Q3 2021 Lantern Pharma Inc. Earnings Call

The conference call and webinar will be available on the lands from Farnell website.

And with that I'd like to turn the call over to punish Sharma, President and CEO of Lincoln Pharma partners. Please go ahead.

Thank you Nicole good afternoon, everyone and welcome.

Our third quarter earnings call. Thank you for joining US today. We're also live streaming this call through zoom webinar, which many of your investors have asked for and feel that this format can potentially bring you more information or insight about our business. Thank you for your feedback and request and bear in mind, we will always work.

And improving facets of our operations both internally, but also our communications with investors externally.

This past quarter third quarter has been a very exciting and bid very busy quarter for <unk>.

We've made meaningful progress on multiple fronts clinically operationally on our radar platform, which many of you read about this morning.

And also with our ongoing discovery efforts I'd like to highlight that we have exceeded our growth expectations that we set out earlier this year regarding our proprietary AI platform radar. We just surpassed 10 billion data points. This past month and this represents a 10 X increase in the number of data points since November of <unk>.

Last year and approximately a 37 fold increase since our June 'twenty IPO.

The increase in data points, which many of you have asked about in the past provides lantern and important long term advantage.

First it accelerates our drug development timelines by giving us ideas about indications or the feasibility of certain indications.

It allows us to uncover new therapeutic opportunities.

And potentially in license new compounds, we're finding new uses for our existing portfolio.

It also allows us to develop insights into how we can create combination therapy programs with our drugs and existing approved therapeutics, and we'll talk a little bit about that today as well.

And most importantly, it expands our ability to collaborate with additional Biopharma partners. We believe that the platform has gotten to a stage where it can be used not only for our existing portfolio, but for many other drug development portfolios in oncology.

Radar uses vast amounts of data from the transcript from the genome from expression data <unk> data drug sensitivity data from a wide range of curated sources, both human and animal cell lines, Pdx, <unk> steroid and even cell line.

All these data are analyzed monitored scored and constantly updated.

And ultimately the goal is to reduce the cost.

Reduce the risk and accelerate the timeline to get drugs developed by uncovering mechanistic insights on drug tumor interactions and developing companion diagnostic biomarker signatures.

<unk> signatures are essential.

Derisking drug development and as I'll talk about later have proven to increase the likelihood of bringing a drug to market on an average of five times higher than those developed without such signatures.

Ultimately our goal is to potentially benefit and select patients that have the best option for our drug therapies or combination therapies that we uncover.

Now a corresponding with this growth in data points. We also focused our resources and the technology on a very important area, which is the growth in constant improvement and evolution of our library of algorithms.

Algorithms are critical because they are constantly giving us new ways to correlate the data automatically sift through the data and more importantly give us new ways to rapidly identify correlations, we may or may not know about that are critical to making decisions in cancer drug development. They also allow us to.

A rapidly identify rare cancer subtypes that may have gone unknown or unnoticed or misunderstood.

And they provide insight into potential drug target interactions.

They also can help uncover patient groups that can respond to specific drugs not only one time, but over the course of their treatment.

Now with such an incredible assortment of algorithms and as it grows what we've done is also embedded in machine learning development operations environment. This is very important because it allows us to then pick and choose and select and compare different algorithms and how they perform or algorithms being used together.

<unk> algorithms are used together. This is called an ensemble based approach, where we use multiple alagoas and methods and we can rapidly and with <unk>.

Higher accuracy understand what the response is going to look like in a patient or a group of patients to our drug or drug candidates.

All of this is critical because it helps define and develop the strategy to bring this drug to market and develop companion sorry combination strategies that we think have a higher chance of approval.

We plan on continuing further data expansion, maybe I've always asked me how much data is enough. The answer it really there is no enough and data $10 4 billion data points, a wonderful and very meaningful milestone for our team, but there are tens of billions of additional data points to collect.

Hundreds of additional cancers to further explore and additional data sets being generated globally every single month or.

Our job is to bring in these datasets score them understand them and more importantly, do this in the automated where where we can evolve radar, but mostly now turn our attention to the library of algorithms that were evolving.

