Q2 2023 Exscientia PLC Earnings Call
[music].
Hello, everyone. My name is Abby and I will be your conference operator today.
At this time I would like to welcome everyone to accent chairs business update call for the second quarter 2023.
Today's call is being recorded and all lines have been placed on mute to prevent any background noise.
After the Speakers' remarks, there will be a question and answer session.
If you would like to ask a question during that time simply prestige Starkey followed by the number one on your telephone keypad. If you would like to withdraw your question Press Star one a second time.
Thank you and at this time I would like to introduce Sara Sherman Vice President of Investor Relations. Sir you may begin.
Operator, our press release and 6K were issued this morning, with our first half and second quarter 2023 financial results and business update. These documents can be found on our website at www dot investors thought extend she had dot AI along with the presentation for today's webcast.
Before we begin I'd like to remind you that we may make forward looking statements on our call. These may include statements about our projected gross revenue is this models preclinical and clinical results and business performance.
Actual results may differ materially from those indicated by these statements unless required by law extension does not undertake any obligation to update these statements regarding the future or to confirm these statements in relation to actual results.
On today's call I'm joined by Professor Andrew Hopkins, Chief Executive Officer, Dr. Micron's, Chief Quantitative Medicine Officer, Dr. Nicholas Crown E V P precision medicine, and Ben Taylor, CFO , and Chief Strategy Officer, Dr. Dave Hallett, Chief Scientific Officer will also be available for the Q&A session.
And with that I will now turn the call over to Andrew.
Thank you Sarah.
The first half of 2020 free have seen a major step forward in our development pipeline with four compounds progressing incentive controls.
We recently dosed the first patients in both elucidate our phase one two trial about CDK, 7% EBITA GTA Exs 617 partnered with GT apparel and ignite our phase one two trial about each wave of saps antagonist, Exs 21, five or six.
Earlier this year two partnered compounds a PK see feature inhibitor in licensed by Bristol Myers Squibb for immunology and a bi specific psychiatric compounds designed for Sumitomo pharma also started phase one set of controls.
We have also made significant progress in other parts of our pipeline, notably we initiated a prospective observational study called X linked one evaluates and predictive power of a precision medicine platform in ovarian cancer.
The study has the potential to validate further our platform why do you use across a variety of solid tumors.
Building, a robust pipeline and advancing our wholly owned and partner development candidates is a testament to the strength of <unk> business model capabilities and strategic collaborations.
As we continue to bring differentiated compounds to the clinic.
The strength without AI led ends when discovery process.
We are solidifying our leadership in AI enables drug design and development.
This summer we also opened our automation lab outside Oxford here in the U K.
Which will enable us to integrate AI and automation to drive past the high quality experimentation.
Built in our own hardware and software solutions to automate a wide range of experimental laboratory processes, including chemical synthesis, and biochemical and biophysical screening.
We expect all new capabilities to be online later this year and we look forward to sharing our progress.
The integration of AI with automation to drive ultimately autonomous experimentation as we believe the next frontier in improving productivity in drug discovery.
Oh speaking a moment about our core capability to adapt and rapidly integrated technological advances into our broad platform.
Technology is at the center of our strategy to change the way drugs are invented undeveloped.
To maintain nimble product development and a technology platform, we have promoted free industry leaders to our executive Committee.
Has the Charlotte team as our new Chief AI Officer, Dr. John <unk>, as our new Chief data Officer, and Eileen James Brown, Our Chief Information Officer, all of whom are proven leaders and innovators in their fields.
We also appointed Professor Francisco My core to our board of directors and my extensive experience in cancer research using computational a mathematical methods will be invaluable to us as we continue to advance our pipeline and platforms.
We remain well capitalized with $509 million in cash at the end of a quarter. This provides us with several years of runway to advance of near term programs.
We look forward to achieving our upcoming milestones and serve in more detail our clinical development plans and progress in the second half of the year.
