traded company. I want to express my gratitude to our frontline service workers, essential staff, and those in our health care systems, especially during this challenging time with COVID-19 cases surpassing 15 million globally. I am confident that we will work together to address COVID-19 and the broader issues it has intensified in our economy and society. Today, we are on the brink of a golden age of artificial intelligence, where advancements in data availability, computing power, and investor demands converge to enable innovative approaches to complex problems across industries. Drug development, particularly in oncology, is just beginning to harness this potential, and we believe it can significantly increase productivity while reducing costs and risks. At Lantern, we are pioneering the application of AI in targeted oncology drug development, which we believe will ultimately yield better outcomes for cancer patients worldwide. Our business model centers on using AI to enhance drug rescues and development, with three candidates currently in our portfolio. We are also actively discovering new drug candidates that can be further pursued through our data-driven strategies. Our RADR engine plays a vital role in generating robust biomarker signatures that assist in selecting the right patients for our therapies, both in clinical trials and as future commercial diagnostics. Combining our AI capabilities with the extensive experience of our leadership team, which has an average of over 15 years solely focused on oncology, positions us well to revolutionize cancer drug development. Following our IPO on June 15, where we raised $26.3 million, we announced that our RADR platform exceeded 450 million data points—six months ahead of schedule. We have since surpassed 500 million and expect to reach 1 billion data points soon, aiming for over 3 billion based on our current trajectory. This data is tailored specifically for oncology drug development and comes from numerous sources. Since I joined nearly two years ago, our platform has grown from about 10 million data points covering a few drug classes to a comprehensive dataset spanning over 144 drug-tumor interactions involving over 95% of approved oncology compounds. Our team is dedicated to collaborating with experienced industry partners to refine our AI models and validate our approaches. Our goal is to add an oncology development program each year through partnerships, collaborations, or in-licensing. This methodical approach to identifying and developing new therapies can create substantial value for investors while maximizing our AI platform's potential. Currently, we have active development programs across four compounds. The first, LP-100, is in a Phase II trial guided by a genomic signature in a prostate cancer trial. We anticipate reporting results from this trial in the first half of 2021. The second candidate, LP-300, is gearing up for a Phase II trial targeting non-small cell lung cancer in never-smokers, a group that has seen a rising incidence of the disease. Our aim is to better understand the genomics of this population to improve patient outcomes. Our third candidate, LP-184, is being developed in two programs, focusing on specific genomic profiles in solid tumors and CNS cancers. We believe this drug could significantly benefit patients with glioblastoma, as many currently do not respond to standard treatment. We plan to conduct preclinical studies and launch IND-enabling studies in 2021, expecting to initiate a Phase I/II trial in 2022. The market potential for LP-100, LP-300, and LP-184 could be several billion dollars annually in top medicine markets. As we advance our studies, we will keep investors informed about our progress and developments. With our IPO completed, we are also expanding our AI, data science, and development teams while focusing on leveraging partnerships with high-quality labs and service providers. These partnerships are crucial for our growth strategy, and we will update investors on their contributions to our mission of providing effective cancer treatments to patients faster and more cost-effectively. By integrating our current drug candidates with the RADR AI platform, Lantern is positioned to achieve multiple milestones that will enhance shareholder value while exploring exciting opportunities for new compound developments. Now, I will hand the call over to our CFO, David Margrave, to review our second-quarter results. David?

David Margrave, CFO

Thank you, Panna, and good morning, everyone. I'd like to welcome all of those that are new to Lantern as investors and also welcome our pre-IPO investors that are listening in to our progress. The second quarter of 2020 was our first quarter as a public company, although the time we were public during the quarter was only for the last 2 weeks. Please bear in mind that we'll be making comparisons year-over-year to the second quarter of 2019, during which time we were still a private company. During the second quarter of 2020, we reported a net loss of $833,422 versus a net loss of $629,393 in the second quarter of 2019. General and administrative expenses during the quarter increased $408,279 from $268,120 for the 3 months ended June 30, 2019, to $676,399 for the 3 months ended June 30, 2020. The increase was primarily attributable to increases in labor expense and costs associated with transitioning to and becoming a public company. Research and development expenses decreased $204,250 or 57% from $361,273 for the 3 months ended June 30, 2019, to $157,023 for the 3 months ended June 30, 2020. The decrease was primarily attributable to reductions in product candidate manufacturing-related expenses, reflecting completion of process development and scale-up studies conducted in the prior year period. We expect that our research and development expenses will increase as we plan for and commence our clinical trials of LP-300 and LP-184, and as we develop our AI and our cancer biology teams. As of June 30, 2020, we had cash of approximately $23.8 million, driven by the net proceeds of our IPO that closed on June 15, 2020. We issued 1.75 million shares at the IPO at a price of $15 per share. And after underwriting discounts, commissions and other expenses, Lantern netted 23.4 million in proceeds from the IPO. In regards to some of the key housekeeping items about Lantern Pharma, we currently have 7,370,199 shares outstanding on a fully diluted basis inclusive of warrants and options. Included in that total are warrants outstanding to purchase 332,014 shares of common stock, the majority of which are from historical financings as a private company and options outstanding to purchase 820,608 shares of common stock that have been issued to company employees, management and directors. Currently, we have 10 employees distributed across multiple disciplines, including data science and AI, drug discovery and clinical development and finance and administrative. I look forward to your questions and to providing you information on how we are managing our business and financials as we grow our impact on personalizing cancer treatment and transforming the paradigm of drug development. I'll now hand the call back to Panna.