<unk> will continue to augment the $10 $4 billion billion data points, but in a very specific sets of areas. One area that we looked at last quarter was and hematologic cancers.

A major chunk of our growth came from blood cancers, because of our own focus on blood cancers going into 2022.

Additionally, this coming year will be focusing on immuno oncology related studies and trials data from these studies and trials will include antigen immunomedics and protein data and also robust multi omics analysis that's out there.

As many of you know there is a wealth of methods and algorithms already in development for Io drug response.

Prediction and Io drug drug response combination creation, our team will review many of these will improve them. They will incorporate them and this will make our platform even stronger. We think this will be a long term strategic advantage as we deepen our capabilities in two very important areas antibody drug conjugate development and combination.

Therapies using Io agents.

We already have significant reason to believe that certain Io agents, especially those that show high sensitivity can be high <unk>, meaning tumor mutation burden high as <unk>.

Marked in certain cancers, and they may have the potential to work synergistically with either 184, or <unk> 84, especially intractable and we're challenging tumors.

Turning my attention out of the biomarker signature. We think this is a real importance, but or in our recent multiyear study.

<unk> done by professor.

Dr. Jason Parker from University of Toronto, He and his colleagues reviewed over 10000 clinical trials from 1998 to 2017 and for solid tumors across 745 drug programs.

And they showed that biomarker based trials had success rates that were four to 12 times higher than those that did not use biomarkers.

Actually Dr. Parker's team concluded that the inclusion of biomarker status as a covariate significantly improve the fit of as Mark hub models that they use to describe the drug trajectories through the clinical trial testing stages.

So the hazard ratios on the Mark hub models.

Reveal the likelihood of a drug approval with Biomarkers had an average of five X increase across all for solid tumors.

And it was 12 X <unk> and <unk>, respectively, and breast cancer melanoma, and non small cell lung cancer, all diseases that are highly related and driven now by biomarker analysis.

Markov models, even with exploratory biomarkers outperformed market models with no biomarkers by a major factor.

So his team's conclusion well.

Well first of all we just know this is one of the first systematic statistical case reviews done but had we showed clear evidence of Biomarkers clearly increased clinical trial success rates in multiple indications in oncology and very importantly, exploratory biomarkers long before they're properly validated many labs appeared improve success rates.

In the drug development process. This supports one very important thing early and aggressive adoption of biomarker based signatures and buy in biomarker drive signatures in oncology clinical trials. This is a hallmark of our development process.

This further encourages us utilizing our radar platform with our drug candidates and also independently across cancer drugs to derive biomarker signatures has a unique potential in addressing the $200 billion global oncology drug market and it has a long term place in the future of cancer drug development and discovery.

We've witnessed firsthand now that theyre growing and growing industry interest in solutions that innovate the development of precision therapies and combination therapies and reduce the risk and cost. We believe that these kinds of solutions will pave the road kind of appetite for solutions will pave the road to new partnerships and ultimately greater investor.

Value, we remain committed to achieving our goal of building the world's largest AI platform for precision oncology drug development. We believe we're significantly on our way there already our goal next year is to get to over 20 billion data points deepen our focus in blood cancers add several additional rare cancers and add valuable data.

I own that will aid in I O and ADC development.

We believe that our AI platform will be pivotal in uncovering potential new therapeutic opportunities and also opportunities both internally and with third party collaborators.

Now getting into our drug candidates during the quarter, we reported positive preclinical data for <unk> four in pancreatic cancer and GBM glioblastoma multi form of brain cancer.

We also advanced L. P 300 toward a phase II clinical trial for never smokers in non small cell lung cancer. We began assessment of the next phase of our LP 100 program in metastatic castration resistant prostate cancer and potentially other cancers that will talk about later and prepare to <unk> 84.

For further development in blood cancers, as we have some exciting data coming out later this quarter and also 284 in sorry opportunity for next year in 2022 will be significant area of focus.

Now first as a result of encouraging results in 184 in GBM and pancreatic cancer. We were granted orphan drug designation and are receiving orphan drug designation gives us several benefits, which many of you know about market exclusivity for seven years eligibility for tax credits for qualified clinical trials done here in the U S.