Oh computational platform designed to learn and solve problems that have been too complex for traditional methods.
Order to make that process faster and more efficient, we must be able to generate relevant high quality proprietary biological data to inform our models.
The wide variety of digital data, we generated reflects the complexity of geology.
This integrated data is shared across our models to drive system Luna and better results.
Importantly, our modeling is data agnostic and our generative design technology is model agnostic. This is important as target product profiles. We designed two are.
Not defined by one data types, such as a protein structure or high content screening, but by a wide variety of data types.
Some of our experimental systems are the first of a kind such as a precision medicine technology using AI to assess life patient samples to predict patient response, we conducted a prospective clinical trial showed that was able to improve outcomes in selecting the right drug for specific patients.
Other capabilities are focused on capturing the most state of possible from experiment and integrating it real automation. This gives them the advantage of both understanding the model system as well as speed and cost efficiency.
The power of our competition platform is and its integration and Parex.
There is no single algorithm with defined so operations, but a wide variety of proprietary algorithms and datasets.
Our platform is constantly evolving and our capabilities have expanded as we invent and adopt new technology.
The overarching technological approach that unifies, what we do from discovery to development is model driven adaptive learning.
We pioneered the use of January to the eye and active learning to design drugs. We continue to build on our leadership position in both capabilities. We have now also built thousands of predictive models.
In power, our workflows to evaluate novel chemistry in a virtual environment.
In addition, we've now built a world class physics based platform that we integrate into our generative and modeling systems for structural analysis.
It is a natural next step for us to integrate AI and physics based design methods together.
Over the last year, you have now seen how we apply the same methodology of model driven adaptive learning to improve clinical trial design and execution, we utilized clinical trial simulation to better understand the most important variables in clinical trial design.
We then create a statistical plans that evaluates results in real time as the trial progresses notice to make better decisions sooner on the clinical trial progress.
We've also laid the groundwork to integrate a precision medicine biomarker capabilities into our clinical trial execution in the near future. We believe this can lead to far higher probabilities of success as we are able to better understand which patients will respond to our drugs.
Most importantly, we have demonstrated that our platform works.
Our AI based platform has delivered eight development candidates in other words novel drugs that have or are expected to enter clinical trials.
The physical properties of these drugs can be clearly measured and that shows they have achieved complex design goals, where traditional methods did not.
Importantly.
Our generative molecule design technology has been core to deliver NBA to development candidates sofa.
Cynthia pioneered reuse of January to the eye and active lead into a better drug discovery. Since we first published a revolutionary approach and believe in the scientific journal nature.
The combination of our deep bench of experts in both tech and drug discovery.
Allows us to lead the field with our proprietary algorithms and deep learning models.
We have also demonstrates that we can rapidly adopt new technologies with customization for our platform as we learn and grow as a company.
Example, we believe a physics based modeling should be integrated into AI driven systems to take advantage of agenda to power and multi prioritization optimization that AI allows.
In a period of <unk>.
Just about a year, we were able to deliver a physics based system that benchmarks in line with industry leaders. However, because its purpose built our systems, we're able to customize it for better results was that our own architecture.
Even now working on how it can be seamlessly integrated with our generative algorithms.
Similarly, we have industry need and protein modeling capabilities and optimize the antibodies and other related biologics. This allows us to use January two methods with de Novo biologics design at scale and we tell you more about this program later this year.
Before turning it over to Mike crowds of Nicholas call I'll now take a moment to highlight where we are though clinical and <unk> clinical programs and the important progress we've made this year.
As you know by next year ex Cynthia has committed to advance of at least four molecules are meaningful economics in the clinical development, we well on our way to achieving this goal with five programs either in clinical stage or enter into IND, enabling studies as of now all of which have been designed to use now a M ply.
Fall in much shorter timeframes and industry average and we believe maximum quality use now AI late discovery platform.
Both our CDK seven EMEA toy programs and now in phase one two clinical trials with patients enrolling in similar timelines ignite.
