Good afternoon and welcome to Lantern Pharma’s Fourth Quarter 2020 Conference Call. As a reminder, this call is being recorded and all participants are in listen-only mode. We will open the call for questions-and-answers after the presentation.
I would now like to introduce your host for today's conference, Marek Ciszewski with Investor Relations at Lantern Pharma. Marek, please go ahead..
Thank you, Christie and thank you for joining us for Lantern Pharma’s fourth quarter 2020 conference call. On the call today are Panna Sharma, Lantern's President and CEO; and David Margrave, Lantern’s CFO. A press release was issued this afternoon with our fourth quarter financial results that we will be discussing here today.
Following the Safe Harbor statement, Panna will provide an overview of business highlights, after which David will share our quarterly financial results. Panna will then offer concluding comments, after which we will open this call to questions.
Please also note that we have provided a link on the IR website to the slides that we will be referencing in today's call.
I would also like to remind everyone that remarks about future expectations, plans, and prospects constitute forward-looking statements for purposes of Safe Harbor provisions under the Private Securities Litigation Reform Act of 1995.
Lantern Pharma cautions that these forward-looking statements are subject to risks and uncertainties that may cause actual results to differ materially from those anticipated.
There are a number of important factors that could cause our actual results to differ materially from those indicated by forward-looking statements, such as the impact of COVID-19 pandemic, the results of our clinical trials, and the impact of competition.
Additional information concerning factors that could cause actual results to differ materially from those in forward-looking statements can be found in the risk factors section in our annual report on Form 10-K for the year ended December 31st, 2020 which was filed with the SEC on March 10th, 2021.
Any forward-looking statements made on this call -- on this conference call speak only as of today's date, Wednesday, March 10th, 2021, and Lantern Pharma does not intend to update any of those forward-looking statements to reflect events or circumstances that occur after today. Please refer to today's press release for replay information.
And now, I turn the call over to Panna Sharma, President and CEO of Lantern Pharma..
Marek, thank you and good afternoon to everyone on the call today. Thank you for joining us for our fourth quarter and year end 2020 conference call.
For those of you that are new to Lantern Pharma's story, we are a unique company, an oncology biotech that leverages the power of artificial intelligence and machine learning to both rescue and develop oncology therapies. We do this through our internally developed proprietary AI platform called RADR.
We're one of the few AI-based biotechs that has multiple clinical stage programs in development, as well as a rapidly growing proprietary platform for accelerating our understanding, modeling, and prediction of patient and tumor response to cancer therapies.
In this regard, we're a very unique company at the forefront of the data and machine-enabled transformation happening in drug development and drug discovery today.
Our team has been working very hard this past quarter, advancing our collaborations, developing meaningful lab data, advancing our manufacturing, onboarding new team members, both employees and consultants, while also hitting major new milestone for our platform and for developing insights for new indications that will power future therapies.
Shortly after we began trading last June of 2020, we announced that our proprietary AI platform for precision oncology drug development RADR surpassed 450 million data points. That was roughly six months ahead of our plans. Now, we plan to cross the 3 billion mark during 2021. We closed 2020, we're a little over 1.1 billion data points.
These data are highly curated data sets specifically for oncology, drug development, and drug response prediction.
Our team has made tremendous progress in this front and has recently announced a publication in BMC Bioinformatics, which showcases some of the processes that our platform enables for drug development, in particular preclinical work for selection of indications and the development and -- of a biomarker enabled signature that can be used for both patient selection and prediction of tumor response.
Our process for selecting clean, curating, and tagging the data has gotten significantly more efficient and powerful and this will allow our company and particularly, our partners to develop cancer therapies and better understand where and how certain compounds work with even greater precision, reduced risk, and a much more rapid pace.
We will be seeking and developing select partnerships with biopharma companies where our RADR AI platform can help in the development of their programs and generate rewards and upside for Lantern and our investors.