This waiver marketing registration application fees reduced annual product fees and assistance in the clinical protocol as well as review hopefully in an expedited manner. These real massive massively important because they reduce our burden of development and they give us increased commercial protection two very important areas that investors should look.

As positive early validation, we accomplish both this past quarter. We continue to look at orphan designation as an important milestone, but also a validation of our novel AI driven approach.

We also submitted an abstract.

With Doctor Igor Astrocytes and established NCI funded physician scientist is also co leader of the Marvin and can Cheddar Greenberg and critic Cancer Institute at Fox Chase Cancer Center and that was accepted for presentation at the ACR virtual conference in pancreatic cancer, we release data about.

The abstract and about the work that was designed that showed the efficacy of 184 and multiple.

Mice models.

And it showed increased efficacy.

Potentially as a synthetic lethal agent in pancreatic cancers that also harbored some kind of a DNA damage repair deficiency and our chief Scientific officer for sure Bob will talk about that later. This is an area that is particularly unique and we're continuing further development because it provides us a roadmap for <unk>.

Prioritizing additional cancers, where we can potentially develop first in class solutions or show significant improvement over the existing standard of care outcomes.

<unk> wondering if we're also showed potentially best in class efficacy in pancreatic cancer with a unique mechanism of action.

The study that we did observe that <unk> 84.

Not only had.

Very good effects in pancreatic cancers, but also in pancreatic cancers that were resistant to standard of care drugs.

We also showed very importantly, using CRISPR and gene editing that the biomarker that we had predicted through radar does actually directly linked to the anti tumor activity of 184. This is <unk>, where we saw not only.

Just really exquisite.

Activity.

Once <unk> was there, but we saw really no activity.

It's almost <unk>.

<unk> White scenario, if you look at the charts.

We believe we can exploit this biomarker mechanism in various tumors beyond pancreatic cancer in the future and very importantly, again take a biomarker driven approach to selecting and developing the trials.

We are now in discussions in the design of the first in human clinical studies for 104 in collaboration with Fox Chase other kols in the pancreatic cancer treatment landscape, we plan on <unk>.

Dr. <unk>, who will tell you we've initiated IND, enabling studies.

And those will then form and guide or phase one human trials.

Next year once we finish that IND application.

I'm also very pleased to announce that we will be hosting a virtual KOL event on for one <unk> one <unk> hundred 84 in pancreatic cancer with Doctor eager Astro soft and Kishore Bosnia on November 18th World pancreatic cancer day, we'll announce the details of this event later this week.

We also reported very importantly in another.

What we feel is a multi billion dollar global indication against and trucks will cancer GBM Glioblastoma.

<unk> hundred 84 was able to significantly improve survival in animal models.

Particularly meaningful way. This study was done with Kennedy Krieger and Johns Hopkins University and results of this study are expected to guide the clinical application and focus of this drug candidate.

Now our next phase as we expand in the next phase of the work with Johns Hopkins and Kennedy Krieger, So look at a very important observation.

And that is that we've looked at in silica that LP 184, it can be an effective treatment in glioblastoma, which we've now seen in the lab and we've proven that in mice and we plan on taking this into humans next year, but one important observation is that we think that it can be an effective treatment in GBM, regardless of MGMT status of DNA repair it.

Design that gives you not only a status of the cancer, but potentially actually gives information about.

Its ability to respond to TMZ. We believe that this has significant potential to provide a much needed alternative to the standard of care drug <unk>, especially in GBM that over express MGMT, which is about 50% of GBS. So this is a major population that needs a new drug.

Choice. These patients that are over expressing MGMT are generally unresponsive to TMZ and then new therapy options. So development of an agent with efficacy in GBM, regardless of MGMT status would be an important advancement towards addressing this critical gap and we believe as a molecular pathway that can.

Be exploited elsewhere.

Our current and silica analysis actually shows that <unk> hundred 84 should work regardless of the status, but actually interestingly enough actually shows increased sensitivity and many MGMT.

Cancers.

Now we also will plan on launching additional studies for the ADC program in Q4.