Ignite.
Is a phase one two clinical trial of 546 hour HOA receptor antagonist in combination with anti PD, one therapy for renal cell carcinoma, non small cell lung cancer.
Elucidate as evaluation a novel CDK seven inhibitor 617 for the treatment of advanced solid tumors, both as monotherapy and in combination with standard of care Elucidate phase one two trial will evaluate the safety efficacy and pharmacokinetics of six from seven across multiple ascending doses.
In six indications, including head and neck cancers, pancreatic cancer, non small cell lung cancer, and HR positive <unk> negative breast carcinoma in ovarian cancer.
And brophy elucidate and ignite trials, we use simulation guided trial designed to determine the operating characteristics and adaptive design to evaluate statistical results in real time when the trial is wanted.
Both of these programs demonstrate the true hallmark of an extent Tia drug candidate for <unk>.
<unk> designed compounds using AI and ml combined with Novo patient selection strategies with the goal of identifying the right patient over white drug.
Our precision designed PK see feature inhibitor for free one eight partnered with Bristol Myers Squibb continues to advance through phase one clinical trials in the United States. This is another example of using our AI driven technology to design the gains complex multifamily or challenges where others have failed.
Our two wholly owned precision designed L. S. D. One on multiple inhibitors 539, and 565 are continuing to progress with IND, enabling studies and we'll share more detail on our clinical plans later this year.
I'll now turn over to Dr. Mike <unk>, our chief quantitative medicine answer.
Talk a bit about our CDK Simon program.
Mike.
Thank you Andrew.
We'll highlight more details of our <unk> seven program, how we are optimizing our clinical development strategy and how we choose the patient population that may benefit from this molecule.
Additionally, alongside evaluation of 617 and be elucidate trial, we will partner with GTO param to generate data on quarterly data in response to previously collected the ex vivo results.
To substantiate the value of our precision medicine platform.
Here, we highlight the design of the elucidate trial for 617.
As Andrew mentioned, we're looking at six different tumor types and we'll be studying $6 seven both as monotherapy as well as in combination with standard of care.
One thing to note is that <unk> seven is a broader biological mechanism each week.
Why are we including more tumor types and also why we are using our platform differently in this trial.
Nicholas will talk about this more.
As with ignite elucidate is also following the principles of model informed drug development.
We started with simulation work to understand the key variables and structured the phase one trial to see what dosing may be most impactful.
We're moving away from traditional three plus three designs to focus on what we believe will be more informative.
In learning about the investigational compound.
Our precision medicine platform will help us assess the best potential combinations for dose escalation.
Importantly, we don't expect to be going into specific subtypes.
Dose escalation is a good majority of patients are expected to be responsive to this mechanism of action.
Instead, we will retrospectively assess if there are biomarkers that impact the level of response in patients to help inform the phase two or later clinical development strategy.
As I mentioned on the prior slide <unk> seven as a growth mechanism that we believe can apply to a large number of cancer types.
On this slide you can see the six indications we have selected for phase one two trial based on experimental work, we have done to date as well as peer reviewed literature.
Highlighted here is the U S incidents for these indications.
Which are all relapsed refractory patient populations.
In the U S alone there are 75000 patients each year that fit the criteria for which we are enrolling elucidate trial.
One place of potential benefit for this mechanism is within CDK four six refractory patients.
Through our platform work, we believe it could be much broader and look forward to learning more in the clinic to see which patients may benefit most from CDK <unk> inhibition.
I will now hand, the call over to Nicholas <unk>.
Our EVP of precision medicine.
Walk us through how we're using a precision medicine platform with this program.
Thank you Mike last quarter, we highlighted how we have taken functional data from a precision medicine platform and combined it with matched multi omics data to achieve a better understanding of disease biology. This is bill.
Possible through our investment into state of the art next generation sequencing capabilities at our sites.
Today, we are expanding on this theme and showing that we have leveraged both functional and omics data to reveal potential combinations for our CDK <unk> inhibitor 617.