Beyond merely the sheer amount of data, the quality and relevance of our data and functionality continues to grow, as evidenced by the increase in the number of indications and programs we have developed since our IPO. In June, it was three and now it's seven programs. And this is all in the span of the last nine months.
Our RADR AI platform stands at the core of our business model alongside a targeted and accelerated drug development path. The growth in the quantity and quality of our data and also our functionality is an important driver of the value of our franchise.
RADR's growing genomic drug sensitivity and patient outcome datasets, combined with our AI and machine learning, enable us to streamline the drug development process, while also identifying patients and patient populations that will benefit from our oncology therapies.
We are confident the power of RADR will enable us to add at least one additional biomarker or genetically defined program or indication to our pipeline every 12 to 18 months.
During previous calls, I've spoken extensively about how we are now beginning to experience and live in the beginning of a golden age of artificial intelligence, an era where the availability of relevant data, computing power, cloud resources, on-demand sequencing, talent, and the acceleration of AI and large scale data analytics and algorithms, along with shifting economic and industry demands have aligned to make large data-driven, highly responsive, machine-driven approaches to solving complex, sometimes unknown problems a reality.
This is especially true in drug development. We are harnessing the trends and capabilities of this golden age to accelerate our pipeline, and most importantly, to benefit cancer patients and to bring down the costs associated with the risky and lengthy process of cancer drug development.
For those of you that are still new to the story or learning about Lantern, our pipeline is small molecule oncology assets and antibody drug conjugate asset includes new compounds that we have identified to our biomarker discovery efforts, as well as potential therapies of extensive prior clinical experience that we acquired after previous owners abandoned development efforts following Phase 3 setbacks.
In all regards, we own the therapeutic rights or developmental rights to all the assets that were developing. Our RADR AI platform underpins each development or rescue efforts and we are confident that this will help us achieve a scale and transformation to the oncology drug development process.
2020 was a pivotal year for Lantern Pharma marked by a series of financial, operational, and drug development achievements, each -- some -- many of which are highlighted in the press release that was issued earlier today -- earlier this afternoon.
But these achievements validate something that's very unique about our business, not only are we capital efficient and leveraging the power of AI, but we also are combining that with the knowledge and experience for a scientific team to rapidly take these insights and march forward in our drug development programs.
In the short time since our June 2020 IPO, we've more than doubled the number of programs that we have in active development. This increases the number of opportunities for high -- for creative licensing deals, partnering opportunities, and generating upside for our investors. We also initiated a highly differentiated antibody drug conjugate program.
This leverages some very unique linker technologies developed by Califia and it also -- we also grew the number of data points that fuel our AI platform by over 5x past year, initiated manufacturing, research and development, collaboration with leading cancer research institutions; these include Johns Hopkins in glioblastoma, Georgetown University in prostate cancer; Fox Chase Cancer Center in pancreatic cancer; and also their solid tumors were nucleotide excision repair mechanisms can be exploited.
These are all very targeted programs and many of these programs and collaborations are now entering their second stage including the one with Georgetown.
The first stage of joint research activities began in the fourth quarter of 2019 and generated compelling evidence of efficacy of LP-184 in solid tumors, in particular, solid tumors that overexpress PTGR1.
This anti-tumor activity was linked in a dose-dependent fashion and we validated it in very specific subtypes of prostate cancer where PTGR1 is naturally over expressed as a form of it becoming metastatic.
This research has helped us guide specific development of that signature and more importantly, correlates to increased response among certain subtypes of cancer, including cancers that are DNA damage repair gene deficient.
The next phase of collaboration will focus on a larger set of the X models, it will pinpoint the specific mechanism, seek confirmatory validation on the role of PTGR1 and other genetic mutations and the research will complete the acquisition of detailed genomic information in prostate cancers, and potentially, other related to your genital cancers.
The second phase goal to create a biologically relevant robust gene signature that we can take into clinical trials and will prepare us to select patients with the objective of a lot of future prostate cancer patients to experience the benefit of a more personalized cancer treatment approach.