And we expect to have data during the second quarter of 2022 for our ADC program and to a few specific designations.

Unlike conventional cytotoxic agents or chemotherapy.

Or even some targeted therapies that can damage healthy sales or have toxicity toxic side effects adcs are targeted medicines that can deliver for the chemotherapy or targeted molecular agent to a very specific cancer cell through the ADC connecting the ADC and the right molecule is a little bit of a science and art to the linker.

Now we're up to now we've been working this year on protecting this and we believe we can take advantage of the high potency of our molecule and the superior specificity of some of the antibodies that we have selected we believe our ADC program represents a huge market opportunity.

Two out of the four largest oncology licensing deals last.

Last year, we're in ADC assets, and it's clear that Adcs will continue to be a critical part of the therapeutic armamentarium against cancer and its area, where our AI platform is only becoming.

More relevant and more powerful.

Turning now to <unk> 300 candidate we've entered into a strategic collaboration deep lens to digital health care company enables on one thing that's faster recruitment of the best suited cancer patients that meet our protocol. So we're leveraging their AI clinical trial technology Viper to basically create a unique end to end.

<unk>, where we're using.

Basically develop the drug but then we're using AI to actually find the patients. So their technology was able to come through thousands and thousands of records electronic medical and health records to understand the criteria that allow us to match the right patients in our case never smokers with non small cell lung cancer that are chemo 90.

<unk>.

And our relapsing from Teekay.

Now we have experienced some supply chain and sourcing issues caused initially by COVID-19, and then eventually seeking into global shipment and equipment availability and then sourcing some backup equipment, so were delayed and finalizing our manufacturing, but we are planning to launch a 90 patient phase II clinical trial in the U S and.

Near future, meaning later this quarter early Q1 in non small cell lung cancer focused on never smoker population there are no other.

<unk> focus in this population and we believe we have a unique protocol with a very clear.

Selection list for the patients.

So we're now planning on enrolling about 20 sites in the U S and we believe we can select four to five patients at each of these sites never smokers and fairly quickly.

Our existing AI platform allows us to predict drug outcomes and the fiber platform allows us to use AI to find the appropriate patients and proactively suggests patients that can match to our treatment.

This will reduce the timeline next year and importantly, reduce the cost.

We will always intend to really exciting collaborations with like minded companies or companies that are leading leaders in their industry. One such was code ocean or leading computational research environment for sharing scientific discoveries so not on the patient side, but on internal operation side, two very different areas, but code ocean.

Allows us to share scientific discoveries and a more secure more transferable manner and allows us to do it internally and externally with our network of collaborators that allows us to manage our external data and our code with simple ease in a much more cost efficient environment.

And it already takes our radar platform and adds new efficiencies in terms of development time and cost. So we think this powers our platforms for faster more collaborative discoveries not only internally as we have distributed teams, but also with our collaborators at major research institutions.

As evidenced by our progress this quarter again, not only clinically but also across any number of measures.

We remain very excited and committed we've announced some exciting and positive data as well and we believe that these advancements are the types of enhancements that are needed to change the cost and the risk associated cancer therapy development.

I'm also pleased trip.

Report this quarter that HC Wainwright investment banker has initiated research coverage in lantern and we remain committed to growing awareness of <unk> within the investment community, especially with a number of upcoming milestones that we have.

A lot of progress in our <unk> program, which for sure will talk about progress in the IND, enabling studies for our ADC program and also we'll have results in 184, and a number of indications, including pancreatic bladder and GBM in the coming months.

So we have a lot of data to share, but also we have continued to show good financial discipline and I'll ask David Margrave our CFO to provide an overview of our third quarter financial results David.

Thank you Panna and good afternoon, everyone.

I will share some of the financial highlights from our third quarter of 2021.

We ended September 32021.

We had a net loss of approximately $4 1 million.

Or <unk> 36 per share.

For the quarter ended September 32021.

<unk> to a net loss of $1 7 million or.

<unk> 27 per share.

For the quarter ended September 32020.

Research and development expenses were approximately $2 96 million.

For the third quarter of 2021.