Further the <unk> program will be deployed alongside our clinical trials will be profiling for instance, peripheral cell free DNA in blood cells to enable an understanding of target engagement and allow us to study disease mechanisms and drug activity beyond our ex vivo efforts.
Specifically did we show how we used our precision medicine platform to understand the potential effects of 607 and patient samples from various cancer indications such as breast lung and ovarian cancer.
These are four of our six indications included in elucidate.
Ex vivo nearly 75% of samples show sensitivity to the $6 seven inhibitor.
This supports our notion that 617 will have an effect in a variety of patients and indications. So the work is ongoing to determine how the depth of response may correlate to in vivo response prediction.
Using our ability to measure drug response in primary human tumor tissues. We then profile different combinations of 617 and already approved drugs for potential synergies.
On this slide we have highlighted a few examples of combination of potential synergies that we have uncovered using our platform we.
We have identified three drugs with different mechanisms that have synergistic effects ex vivo with 617 in the reduction of cancer compartments and primary samples.
Further biological mechanistic validation as well as further data from different indications ex vivo has been collected.
On top of the screening shown here. We are also deploying transcript omics and functional profiling to support the discovery of potentially clinically relevant combinations through correlation of drug activity target and pathway modulation.
This is a similar approach to <unk> using omics profiling of primary patient material combined with our functional platform to reveal disease biology and targets as presented in the last earnings call.
As shown as prime medical meetings, we are highlighting that the platform has also uncovered dose dependent PD biomarkers to have shown here that we believe to be non invasive. So we can potentially show drug activity early on within the escalation study.
This is an example of two genes uncovered through Omics profiling, where one of them has also been reported by another company that CDK seven space. This.
This data adds to the use case of a precision medicine platform in the context of biomarker discovery as we aim to bring clinical relevance to all areas of preclinical research.
I'll now hand, it over to Ben Taylor, our CFO to walk us through the financials Ben over to you.
Thank you Nicholas I'll now take a minute to close with highlights from our financial results for the second quarter 2023 full results are detailed in our press release and form 6K.
I'll review the results in U S dollars using the June 32023 constant currency exchange rate of one point to $7 to the pound.
We ended the quarter with $509 million in cash equivalents and bank deposits. We believe this provides us with several years of cash runway and the resources to continue investing in our growth.
Last quarter, we highlighted cost efficiency programs being put in place and we've already seen a significant impact on our spend.
We expect to save over $30 million during the course of 2023 and more in 2024, while still delivering on the goals that we've outlined.
As expected cash inflows from existing partnerships have been limited for the first half of 2023 as we are in the middle of discovery execution on a number of pipeline programs.
We expect these milestones ramp up substantially in 2024 and beyond as we reached the development milestones for the partnerships.
We are also maintaining our guidance for two new business development deals during 2023.
<unk> remains well capitalized as we continued to successfully advance our internal and partnered projects at the same time, we are cautious in the current macroeconomic environment and intend to continue our cost control efforts through the end of the year with a focus on optimizing workflows and automation.
With that I will turn the call back over to Andrew.
Thank you Ben.
Our mission of extent here is to change the way drugs are made to create better drugs for patients faster.
Our goal is to significantly increase our probability of success within drug discovery and development for an end to end patient centric approach.
The progress we've been making in precision design important and selective drug candidates build in a clinical pipeline and advancing our owned and partner development programs gives us great confidence in our business model, our diverse team of experts with outstanding capabilities and in the quality of our strategic partnerships, we look forward.
It's continuing to meet our milestones and follow through on our commitments of bringing yet more differentiated compounds into the clinic and service strengths now AI lead drug discovery capabilities.
And with that we'll open the call for questions and answers.
Thank you.
At this time I would like to remind everyone in order to ask a question Press Star then the number one on your telephone keypad and we will pause for just a moment to compile the Q&A roster.
And we will take our first question from Peter Lawson with Barclays. Your line is open.