Panna Sharma, President and CEO

Thank you, David. I think it would be valuable to discuss our future plans concerning our platform and portfolio to provide context for investors, particularly before we transition to Q&A. To summarize, we believe our core business model is scalable across many more compounds, and the RADR platform is a foundational element on which our franchise's value can continue to grow. We are concentrating on several multibillion-dollar therapeutic opportunities in oncology and will maintain our focus on cancer. We have developed RADR and are continually refining it as our data sets grow in wealth and quality. We believe our platform's capability is unique. RADR has been developed and improved over the past few years and now integrates over 0.5 billion data points from more than 145 drug classes that are directly relevant for oncology drug development and patient response prediction. We are currently utilizing advanced convolutional and artificial neural network technology, along with AI and proprietary machine learning algorithms, to determine the best paths for development and disease prediction. By identifying clinical candidates alongside relevant genomic and phenotypic data, we believe our approach will aid in designing more efficient preclinical studies and more targeted clinical trials, thereby speeding up our drug candidates' time to approval and ultimately to patients. We think this data-driven, targeted approach can lower the cost and time involved in bringing oncology drug candidates to specific patient groups. Looking ahead, there are four key areas that we believe will likely generate lasting value for shareholders. First, our AI platform. RADR is unique, timely, and an industry-defining asset that continues to grow rapidly. We aim for this platform to become the largest AI-enabled oncology drug development platform. Second, our existing portfolio of therapies. Our three compounds are at various stages of active clinical development in areas that represent multibillion-dollar global therapy sales, many of which currently lack adequate therapeutic options. Third, future drug development initiatives. As mentioned earlier, we are uncovering meaningful and targeted insights into where rescue and accelerated development efforts should be applied to certain failed or stalled compounds, and we believe we can in-license and explore at least one additional opportunity per year. Fourth, our potential for future collaborations with pharmaceutical and biotech partners. Since going public, we have seen heightened interest from pharma and biotech regarding our approach, and we now have a more robust team and infrastructure to pursue many of these joint initiatives. If we can finalize collaborations with other companies, it could lead to significant additional financial resources and potential upsides in milestones and economic rights to more drug programs. As I mentioned at the start of this call, we believe we are at the beginning of a golden age for AI in drug development. Entire industries will be transformed at varying rates, all shaped by a data-driven approach, near-time analytics, and a significant compression of the traditional value creation cycle. This presents an opportunity to create substantial new value for oncology patients and the healthcare system, as well as for those who invest and engage in these efforts. With that, I would like to open the call for questions. Ashley, could you please open the line for questions?

Operator, Operator

We will now take our first question from Kyle Bauser with Colliers Securities.

Kyle Bauser, Analyst

Maybe I'll just start off with the orphan drug designation for LP-300. I think you already submitted that. Can you just remind us when that took place and kind of when you expect to get an answer and hear back from them?

Panna Sharma, President and CEO

We have applied for orphan drug designation for LP-300 in the never-smoker population. We currently do not have a timeline. We are actively communicating with the orphan designation group regarding our approach and how the never-smoker category can be defined as a targeted population. While we do not have a specific timeline for this, we are pursuing a trial focused on never-smokers or genomically-defined never-smokers regardless of when we receive the orphan designation. Achieving the designation would be an added benefit for us in terms of exclusivity and commercial rights.

Kyle Bauser, Analyst

Got it. Okay. That makes sense. And how about for LP-184 for pancreatic and glioblastoma? I think you're going to be applying for the designation there. Any sort of timing segmentation?

Panna Sharma, President and CEO

I believe those should be much more straightforward since, as you mentioned, glioblastoma and pancreatic cancer are already orphan indications, so that should be easier. We are currently compiling some of our preclinical data, and we expect to submit at least one of those this year and probably the other one early next year. They are both lined up for submission in our queue right now.

Kyle Bauser, Analyst

Okay, okay. And can you talk a little bit more about what steps need to take place for you to begin the Phase II LP-300 trial? Just kind of the final remaining things that you need to kind of accomplish before you can initiate that.