Compared to approximately zero point $6 million for the third quarter of 2020.

The increase was primarily attributable to increased manufacturing related expenses.

And expenditures to advance and expand the company's product portfolio.

General and administrative expenses were approximately $1 2 million for the third quarter of 2021.

Paired to approximately $1 1 million for the third quarter of 2020.

The nominal increase was primarily attributable to increased business and corporate development expenses.

Legal and patent related fees.

And general and administrative related stock option expenses.

Our R&D expenses for the third quarter of 2021.

We're approximately two five times the amount of our G&A expenses for the same third quarter 2021 time period.

This reflects our continued focus on advancing and expanding our product pipeline.

Our team continues to be very productive, especially as we might migrate to a hybrid work environment.

We currently have 16 employees, who are primarily focused on leading and in advancing our drug development biology and data science efforts.

We see this number expanding slightly in coming quarters as we add additional high caliber multifaceted individuals to help advance our mission.

To date, we believe we have effectively managed the impact of the COVID-19 pandemic on our operations.

Recently, the timing of manufacturing for our <unk> 300, and <unk> hundred 84 candidates has been impacted by supply chain delivery issues as <unk> mentioned.

Which has extended the time to launch our planned phase II clinical trial for <unk> 300, and.

And extended the time to commence IND, enabling studies for <unk> 184.

Nevertheless, we are making continued progress despite these hurdles.

As of September 32021.

We had approximately $11 2 million shares of common stock outstanding.

This includes approximately $4 9 million shares that were issued in our January 2021 follow on offering.

At September 32021, we also had outstanding warrants to purchase 298204 shares.

And outstanding options to purchase 801588 shares.

These warrants and options combined with our outstanding shares of common stock.

Give us a total fully diluted shares outstanding of approximately $12 3 million shares as of September 32021.

Our cash position.

Which includes cash equivalents and marketable securities.

September 32021.

$73 8 million.

$73 $8 million. This balance is expected to carry us into 2025.

We believe our solid financial position will fuel continued growth and evolution of our radar AI platform.

Accelerate the development of our portfolio of targeted oncology drug candidates.

And allow us to introduce additional targeted product and collaboration opportunities in a capital efficient manner.

Thank you and I'll now hand, the call back upon at Ana.

David Thank you very much I'd.

I'd like to now invite our chief Scientific officer, Dr. Kishore bought them.

To provide some detail on the growing data and excitement on some of our early stage programs.

Also we'll be sharing data for the first time in several of our programs and some insights during this call. So <unk>. Please go ahead.

Thank you.

I'm excited to report the initiation of IND, enabling studies for them it will be 184.

Our first animal.

And then correct toxicity.

And dose range finding studies are expected to begin in the next couple of weeks. These.

These studies are projected to be completed by April paving the way for us to take out 284 capability.

We continue to build on more evidence supporting the uniqueness of our molecule LP One April.

Moving forward with data from the previous quarter.

Efficacy in pancreatic cancers, we now have direct evidence of enhanced efficacy in pancreatic cancer.

Specific mutations that affect the transcription of a couple in Florida.

Possibly.

The transcription couple of nuclear that excision repair pathway as a specialized possibly that cells use to repair DNA.

That's up from damage that blocks transcription.

Our drug exhibits.

The incentive you would need to cancel that have damage insert genes.

That are a part of the <unk>.

An example of this.

Correlation between the <unk> phosphate is provided in this slide what you can see in this slide is that if a cell is a lifestyle that has no mutations in any of these box basis depicted by the Blue how does that mean in line on the top.

The self satellites as well.

If there are mutations.

Specific genes in the pathway in year, we have internal COVID-19 three genes that are part of this pathway.

<unk> and CSP.

Business.

And that'll be 184 in these cells.

It'll be what 84 synthetic lethal to the south and the south start.

Whether it be simply using a CRISPR based ARCC.

Again, he said before it is the product.

Absolutely.

Using crystal basically RCC towards deadlines, you looked at the model, we demonstrated a doubling of the efficacy of LP when any Florida.

These tumors.

So these.

Data.

March quite well with other data that I'm going to show you in the next slide.