Ultimately, we believe that our AI-driven approach could save millions of dollars in drug development costs, perhaps tens of millions, while significantly accelerating the path to commercialization, but more importantly, personalized treatment towards select populations that are most likely to benefit from the therapy.
Work that we're doing at Georgetown is being led by Dr. Partha Banerjee, a world renowned expert in molecular oncology and prostate cancer.
We also have collaboration research agreements with Fox Chase Cancer Center for the development of LP-184 in pancreatic cancer, and this collaboration advances the targeted use of LP-184 in genetically-defined subtypes of pancreatic cancer.
Again, those are the right gene signature and of course, to be able to use that gene signature, biologically relevant and naturally -- and occurring naturally in pancreatic cancers to guide the development of clinical trial.
If successful, we believe that we can develop a more personalized therapy option that has the potential to improve survival and thereafter one of the cancers that has very poor overall survival. The program at Fox Chase Cancer Center is being led by Dr. Igor Astsaturov in the molecular therapeutics program at Fox Chase.
Igor is an internationally recognized researcher in GI cancers, specializing investigating signaling pathways and informed choice of biomarkers and innovative therapy combinations and clinical trials. In the fourth quarter, we announced another collaboration and research agreement with Johns Hopkins as the Sidney Kimmel Comprehensive Cancer Center.
This program is focused on further development of one -- LP-184 in glioblastoma. Johns Hopkins is a leading research center for brain cancers, one of the largest brain tumor treatment and research centers in the world and they focus on treating extremely large number of patients affected by all types of brain tumors.
In fact, after finding that LP-184 crossed the blood brain barrier exquisitely, we've been at the forefront of enriching our RADR database with several dozen million data points in brain cancers.
And again, the collaboration today with Hopkins is focused on defining the subtypes of GBM, but also clarifying the most promising clinical application for the drug candidate, LP-184, especially as monotherapy.
The goal of this collaboration is to develop a clinically ready program that has characterized the drug candidate the most biologically relevant and robust biomarker signature, and using that signature to identify the patients that have the highest potential for response.
This way we can shorten future trials and bring the drug to the benefit of these needed population.
This kind of research we believe is at the forefront of translational cancer medicine, and very importantly, allows us to develop physiologically relevant models using patient-derived material, and then understand the biology of what is actually happening inside the cancer tumor and use that to feed our RADR engine.
The RADR engine allows us to generate more precise biomarker signatures that provide data-driven insight into additional mechanisms. So, we believe this is a very essential -- very important feedback loop as data from physiologically relevant experiments feeds back into our AI engine. Our AI engine generates signatures.
Those signatures then are used to do additional work. And this process is continuing now -- several cancers and several cancer areas at Lantern, and this feeds millions of data points of additional insight -- proprietary data-driven insight into our RADR platform. Our GBM program is being led by Dr.
John [Indiscernible], an internationally recognized researcher in neurology, oncology, and neuroscience. During our last call, we talked about how LP-184 has demonstrated high nanomolar potency and the ability to cross the blood brain barrier, something that very few small molecules can do.
But more importantly, as it crosses the blood brain barrier, it keeps neuronal cells intact and viable, while really focusing the damage on the cancer or the [Indiscernible] cells.
This opens up a potentially high value opportunity to help patients in many other brain cancers and the ability to cross the blood brain barrier is of critical importance and treatment outcomes for CNS and other brain cancers.
Our AI platform along with algorithms tuned to predict blood brain barrier permeability, played an important role in helping determine which CNS cancers and which didn't genomically-define subtypes of CNS cancer should be prioritized for development, using in-silico tools and also in-vitro data from neuronal cell plates, neurospheres, LP-184 demonstrated permeability that was in line with TMZ and other therapies, while also demonstrating nanomolar potency.
This data is extremely significant. Building on this data, we believe we can identify -- we have identified several additional brain cancers where LP-184 can play a major role as a potential therapy and we're pursuing one of the validated indications in Atypical Teratoid Rhabdoid tumors.