Hi, Courtney on for Peter and Thank you for taking our question I just had a quick one around the ignite trial can you give us a little bit more color around how enrollment is going and if it's possible to see data in the first half of 'twenty four or is it more like a second half event. Thank you.
Thank you Courtney great for you to join US today four months I'm going to hand, you over to Mike <unk>, our chief consumer medical offset too.
I'll give you a little color as you say on the nitrile.
Hi, Thank you for the question and recruitment is going well.
We on the dose escalation part of the clinical trial.
We have a dose escalation study vegetable dynamically switch into the dose expansion phase at this point, we are accruing the data on behalf of the usual approach to looking at retail through an independent data monitoring committee.
And.
So in summary recruitment is going well.
Thanks, Mike.
Thank you.
We will take our next question from Alex Stranahan with Bank of America. Your line is open.
Hey, guys.
Thanks for taking my questions just a couple from us.
First on your automation laboratory.
Looking forward to that opening.
The back half of this year it sounds like it is the goal here to supplement your current wet lab capabilities or could this actually replace.
Or amplify some of.
The research that you're doing.
And as a follow up just on the R&D spend I thought it was notable.
That you're.
But youre spending was flat year over year, what are sort of the puts and takes that went into this quarter. Given you do have more clinical studies.
Ongoing and how should we kind of think about R&D.
It's been going forward. Thank you.
Thank you Alex two great questions actually and I'm going to split the answer I'll take the first half of them automation, and then I'm going to hand, it over to Ben to give you a bit more color on the finance of the situation.
We'll be automation, absolutely we've already sort of opened up our new laboratory still continue to build out, particularly the chemical synthesis and new technology hardware that we put in place there.
The goal is absolutely to increase the <unk>.
Full experimental capability <unk> already as you might know we have very strong sort of biological laboratory here in Oxford and also in Vienna, particularly WAF precision medicine patient centric technologies are based on the old MX platforms. What we are building share and oxygen. The automation suite now is how we can transform the way that sort of AI.
Driven automation now goes to scale up, particularly as sort of a biochemical and biophysical screening approaches and also end to sort of bring in house AI driven.
Coaches to retrofit with system and actually synthesize it automated fashion many of our compounds actually that we are making in our sort of optimization design cycles. So what we do in band actually is we see this actually as a new way then all really transforming the design cycles and the time of that sort of takes actually precision systems screen.
To take place much of our work right now takes place with our CLO. So what we see then accurately is how we start to bring more of that capability in house, because we believe this gives us a real sort of piece of the advantage now in sort of the next sort of quantum leap in productivity as we say, we're really excited about last and we look forward to.
Showing you the labs, they already open and hopefully we'll be talking more about that towards the end of the year and hopefully invited many of you to come see it.
Yeah, and I'll pick up on the R&D spend first of all I think what Andrew just outlined is a little bit of our philosophy on how we are trying to.
To advance the Tac and the efficiency at the same time. So we are absolutely an innovation driven company, but what we try and do is not only have that innovation drive new ideas and how we do direct discovery, but also drive new ideas on how we can be efficient and so what we've been doing over the last 12 months.
And we've talked about this is really working on process working on efficiency looking at.
What are the important aspects of our spend versus things that are less important.
That's enabled us to take a lot of cost out of the system, while still getting to the same results and that's part of what Youre seeing in that R&D.
We're doing more we are.
Expanding our capabilities, we are investing a lot.
Across the company, but because of those efficiencies we've been gaining we actually have seen pretty flat spend.
I think we expect that to continue in the near future.
Where you might see that start to meaningfully change is when we get into later stage clinical testing those trials, obviously cost quite a bit more.
But we've actually put them in place a lot of the infrastructure to continue doing our discover.
Discovery and early development work.
With what we have.
Okay, great. Thanks, guys and maybe one quick follow up if I may just on the automation.
You noted in the PR that you've built out some hardware and software solutions sort of bespoke.