Could you update in prostate cancer models and here what we have done is we have taken prostate cancer models.

Downregulates, it, but I've got to buy using such R&D. So this cell.

<unk> are slightly different than this.

<unk>.

The subsidy that was shipped showing earlier.

We added homologous recombination deficient yourselves versus previously I wish I knew the nuclear excision repair nutrition sales Nonetheless.

South Center homologous recombination deficient as you could see.

In the left hand panel.

Donlin regulation of breakout too.

Increases the potency of LP wanted to report and told this is significantly greater than the effect. It has on these cells.

The increase is roughly about $1 seven fold.

The uniqueness.

LP what lies in.

These two aspects.

Not only does it target cells that have nuclear exclusion prepared efficiency, but it also have target cells stood up on all of US the combination of the bad news.

This.

The target date.

Phosphate so I hope everyone is very unique.

And does not like either with known alkylating agents are non PARP inhibitors. We are really excited because this allows us to utilize that'd be one any thoughts about Hawaii.

<unk> systems.

During this quarter, we further spending will be 184 positioning part of it.

Their central nervous system.

A typical <unk>.

Right.

We've got a sense that this tumor would be an indication from radar data.

Suggested to us that we wanted to point will be very sensitive.

Those cell lines that have a deficiency of smart.

ERP is happens to be a tumor.

That is driven by a division of smart be one which is a CRO magnon Brody be followed these clues and.

<unk>.

If it did by this amazing data and as you can see in the <unk>.

Ralph.

The panel on the left which shows you tumor growth.

The presence or absence of LP, what any fall in mice implanted DRP the Blue line shows you.

Tumor would grow without the drug.

And the Red and the Green line shows you the regression of the tubular.

<unk> hundred 84 was injected EBIT as a dose at the very very low dose of two milligrams per kg for linzess.

The right hand panel basically gives you a sense of the size of that.

But it is not treated.

Roughly doable.

Yes.

<unk> five <unk> dose and in mice that are treated.

Barely any tumor much less than two centimeters.

Our GBS Tony also continues to gather spin.

And at this time.

Very excited to report.

That.

When we look at LP 184, compared with <unk>.

TMC.

For each of the JV.

Can be used to score the bio availability the CNS.

Okay.

Bears quite well with D&C either for us.

As Matt started in cynical analysis, or we do have three DS.

Cell culture Lithia assay.

Let me go into the Mic just that'd be 184 and ask what amount of help me what have you for each of the.

Each of those price AVR give us confidence that LP wanted before would be excellent candidates for CNS bio Liberty AD knowing that it affects our topic models of GBM.

We are really excited.

With the help you wanted to for clinical areas of GBM.

Yes.

Obviously these data allowed us to move forward and update OLED designation orphan drug designation for GBM and the previously discussed allowed us.

And also have that designation.

Pancreatic cancers.

Got that.

The data that I showed you about ERP has now allowed US also to more forward and applied for orphan drug designation as well as pediatric rare disease drug designation for the Herc indications.

During this quarter we have.

Delineated based upon in vitro studies, some very exciting combinations that will be once again. This was driven by a lot of clothes, we get both of them.

Wet lab studies.

From radar and basically we have identified.

Approved compounds that we can combine LTE 184 and <unk>.

Now <unk> 184.

Yes.

Two.

To affect.

Even two months they don't have any obligations in the same way as if you must love it.

Sure.

Our molecule <unk> hundred 84 continues to progress through better.

Clinical understanding of these combinations I will now turn to a new molecule do it before and we are updating additional indications where we can fill unmet clinical gaps in the next months, we will begin an advanced collaboration with a well known amateur oncologist from Duke University.

We will begin animal studies.

Range of metallurgical cancers, including mantle cell lymphoma, diffuse large b cell lymphomas and others.

In order to further fine tune and defined.

The most interesting Thats us.

We will proceed to <unk>.

This will give us greater concentration of the subtypes of the blood cancers that radar and remove that studies are predictive.

Efficacy.

Additionally, this data will also provide us safety and efficacy of dosing studies, allowing us to move quite rapidly.

The 284 program.