This is an ultra-rare brain cancer that occurs primarily in pediat -- in children, especially children under the age of four. And there's typically between 50 and 70 or 80 cases a year. So, very ultra-rare cancer without any therapies today.
And so we believe we can compress the timeline to bringing LP-184 as a potential therapy in this ultra-rare indication and have a potential treatment for these patients. So, we're working -- that we validated this both in the lab as well as in-silico. We're seeking collaborators to further to the syndication.
So, we believe with a franchise now that 12 months ago, was just beginning where we observed the potential for 184 to target GBM.
And after GBM, we now also have found a ATRT, validated blood brain barrier permeability, identified several additional indications that we're in the process of validating, and we've really developed a very unique portfolio of brain cancer indications for LP-184.
We believe this basket of brain cancer indications can be a very important tool to then partner with the right biotech or pharma.
Looking to other development programs, LP-100 is currently being managed by our partner for the treatment of genetically defined metastatic castration resistant prostate cancer, while LP-300 small molecule candidate also is preparing to enter a Phase 2 trial in non-small cell lung cancer as a combination therapy for non-smokers.
For LP-300, we have made significant progress and better understanding the mechanisms involved in LP-300 activity and in-lining the usage of LP-300 with the chemo doublet therapy that is more commonly used today, namely carboplatin and pemetrexed.
This is accomplished through a recently completed non-clinical bridging study that showed the LP-300 is with carbo and pemetrexed is as safe as cisplatin and paxi capsule and doesn't cause any additional toxicity or adverse events. We plan on sharing this with the FDA as part of a process to reenter Phase 2 clinical trials later this year.
Most recently, we also announced something that is very unique, and that is the launch of our antibody drug conjugate program. This was developed by leveraging the AI platform by understanding where LP-184 could potentially work best by synergizing with other optimal targets. And many of these targets were antibody targets.
And we also then were able to work with Califia Pharma to leverage a patent protected linker library that we can conjugate with our unique DNA damaging compounds like LP-184, and potentially other payloads.
According to industry analysts, the global ADC cancer therapy market is expected to exceed $10 billion by 2026, $15 billion by 2030, and it's driven by innovations in protein targeting, which is what our platform does. We're really targeting linker technologies which we now have access to Dr. [Indiscernible] on Califia and conjugation processes.
So, ADCs bring together the ability to target specific antibodies on very specific types of cancer cells and then link that antibody targeting capability to delivering our potent molecule or payload to that cell.
ADC is an emerging class of highly potent drugs and have seen several approvals over the last two years, and a lot of interest from big biotech and pharma and partnering.
The portfolio of technologies and library linkers at Califia has meaningfully progressed with a specific focus on our class of drugs and we believe this optimization coupled with the identification of cancer subtypes and molecular targets has allowed us to save several quarters, if not years, in the development process, and allows us to enable targeting very specific cancers.
This way we can enter the clinical trials at a speed that we believe has not been achieved in the ADC category. So, again, we believe this is another major franchise portfolio of value with the ADC program.
Working closely with the innovators and world-leading drug developers is an essential part of our strategy to leverage and develop new platforms that can transform the timeline and the effectiveness of cancer drug development.
By implementing antibody drug conjugate approaches, we aim to offer cancer patients an additionally highly targeted platform that can make meaningful contributions and also benefit from the synergies over our AI drug development or data-driven approach.
Together our current portfolio of drug candidates and our RADR AI platform has the potential for multiple shareholder value milestones in 2021 and 2022.
In addition, our RADR platform is mature to the point where we're going to begin to focus increasingly on collaborating with other biotechs and pharma companies to further develop RADR and to develop opportunities through RADR for our investors.
Now, I'll hand the call over to David Margrave, our CFO for review in the fourth quarter and year end results.
David?.
Thank you, Panna and good afternoon everyone. I'm now going to share some of the financial highlights from our fourth quarter and the full year 2020.
It's important to note that we incurred added expenses in 2020 as a result of becoming a public company and with our lean operating structure, these changes resulted in substantial differences for purposes of our 2020 to 2019 period-to-period comparison. Starting with highlights for the fourth quarter of 2020.