Panna Sharma, President and CEO

Sure. There are three objectives we aim to achieve with the Phase II LP-300 trial. First, we've already started the GMP manufacturing of the compound and issued a press release about it. We anticipate this will be completed within the next few months. The second objective is to finalize the signature, which we are actively working on and expect to complete by the end of this year. The third goal is to secure agreements with the sites. We will provide an update to investors regarding the sites and key opinion leaders we are collaborating with. We are currently in active discussions with them. We likely have one lead site that is progressing well, but I prefer not to divulge too much information before the official announcements. We plan to communicate more about this in the next couple of months, likely in late Q3. Our intention is to launch the trial by mid-next year, so we are focused on getting everything prepared by the end of this year, with Q1 dedicated to operationalizing the sites, followed by patient enrollment starting in Q2.

Kyle Bauser, Analyst

Okay, okay, that's helpful. Yes. And maybe just one last one, if I may. I know the $2 million to $3 million of the recent raise has been kind of earmarked to explore additional in-licensing compounds. And now with over 500 million data points, I imagine RADR's already kicked out quite a few ideas for new assets to in-license. And you mentioned in your remarks that you hope to in-license about 1 asset per year, I think. But do you have a pretty active list of potential compounds that RADR has already kicked out? I'm just kind of curious how many assets you're actively exploring at a given time.

Panna Sharma, President and CEO

That's a great question. It seems at times that there could be a whole business opportunity, as we have several compounds of interest. We're currently testing one or two, and there are over half a dozen potential partnerships or collaborations coming from biotech and pharmaceutical companies. We're in different stages of reviewing data, gathering information, and having initial discussions or signing NDAs to access their data. Opportunities come our way from insights generated by RADR, particularly when we focus on specific classes of compounds or diseases. Additionally, we're approached by various biotechs and pharmaceuticals expressing interest. This is definitely an area where we could dedicate more time. With 500 million data points and expanding into more cancer categories, we likely have over 10 to 12 more ideas to explore more thoroughly. While this is a positive situation, we must stay focused on advancing our current portfolio. With a team of 10, possibly expanding to 12 or 15, we still have more opportunities than we can currently manage. However, as we scale, we will selectively choose one or two key assets for future development.

Operator, Operator

We'll take our next question from John Vandermosten with Zacks.

John Vandermosten, Analyst

Panna, David, congratulations on going public last month. Let's start with just a chat about some of the inputs that go into optimizing the target population. You've talked about that pretty generally, but I'm just wondering what specific categories are used to identify a drug that might work in a targeted population.

Panna Sharma, President and CEO

Each drug or opportunity generally begins at different stages. Often, it starts with the results of a Phase II or Phase III trial where efficacy was observed in certain patients, although not enough patients showed the same response. This is usually a significant starting point. Another key starting point might be where a strong signal of efficacy was noted in Phase II, but it remains uncertain if it arises from a single mechanism or multiple mechanisms. Additionally, we often find good signals from approved drugs, where improved therapeutics for a specific indication were anticipated to work for another type of cancer based on tumor location, yet the mechanism didn't succeed and failed at another site. These are common areas we explore. The approach we take really depends on the drug's stage and direction, as we strive to determine if there is a signal identifiable by examining responses in certain groups contrasted with a lack of response or incomplete response in others. This process begins with data from RNA gene expression and, sometimes, genomic data. These data points serve as our foundational starting points. We then integrate drug sensitivity information and enhance our findings with specific cell-based assays that focus on particular functions or endpoints, often through proprietary studies conducted with contract research organizations or collaborators. If we discover differing RNA signatures, we carry out proprietary sequencing efforts, either in biopsies obtained under institutional review board regulations or in xenograft models, organoids, and occasionally cell lines. Generally, we focus on higher value models to examine potential RNA signature changes between responsive and nonresponsive groups. Each type of cancer presents its unique challenges, including model availability and quality, which sometimes necessitates the creation of new models. Thus, each scenario is slightly different, but it fundamentally revolves around gaining a detailed understanding of responder versus nonresponder groups based on biological networks and their activities before and after dosing or other relevant events, which could be genomic, transcriptomic, enzymatic, or protein-related, encompassing all aspects.

John Vandermosten, Analyst

Okay, great. Good summary. A lot of your drugs have considerable data available since they've already undergone trials. How does having this previous data influence the trial design, especially in your focus area and costs moving forward? Clearly, there are benefits. What are some specific advantages you can derive from having this historical data?