During this past quarter results from both studies was accepted at several scientific conferences, including.

The ACR pancreatic cancer conference.

At present, the data from the benefit to cancer.

We will be present data on the video customers.

The idea of Neuro oncology conference later on in November and 284 data will be present data at ash.

<unk> and <unk>.

Similar.

Hi, Matt.

Yes.

Okay.

Yeah.

Yes.

Okay.

Thank you for sure.

Before I open it up to questions I'd like to provide a brief recap.

And also discuss some of the anticipated milestones.

As you know, we're pretty very confident and the launch of multiple human clinical trials over the next 12 months for 184 and 301 hundred.

Also looking at the ongoing growth of our radar platform as well as committed to bringing the ADC programs further along and through IND, enabling studies.

We also believe that with our network of strategic collaborators that we'll be adding additional kols and collaborators to that we'll be able to generate positive new data.

And more importantly, generate new programs through licensing opportunities, both with radar and also our existing drug portfolio.

We believe that 2022.

Would be a fairly transparent national year for lantern.

We do expect that the platform will grow that the trials will initiate and most importantly, we will continue growing our very experienced.

<unk> team.

<unk> is committed to bringing these drugs and more importantly, doing it faster and cheaper.

So with that I'd like to now open up the call to any questions.

Thank you Panna, we've ever seen for questions from analysts and our first question.

Question comes from how 'bout Bill Collier.

Our annual golf, our radar in terms of number of data points of what sort of visual demonstration Maui E. During the upcoming Investor day.

Thank you Kyle and.

Killer from Colliers Great question.

We had set out to reach.

When we came into 2021.

With $1 2 billion data points, we thought we'd get to five or six by the end of the year, we updated that middle of the year or two eight to 10.

Now that we're 10 four.

We're thinking next year, we'll get to 20, maybe.

Maybe slightly north of that but we're.

Also looking at new types of data as I mentioned and we're also looking at the.

The complexity of our algorithms that's one of the big areas of focus is the machine learning development environment.

So in terms of numbers that I believe will be at 20 plus next year.

And maybe even faster.

In terms of the.

We do have some really exciting visuals.

Visualizations of the output of the platform we call. These radar insights internally we routinely review these during our key meetings, we expect to have an analyst day.

Trying to figure out the right time, and the right kind of environment for that.

So sometime in December January where we will showcase many of these radar insights and also a peek at the kind of a development environment. So yes, we will have some looks at what radar it looks like and feels like but also in terms of what is the data and what are the nature of algorithms that's probably the most.

Horton thing.

So thank you for that question.

Next question are you still evaluating new partnerships.

<unk> equity.

And how long that need a therapeutic partnership program.

Great question, one of the most important reasons for making the $10 billion announcement was two <unk>.

Okay. So we're continuing to develop the platform for much wider use than just our own and so we think that now is the right time for us to even be more aggressive we've had very good experience with our first partner Actuate therapeutics, that's given us a great template to think about how to approach additional partnerships with both emerging companies.

And we've had actually some interactions with some bigger biopharma as it gives us very good ideas and process that we need so part of today's announcement was really to get.

Onto People's radar so to speak.

That we're going to be much more aggressive in seeking radar driven biopharma collaborations, where we can take equity or milestones.

As part of our growth.

Question is how much faster do you anticipate enrolling the phase two trial now that you've inked a collaboration agreement with <unk>.

It's a great question and I know that.

David probably won't want me to commit to any number but I can tell you what we've learned in the process, which we believe is a template.

For what we're trying to do with deep learning.

We spoke to many people in the Biopharma industry as part of a reference checks for <unk>.

Not only the deep learning technology, but other patient recruitment technologies that sift through patient data.

And we found that the people who use the deep lens technology, we're able to.

Talk about enrollment rates that were two times higher faster than they expected. So if you imagine a 18 month enrollment youre looking at nine months 12 months enrollment looking at six or seven months. So we're hoping that we can be in that same ball ranked ballpark.

And but to be honest since we're going after probably a group that has less competition, which is the never smokers.

I think once people know about it I think there is a very high likelihood that they meet all the clinical criteria.