For quarter ended December 31, 2020, we had a net loss of $2.9 million, or $0.47 per share, compared to a net loss of $675,000 or $0.34 per share for the quarter ended December 31, 2019. The net loss for Q4 2020 included non-cash expense items of $1,024,904 related to employee stock option compensation.
Research and development expenses were $1.3 million for the quarter ended December 31, 2020 compared to $177,000 for the quarter ended December 31, 2019.
The increase was primarily attributable to increases in research studies and non-cash research and development related stock option compensation expense, as well as the expansion of the company's research team. The Q4 2020 non-cash R&D expense related to stock option expense was $470,401.
General and administrative expenses were $1.5 million for the quarter ended December 31, 2020 compared to 498,000 for the quarter ended December 31, 2019.
The increase was primarily attributable to an increase in expenses associated with operating as a public company, along with increases in non-cash general and administrative related stock option compensation expense. In Q4 2020 non-cash G&A expense related to stock options was $554,503.
In terms of fiscal year 2020 financial highlights, as of December 31, 2020, we had working capital of approximately $19.7 million, primarily driven by the net proceeds of our IPO that closed June 15, 2020.
For the year ended December 31, 2020, we reported a net loss of $5.9 million or $1.37 per share compared to a net loss of $2.4 million or $1.23 per share for the year ended December 31, 2019.
Research and development expenses increased $1.3 million or 135% from $953,000 for the year ended December 31, 2019 to $2.2 million for the year ended December 31, 2020.
The increase was primarily attributable to increases in research and development labor and research study expenses, as well as an increase of approximately $470,000 in non-cash research and development related stock option compensation expense.
General and administrative expense increased $2.2 million or 149% from $1.5 million for the year ended December 31, 2019 to $3.7 million for the year ended December 31, 2020.
The increase was primarily attributable to expenses associated with transitioning to and becoming a public company, including increases in corporate insurance expense and general and administrative labor expenses, as well as an increase of approximately $604,000 in non-cash general and administrative related stock option compensation expense.
We expect we will continue to increase our R&D spin as we further advance our portfolio and recently initiated ADC program and move towards the commencement of additional clinical trials and research studies.
Currently, we have 15 employees, 11 full-time, four part time, as well as for consultants, who are primarily focused on leading and advancing our drug development, biology, and data science efforts. Our cash position at December 31, 2020 was $19.2 million.
As a result of our 2020 development and operational progress, as Panna discussed earlier in the call, we were able to significantly strengthen our balance sheet subsequent to year end, with the closing of a $69 million follow-on public offering in January 2021. This additional cash extends our anticipated cash runway through mid-2025.
We believe our solid financial position will fuel continued growth and evolution of our RADR AI platform, accelerate the development of our portfolio of targeted oncology drug candidates, and allow us to introduce additional targeted product opportunities in a capital efficient manner. I'll now hand the call back to Panna..
Thank you, David. I have a few more comments before we open up for Q&A. Moving forward; we expect to make additional progress on the development of our existing programs, while also strategically focusing on new opportunities that we're uncovering or that we can create in collaboration with others.
As seen our growth in programs from three to seven just over the last several quarters, we believe that our data-driven genomically targeted AI-driven approach is really a transformational way to do drug development for oncology and allows us to identify and rescue and develop candidates that we believe can be done at a fraction of the time and cost associated with more traditional methods of development.
Our dual approach to developing both de novo biomarker guided drug candidates and also having the potential to rescue historical drug candidates by leveraging the data sets and other work inside of RADR, we believe is a massive advance in genomics computational biology and cloud computing.
We believe this is emblematic of a new era of drug discovery and development that we are proud to be a leader in. In this context, we are focused on building a portfolio of high value oncology drug candidates, each of which can be potentially partnered for pivotal registration directed trials or sold or licensed off.