Panna Sharma, President and CEO

Yes. The historical data serves as a useful foundation to understand the issues examined by previous researchers. However, the relevance depends on when that data was finalized, whether it was in 2007, 2014, or 2018, as the quality of sequencing has significantly evolved over the last decade. The technology has advanced through various generations, and the volume of studies has increased greatly. While this information gives us insights, it does not provide a complete picture. Therefore, we consider it primarily as a starting point. Often, there are specific biomarker studies, structural studies, or binding studies that we take into account. We analyze these to identify gaps, as well as questions regarding data quality or value, sequencing depth, or sequencing capabilities that may need to be revisited. Overall, historical data is a valuable resource, but the most critical historical data we seek is the response from trials, which we prefer to examine closely. This data is sometimes shared, but it typically requires extensive discussions under NDA to obtain.

John Vandermosten, Analyst

Okay. Helpful. And I want to extend an...

Panna Sharma, President and CEO

To address the second part of your question, using a trial or an abandoned drug can save several years of effort—about 2 to 3 years or even more. This is because we can bypass the IND-enabling and Phase I/II studies, which means significant savings in both time and costs. We believe this is why exploring these efforts is beneficial, as there are thousands of trials that have not succeeded over the past decade, and we see several hundred of those as potentially valuable compounds. Our challenge is to determine where these compounds can be most effective and if there is a substantial population that requires them. This is fundamentally a data challenge. However, complete data is not always available, so we attempt to reconstruct that information through proprietary methods. This might include collaborations, partnerships, sequencing campaigns, sensitivity studies, and specific cell-based assays related to the mechanisms we're investigating. The goal is to enhance our data collection. With more data, we can condense the timeline for traditional bioinformatic or statistical analysis from months down to days. This efficiency allows us to ask and answer questions more quickly, which in turn guides our research. Instead of spending hundreds of thousands or millions only to find that something isn't viable, we can take a more focused approach. Thus, targeting a rescue compound can save us years and substantial upfront costs, while enhancing the overall efficiency of the process as we re-engage in pivotal trials.

John Vandermosten, Analyst

That's the goal. And just an extension on the orphan topic we were discussing earlier. Because you have these very focused populations and subsets of populations, do you anticipate future products will be in that targeted area? I mean, obviously, there are benefits to having an orphan drug. And it seems like the approach that you're using would identify those kinds of populations more likely. Is that kind of a goal that you see going forward? Or is it a beneficial by-product in some cases like NSCLC?

Panna Sharma, President and CEO

I believe it's a positive aspect. It's definitely a valuable outcome. Most oncology therapies being approved today are targeting increasingly specific populations based on genetic profiles. If we obtain an orphan designation for that genetic profile, it enhances our value and provides additional commercial rights, although it is not essential. However, I consider it a positive development. We don’t need it to progress, and this is part of the value of our companion diagnostics, which allow us to effectively identify these populations, ensuring a greater chance of response. We believe that these populations will be more narrowly defined, and this aligns with the opportunities for RADR to expedite and improve this process. Additionally, we are also exploring combination programs, which we will discuss further in the latter part of this year. Many cancers develop resistance over time, and one significant takeaway from advancements in computational virology is that combination therapies can be highly effective because they target multiple mechanisms through which cancer can evade treatment. Instead of relying on a single approach, utilizing two or three therapies simultaneously greatly reduces the chances of cancer recurrence. Finding and testing these combinations presents a more complex challenge than developing a single agent. This is fundamentally a data and testing challenge. Thus, we are concentrating on utilizing RADR to enhance our algorithms and models, enabling us to recommend combinations to pharmaceutical partners, explore combinations for our current medications, or revive previously unsuccessful drug combinations. This is an area we’ll focus on as the year progresses and definitely into next year with our combination programs.

John Vandermosten, Analyst

I have one final question regarding the FDA's willingness to grant an orphan designation. We may have a specific population that qualifies as an orphan indication, but do they resist that? For instance, in the case of non-small cell lung cancer in never-smokers, what kind of pushback is encountered when defining such populations? You can pinpoint that as a different demographic, but how does the regulatory agency respond when you present this to them?

Panna Sharma, President and CEO

We're still in the early phases, so I don't have a definitive answer. The pushback often stems from the need to clarify how a condition is defined; if it's not already established, it becomes more challenging. As Kyle pointed out earlier, there are areas like glioblastoma that have been clearly designated as orphan diseases due to the historical data collected on tumor location. Now, as they consider making orphan designations based on specific signatures or unique characteristics, it becomes a dialogue to demonstrate that this is indeed a unique population. The essence of the matter is proving that it is a distinct group, which will likely respond differently.

Operator, Operator

It appears that there are no further questions at this time. I'll turn the call back over to the presenters for any closing remarks.

Panna Sharma, President and CEO

Great, Ashley, thank you for the Q&A. So we look forward to having discussions with many of you, and we hope that you continue to follow and watch Lantern as we progress. And we will be providing periodic updates and press releases about our progress, and we hope to be talking with many of you very soon. Thank you all for joining our first quarterly call.

Operator, Operator

Thank you. And this does conclude your program. Thank you for your participation. You may disconnect at any time.