In your process could you maybe highlight one or two key examples.
Once you've actually had to build.
In house, and how that feeds into the.
The facility overall, thank you.
Absolutely no I mean, that's a testament I think for talent, we have inside expense here that if you look at our biology teams now.
Also the integration between sort of west biologist.
Software developers and hardware engineers as well when you look at our processes getting real feedback about what is the quality that we want to now generate in an efficient manner.
Two examples of that actually how we've been thinking about sort of generated in scale.
It is not in the traditional way you would think about high content screening, which usually thinking about how can I screen say 1 million compounds in one type of assay, we actually want to turn it around but we interested it is actually collecting a lot of data on a small number compound. So when we make in our precision design molecules don't get deep insights into my apology to return it.
Round denim thing how to automate spend the technology, we build some of new hardware so allow us to flex our multiplex in multiples of the data points on many different types of assays onwards compounds, it's really changing sort of the way of youre thinking about some high throughput really to have a high throughput high quality due to the diversity of data that we now generated.
So what we built in as well in terms of how to automate techniques into the physics, and where we can actually then take us through sort of a next level of really thinking of sort of modular approaches and to add analytical technologies. We're really excited about showcasing some of that sort of later in the year et cetera, as we have them start to reveal it and I think it actually been outlined.
The depth of innovation at <unk> has now taken this is actually part of a bigger picture, we see the bigger frontier now is how AI now staff to help them control and drive experimentation and Thats, where automation is key when linking those two will gap between experimentation and automated design coming together and Thats, where the ultimate.
<unk> platforms.
Thanks, I appreciate the color.
And we will take our next question from <unk> <unk> from Baron Berg capital market. Your line is open.
Hey, guys How's it going thanks for taking my questions.
First, especially since you have two preclinical programs on deck.
What's your bandwidth in terms of how many programs you believe you can internally conduct clinical trials on simultaneously just trying to think about what your capacity is.
How many internal programs are able to have in the clinic at the same time.
So that's a great question actually.
We can answer it sort of.
Paul in terms of the of our capabilities within our discovery and development capabilities and we all builds in a very flexible pipeline, that's where if you look at we had a number projects providing pre clinically across it.
Significant bandwidth you automation platform form is also increasing our capacity long term in that space as well.
In terms of how we run and developments as well I'll, let Mike to step in here as well, we have done and actually a very tight ship and that's some of the key advantages, which actually modeling for drug development and adaptive technologies also allow us to do Mike you want to give a bit of color on how youre thinking around the capacity in your clinical.
Department, Yes, absolutely. Thank you for the question so.
Andrew you mentioned the keyword in it is modeled informed drug developments before we ever start going into the clinic, we really tried to dive deep into our understanding of the underlying biology integrate information in a quantitative fashion and then huge development strategies that allow us to make the correct decision.
At the earliest time point in the most efficient manner.
The way we do this is to currently.
Plan for approximately full programs between one time to undergo this process but.
There is an opportunity to borrow inflammation across so in our efforts to apply the model informed struck development shrinking.
We have the intention to leverage learnings that are applicable from one program to the next.
Thanks.
In terms of pure numbers at any one time point on compounds to be progressing.
Okay.
Okay.
Got it and then just one more follow up from just one more follow up from me on capital allocation given the current macro environment are you prioritizing later stage programs and preclinical programs versus let's say starting new programs are emerging discovery programs or do you feel you have the resources to tackle both simultaneously.
We are well capitalized and I believe as a team we have the capabilities and resources actually to both develop the pipeline as you see and actually this year actually we have seen incredibly proud of the development. We've seen in the clinical space of our pipeline, but also in terms of where we are and there's been some explained to the lost tons.
And as well, how we manage and efficiencies in discovery is that we now start to see that how our technologies can allow us actually to potentially do mobile resources. We have now is actually from a key part of our philosophy in terms of automation and I don't know if you want to add is actually some extra color on that.