We provide -- we believe this provides a very clear and defined path for potential significant value creation for our shareholders and establishing Lantern Pharma as the leading AI-driven oncology, drug discovery, and drug development franchise, we believe is something that we're well on the path to do.
So, with that, I'd like to go ahead and make sure people understand that the key goal of our company and franchise is to transform oncology drug development through the use and power of AI and build true enduring value by doing that.
We think the golden age of AI and drug discovery and development is here today, and will make -- have significant repercussions throughout medicine.
We believe we're one of the leading leaders in this paradigm shift to change the pace risk and costs of oncology drug development and that we are proving that our platform can provide significant deficiencies in the time and cost.
More importantly, our growing pipeline of drug candidates shows that the rapid identification and validation of molecular drivers of cancer allows for more targeted and more effective pathway to developing new drug candidates, identifying drug combinations, and potentially new constructs such as antibody drug conjugates.
So, we look forward to sharing our ongoing progress with you in future updates and hopefully, more of these in person as the year progresses.
I would also be remiss not to take some time to thank everyone who's been on the front line or knows people on the front line of all the work that's being done, especially with health care workers and advocates, and of course, all the millions of people that are helping to care for and put an end to this COVID pandemic.
We should all take time to be thankful each day for the efforts that have put forward to bring society and business back toward normalcy. They've oftentimes done this in a hostile and oftentimes, under accepting umbrella of -- being misunderstood.
So, with that, I'd like to put my hat and say thank you for all the work that everyone has done to make a change and bring this pandemic to an end. And I look forward to meeting more of you in person throughout the year, and zooming more normalcy to business and society. And with that, I'd like to open up the call for questions..
[Operator Instructions] We will take our first question from Kyle Bauser with Colliers Securities. Go ahead. Your line is open..
Great. Thanks for taking the questions and appreciate all the updates here. Certainly, a lot going on.
I know you talked about the current cash balance being able to get the company to mid-2025, but could you talk a little bit about how we should think about the quarterly burn with the most recent updates on the ADC program and other opportunities like ATRT, just want to make sure I'm thinking about the burn correctly over the near-term here?.
Yes, absolutely. Go ahead David and walk through -- I'll let David to come and walk through the burners and how we see that progressing, but we do see progressing upwards over the years.
So, David, do you want to walk Kyle through that?.
Absolutely. So, it's a great question and important question for us. We are in a much stronger financial position now and this allows us to execute on a lot of things that we had brought online at position for since the time of our IPO, but this really allows us to accelerate that.
We will see a substantial ramp up as we move towards the launch of LP-300. Additional clinical trials we have planned related to 184 as well as our ADC program and over the course of the next two to three years, we see our quarterly burn, increasing substantially, a higher and higher proportion will be associated with R&D.
You see that increasing in particular as we start the Phase 3 for LP-300, and then in 2021 -- into 2021 and start of 2022, as we move towards starting additional clinical trials for 184..
Got it. That's helpful.
And just curious regarding the ATRT opportunity, it sounds like this ultra-rare condition could allow for a much faster timeline, but given the small prevalence of the addressable patient population, would pricing be able to offset the small number of potentially treatable patients? I'm just trying to understand the ROI on this opportunity, given the prevalence size? Thank you..
I think you read the prevalence again, is -- it's an ultra-rare cancer. So, I think for us we're more interested in benefit to that patient population, initially, but also, once we have the drug in market, there are a number of other tumors that are similar to ATRT.
These rhabdoid tumors also occurrence in forms of kidney cancers and sarcomas and they're oftentimes marked by a certain biomarker that makes them sensitive to our drug. You'll see that we publish a little more about that later, but it relates to the genes SMARCB1.
So, as SMARCB1 B1 is mutated, it tends to then not produce a downstream protein, also SMARCB1, which is a tumor suppressor. And it occurs in a few percentages of cancer, but mostly in ATRT and certain kidney cancers synovial sarcomas. And so our goal is we know there's a need in this patient population.
We know there's clear ability for this to cross the blood brain barrier, we believe we can get fast-track, and then we can introduce LP-184 in some of the other cancers that I talked about, which will increase the size of this market significantly.