That we could see very good acceleration because of that.

Thank you.

Yes.

Thanks. Our next question comes from Michael <unk> with H C. Wainwright.

The Atlanta, presenting a poster at ash on what will be the topic.

Okay.

It's a good question from H C. Wainwright, Thank you Michael and a narrow.

We're not allowed yet to give the date and title XI right Kishore.

That's still under embargo I think till the end of this week. So at the end of this week, we'll be lifting that and talking about the presentation.

Thank you.

Next question any progress on doing the L. P 100 clinical trial after the buyback.

Yes, great question. So we have some very good promising data in the 100 trial not only about the.

Median overall survival improvement that we've seen in the nine patients that were dosed <unk> hundred.

But we also have seen publications now that support the role of L. P 100, and DNA damage repair pathway deficient tumors like bladder cancer, namely bladder cancer actually with <unk> three mutations.

We're thinking about some modifications to the trial.

To allow us to attack both groups of patients.

But also to refine and simplify the signature that was used to potentially guide their enrollments are in the process now of doing the modifications, but also now exploring bringing the drug substance in the trial to the U S for some of the indications including bladder.

We will have more timing on that I think in Q1 of next year.

A question on furniture.

Any progress on the trial or <unk> 300.

Yes, so I think most.

We're hoping to submit the protocol and the final final manufacturing dossier separately, but after under advisement and because of the manufacturing delays. It's been advised that we submit both together.

So we're hoping that over the next 30 45 days, we'll have clarity on the submission but were already gone ahead and beginning to look at clinical trial sites and the types of patients. So.

The supply chain issues around manufacturing has really held up the final submission to the FDA and so I'm, hoping that happens during this quarter early January at the latest.

Thank you.

Next question will come from John vendor will fill that.

Hello, Codell shandy.

The R&D program.

That's a great question.

So.

Third Ocean is again a development environment.

Container arises the code the data.

And the environment that you use whether it be our python or something else and it puts it in the secure package more importantly time stamps what youre doing so if we can go back and we can take a look at who is doing is doing or wasn't doing what.

Whether it be internally or externally people, who don't have to manage the creation of <unk>.

Pipelines the instantaneous.

Securities might be required to go from one institution to another so a lot of these things are simplified.

So with collaborators, we expect a pretty significant increase in the efficiency of doing work internally. We also expect efficiencies that allow our team to focus more on the code and the analysis and less on the management of the development environment and so this container type of approach I think increases the one of the most important.

Things that's needed machine learning, which is reproducibility.

Produce ability can be very challenging.

To know what the algorithm was exactly what language on on what the input data as were what the hyper parameters.

Or we're not and what was the raw data that was used ultimately saw that now is handled in an automated fashion. So it reduces the Iot burden and staffing burden on us and it also reduces the expense. So it's an important development internal operations type of collaboration but we.

Do think it is a competitive advantage, we don't see many of our peers, having a sophisticated whereas mature.

As a development environment for machine learning as we as we have.

Well. Thank you. This now concludes our question and answer session.

Turn the call back to panel for closing remarks.

Thank you Natalia and thank you for the great questions.

So as I mentioned, we're very excited for the outlook for lantern.

We think well make significant progress next year and throughout this quarter. We've got a lot of data coming out this quarter at the society of neuro oncology at Ash with our ATR T program and we believe that this data and the progress will translate into Biopharma deals, where we can partner or license our portfolio for several hundred.

Billions and ultimately Thats really the way to generate value for our investors is to take our programs and to partner or sell a license to now so we look forward to providing further updates as the developments unfold and also to meeting many of you in person in the coming months or in 2022.

So thank you all and with that ill turn it over to our host Nicole and finance.

This concludes today's earnings call and webinar, we will look forward to pushing you on our next corporate <unk>, which will be on Thursday November 18th on royalties.

Hey.

This webinar will be covered by doctors P. Goris Natura from Fox Chase cancer center, and tissue or backyard, Tom Lynch from pharma.

We'll release additional details in the press release later this week and thank you so much everyone for joining and have a great Thanksgiving.

Thank you.

Thanks.