No.
Absolutely on from my perspective, so we keep a very balanced portfolio I think what it has required us to do.
Remember, we are investing behind target IP with our Sanofi collaboration and our internal efforts, we continue to move things up through our partnerships and internal pipeline, but obviously have our clinical stage portfolio. So.
What we have to do is to be really disciplined about management decision, making.
And say.
From the beginning is this a patient population that needs a drug is this an area, where we can design something that's differentiated.
And if it's not we need to be ripped.
Replacing it with something like that can be so we use our operating efficiency to be able to maintain the scale that we have.
We also need the management discipline, so that we don't get distracted and lower value projects.
Awesome guys.
Thanks.
And we will take our next question from Chris Shaw with Tony with Goldman Sachs. Your line is open.
Hey, this is Roger on for Chris just two quick questions from us.
One is could you elaborate a little bit on the the milestone payments you've previously talked about.
Wanted to better understand is it going to be more early near term in the second half of this year or more latter weighted towards 2025.
And then our second question is on 617.
Just wanted to learn a little bit more about the the deep learning component for the study from the elucidate study.
Will you be priority prioritizing any of the six indications to maybe build upon training datasets before looking at others.
Then is the goal here to really just see outcomes from an initial set of patients before moving to the dose expansion phase. Thanks.
Thank you Roger Thanks for your questions today, I am actually going to split with quest.
Questions first one to ban on the milestone payments of progression and the second piece on the 617, a precision medicine strategy to Nicholas Ben Yes.
Sure so on the milestones.
We expect the 2020 for 2025 and beyond years are going to be much more heavily weighted towards the milestones from the BMS and Sanofi collaborations. So if you think about the time period.
When we entered BMS and Sanofi. It takes a couple of years basically to start up the programs advance and reach the initial milestones and so from the timing of when we entered that you would expect 2023 to be probably the lightest year.
And then building up as you go into the future and you start to hit the more meaningful.
Milestones moving forward.
That being said, we still see several hundred million dollars of potential milestones over the next handful of years.
And are really excited about that relationship.
Even with all of the craziness in the macro environment.
Sanofi and BMS have continued to be great partners.
And with both continue to really invest a lot of time and resources behind those partnerships.
Thank you Ben and in terms of the 607 precision medicine strategy and how we apply that technology to explore that program Nicholas would you like to describe it in a bit more detail.
I think some of it in your comments earlier.
Thank you so much for your question so in our preclinical work using our primary human tissue platform. We have shown that our molecule actually has activity of <unk> across a broad range of tumor indications.
Some of which we are exploring in our clinical studies, maybe Mike can comment about this.
Well.
In terms of prioritization.
We are currently exploring different hypothesis of how we could further which would this down.
Stratify patients.
Alongside our clinical trial, and then really be guided by our data to go from the exploration that we're doing at the moment to potentially focusing on a few more indications.
Okay.
The other thing is that as vast as well is of course was Nicholas presented earlier of course, using our platform helped us to understand the prototypes potential combinations as well and we hope to move into X. We certainly see that as part of a key long term strategy.
Okay.
Mike anything to ask.
I think.
Because you said it all to decision problems.
One rich.
Which indications to pursue.
Second which combinations within those.
To integrate across all information both on.
Therefore, the outcomes and biomarker outcomes to make the correct decision.
Okay. Thank you so much.
Thank you Roger.
And we will take our final question from Vikram <unk> with Morgan Stanley . Your line is open.
Hi, good morning, Thanks for taking our questions. We had two one just to follow up on the topic of partnerships.
I'd, just like to learn a bit more about how youre thinking about the potential for more partnerships over the next call. It six to 12 months.
And how your views on BD might have evolved if at all over the past several months and what you'd be looking for in new potential partners. If you have those discussions and then secondly on.
The topic of biologics.
Just wondering if you could provide us an update on how those efforts are progressing internally and when you might be ready to discuss the biologics capability you have been building a bit more externally. Thanks.