But also, it'll -- since we'll have our drug in market, we can then pursue other combination indications.
So, it's really not just the ATRT market alone that we're looking at, we're also looking at once this drug is in market and being used clinically, that opens up a lot of other opportunities that we would not have by not having a drug that's being routinely used..
That's helpful. Great. Well, thanks for taking my questions and for providing all the updates here..
Thank you, Kyle..
And we will take our next question from Daniel Carlson with TW Research Group. Go ahead, your line is open..
Yes. Thanks for taking my question guys and congrats on all the progress. A couple questions. You talked about the ADC program a little bit and certainly seems like an attractive space to be in.
Can you provide any additional insights into what is going to have exactly your program and timing around that?.
Sure. Thank you, Dan. Good question. So, we've done some more progress on the ADC world, we probably will have -- host a conference call a broader update later this year.
But we really narrowed in on certain antibody targets, specifically targets where the antibody can be internalized into the cancer cell and as a result of the changing environment, release the payload. So, this cleavable linker, we've kind of identified, we've identified a few of the antibodies, specifically antibodies that can be internalized.
So, we have some initial data on that. So, we've continued to narrow down the program in terms of how we would approach it. We also have kind of a backup category. We also have some initial indications in a hem cancer as well that we might pursue. But the key for our drug to work is for the drug to be internalized in the cancer cell.
And so that has narrowed down the way that we're thinking about the antibody that we're conjugating it to. So, it gives us a pretty small window of the antibodies that we're most likely to look at. So, I feel like we have a pretty focused program on this.
And again we're going after some solid tumors where there really hasn't been notable improvements in overall survival. So, we think that there's potential for partnering this asset out for a significant amount quickly..
Very excellent. Thanks. Second question for you here. There was a paper published BMC Bioinformatics last week that really seemed in my opinion to help validate exactly what you've been saying about RADR and wonder if you can provide any more insight into that.
And then a second part of this question, you talked about the platform -- RADR platform, I'm wondering how you can really leverage that, is it through bringing in more drugs onto your platform or is there potential to as you build it out and it gets bigger to take it out to a broader audience partnerships, et cetera?.
Yes, great question. So, the interesting thing is that the paper, it's already dated, but yes, it's a great paper because it showcases how we're using it to make decisions about the indications that we're going after and the types of genomic information that it's zeroing in on.
Again, this is for a fairly small group initially, when – when this work was started, you know, our group has increased, as you know, we're six people went public with 15. So still not huge, but we have more talent. And we can crunch through more data and more numbers and do more with the platform.
But yeah, the BMC Bioinformatics papers, a great example of how we can use RADR processes on one specific drug to unlock multiple potential indications. In terms of we've developed a signature, we selected preclinical indications that we went into a lab with that really bore out a lot of fruit.
And, actually now, the platform has actually grown significantly since that, since we started working on that paper. And because of that, we do think that we'll be able to start generating, what I call time to indication, typically takes six months to a year, wherever, during that time to indication down to a matter of weeks.
And so at that level, we will come up with more ideas, and we can possibly develop completely on our own.
So we do think, it's getting to the point, especially as RADR gets to 2 billion and 3 billion data points, which should be fairly quickly this year, that we will seek more partnerships, using the platform will make the platform more powerful, and we think, be able to potentially give our investors upside and other programs.
So yes, that is part of our strategy that we're going to unfold now is to take some of our time and interest and take a look at how we can leverage this platform to get access to other – other programs, other indications, other molecules.
And there are a lot of companies that have approached us and we've had some discussions with so that's something that will we will selectively pursue this year..
Great. Thanks.
And then there's one quick follow-up in on this ATRT, and maybe a little naivete on my part, but with this qualify for a priority review voucher?.
David, do you want to talk about what we know that the priority reserve programs? Right?.
Right. We think there is potential for that. And the voucher program is, as many know is something that has just been re-extended with recent legislation. So that – that's encouraging in terms of further incentivizing companies to pursue pediatric indications.
The vouchers are able to be used by the sponsor, or they could also be purchased by another company. So there is potential value in the rare pediatric disease voucher program, and we're learning more in terms of the details with respect to ATRT and that indication.
But from what we are aware of right now, we believe that it would be potentially eligible for the voucher program..
Right, yeah. Those have been traded for like 100 million. So it will be awesome. That's it for me. Thank you. Keep up the great work..
Thank you..
Thank you, Dan..
[Operator Instructions] We will take our next question from John Vandermosten. Go ahead, your line is open..
Hey, good afternoon, Panna and David. How are you guys doing? Let me -.
Hi. Thank you, John..
Hi, John..
Hey, how are you? Let me start with a question on 184 seems like the potential that – for that is fairly broad, you've named a number of areas there, including CNS, which, you know, could be a number of indications there.
How are you going to use the data that comes up to narrow that down further and when you probably get to perhaps Phase 2 or something like that to know what you're going to try to take all the way to the end?.
Well, we are looking at what is there a subset of what subset of Glioblastoma as well, this work in best. And so that's something that we're hoping in the next few months, we want better understand.
And I do think that, also, the other indications that we're pursuing won't be the entire indication, but again, it'll be a subset or some genomically defined group. And so that's typically how the tribes will be organized or structured..
Okay. And I guess, you know, sometimes there are trials that have multiple – multiple indications in them, and they're adaptive, and you move forward based on what's working.
Is that is that something that you try?.
Oh, yeah, we were looking at there quite a bit. Absolutely..
Okay,.
We look at those adaptive as well as basket trials for some of these indications across –.
Right, right..
Yeah. So we'll definitely look at those, it's a little too early to – to pin one of those down right now..
Okay. No, that's a great way to do it. Because it seems like there's a lot of opportunity. And, you know, you obviously want to focus on what's most promising. And you mentioned, a bit about talking to other companies. And that seems like a great way to help some collaborations going forward.
You bring the RADR platform to the table, and, and your portfolio as well.
How do you go about doing that? Do you reach out to maybe smaller companies, because larger companies probably have their own AI system that they use, but maybe smaller companies and say, hey, share some of your data with us? We'll see if there's any opportunity, is that how you do it? Or what's the process there to find potential?.
I think there are definitely – there are definitely certain drug classes that are better suited. And so I think it'll be certain drug classes where we know we have some interest. Well, we know we have some new data, we're also of course, look for areas where there's been a clinical failure where we believe we can add value.
And of course, because of the ADC, we're going to, we have some identified some antibody targets too that people own and those that combined with 184, for one of our other drugs can be really unique.
So there's, I think there's some natural areas where either we have insight data or knowledge that we're trying to exploit first, and then after that, it's just, traditional BD efforts..
And do you get sharing from other companies? Do they share their data with you in an effort to see how the RADR platform works and how it might – might help them narrow down an indication?.
Yeah. That's the hope is that we will get a percentage. That's right, of the success of that drug, or that drug in the – in the indications that we hope to outline develop..
Okay. And I want to move on to LP-100.
I mean, I know that as an external, external asset, but what should we expect in the near-term on that, what is the next milestone that we should see on LP-100?.
We're having discussions with the clarity on kind of their on the program and the next stages of that. So I think we'll keep people updated as soon as we have details on the progress on the molecule and progress with the trial..
Great. Well, thank you all my other questions were answered. Appreciate it..
Thank you, John..
And this does conclude today's question-and-answer session. I will now turn the program back over to our presenters for any additional or closing remarks..
Thank you. And thank you, everyone, for participating on our quarterly call. We look forward to visiting many of you in the near future. And again, we believe that we really are a leader in the transformation of oncology, drug development using machine learning and AI.
And we believe in many of our programs to be worth significantly more than our market cap today. So we think there's a lot of upside for investors as we grow and meet milestones. Thank you for listening to our call today..
This concludes today's program. Thank you for your participation. You may disconnect at any time..