Excellent. Thank you for your question today Vikram on the first one on partnerships actually I want to introduce.
Dave <unk> CFO to talk in a bit more depth about how those are developing because David obviously intimately involved with the ongoing projects and new projects under discussion Dave.
Dave do you want to run a bit more color on where you see the partnership position right now.
Thank you Angie.
With the.
Was it kind of makes it.
We have in progress.
Yes.
The collaboration.
Thanks.
Eddie.
Yes.
Sure.
And youll kind of collaborations.
Okay across different therapy areas.
And we kind of please hey, Dave.
We're having some trouble hearing you do so.
Maybe I'll just jump in really quickly on the partnership side.
Okay, then so thank.
Thank you.
So on the partnerships.
Obviously, we continue to give guidance that we expect two new partnerships over the next by the.
We ended the year.
And so we absolutely.
We are confident that there is a good business development environment out there now that has evolved quite a bit over the last 18 months and I think we've talked about this a little bit before.
DRA and some of the other macroeconomics had a chilling effect not unnecessarily.
Pharma.
Value, adding opportunities, but really on decision, making inside of the farmers I think what we've seen is a real reengagement from the pharma community and so a lot of those discussions that were ongoing.
Over the last several months really gained traction.
Traction.
The higher levels inside of the organization. So we've seen a lot of engagement out of the senior leaders of large pharma and new inbounds coming in to US now Interestingly I think.
The scope of where those partnerships may go has expanded quite a bit.
From two years ago, three years ago, when almost all of the discussions we're really about.
How can we have a number of pipeline programs coming through I think what we're seeing now is really a lot of the pharma are interested in more advanced.
Technologies and capabilities, which we love because that plays right into our strong suit of having an integrated platform.
Obviously I'd be remiss, if I didn't comment on the tech side as well.
We've seen some really interesting movements from big Tech.
And that's also very interesting potential partner base for us.
They have a different set of priorities.
<unk> pharma do.
It makes them.
Potentially open to different types of partnerships in our large pharma wood.
And we will see where all of that goes over time, but I think.
We feel much better about the business development outlook as a whole.
From where it was even six months ago, we've really seen a lot more excitement.
Thank you Ben and Victor just to add.
Some thoughts on where we are with the biologics platform. If you've been following sort of the conference circuit, we've actually been making quite a few sort of presentation.
Posters on the tech development of algorithms.
They are performing and benchmark in it.
I can start and.
I'm incredibly progress actually in how the outcomes are now coming together on that space. We've also been building out automation as well as how are we thinking of generating data and the.
Biologics platform as I sort of hinted out earlier will be sort of.
Selling you further about some of these sort of automation lab approaches and new ways of conducting surpasses looks department.
We've been building and hopefully to be unveiling bats.
Towards the end of the year importantly, as al. We are also being undertaken sort of the first sort of proof of concept projects as well and bringing all this technology together.
We hope to bring you sort of news on that as well in the second half. Obviously, you are now and to give at building out new capabilities. Both <unk> AUM actually is to guide you to sort of design within apps. So we're incredibly excited.
I do think that 2024 onwards, you will start to see.
Biologic stomps contributes to the extent your pipeline as our confidence grows now in this space.
Got it thank you.
Thanks Rocco.
And ladies and gentlemen, there are no further questions at this time, so I will now turn the call back to Mr. Andrew Hopkins for closing remarks.
Thank you operator, and thank you to everyone on the call today for your continued support of extent yet.
We hope you've seen today, our technology platform can accelerate emerging science to create new therapeutic opportunities.
We believe by controlling the intersection between generative molecular AI predictive modeling whereabouts by machine learning all physics based approaches and automated experimentation with patient relevant systems that we can produce better drugs faster. We look forward to updating you on our progress throughout the rest of the year and operator you may.
Disconnect.
Thank you ladies and gentlemen. This concludes today's call. We thank you for your participation you may now disconnect.
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