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Front Row - AI In Drug Discovery Series II - Part 1
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Front Row - AI In Drug Discovery Series II - Part 1
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Language: EN.
Segment:0 .
[MUSIC PLAYING]
MALORYE BRANZA: Thank you very much for joining us and for talking to us about one of the most exciting companies in AI that we've seen so far and telling us more about your journey. And I wanted to start at the beginning, which is what made you think of this?
ALICE ZHANG: So I was in grad school when I started the company around five or six years ago. And at the highest level, I really had seen just how much technology has really transformed almost every aspect of our lives, from the way we move to the way we eat and communicate. And even in biotech, there have been massive improvements in efficiency and automation at key steps of the drug development process. But despite all of these massive improvements, costs have still continue to increase.
ALICE ZHANG: And as someone that came from neuroscience, I saw firsthand one of the biggest bottlenecks in drug development in neuroscience is at the end of the day, animal and cell models are simply just not great predictors of whether or not a drug will work in a human. And that's especially true for complex diseases. And so when you get increases in efficiency, you essentially just get larger and larger quantities of poor data.
ALICE ZHANG: So when I started the company, it was really born on the premise that in order to succeed in humans, we really need to be starting in humans. So what we do is instead of testing individual hypotheses in animal models, we use data from human tissue as a starting point in drug discovery, which we believe better captures the complexity of disease better than animal or cell models.
MALORYE BRANZA: And how much human tissue do you have? And where do you get it from?
ALICE ZHANG: So we have now over 6,800 individual samples. And that's growing every day. What we've done is we've gone out and partnered with over two dozen different universities and brain banks, where we can source and access thousands and thousands of patient tissue from diseases like Parkinson's disease, Alzheimer's disease, and ALS. And we also have an in-house team, because we've learned firsthand some of the challenges of actually processing that data.
ALICE ZHANG: So we actually source the samples in-house. We dissect it ourselves. We put it through really rigorous quality-control metrics. And then we actually then sequence the full transcriptome, as well as the genetic information. Oftentimes you also have clinical data on these patients. So we really get a longitudinal snapshot across multiple dimensions of each individual patient sample.
ALICE ZHANG: And that all feeds into a machine learning platform.
MALORYE BRANZA: Has anything happened technologically over the last few years that has made this possible? Or was it always it's possible and just nobody did it?
ALICE ZHANG: Yeah, absolutely. I think one of the most exciting things about the field right now is that we're at this moment where multiple technologies are converging. So for our own work, what's made it possible is, of course, the plummeting cost of sequencing over the last two decades, but then also increasing access to human tissue, so the proliferation of some of these biobanks, and then on the back end also the development of human-based cell models, so human-induced pluripotent stem cells that actually allow us to take skin cells from some of these patients, turn them into their own brain cells, and then actually test the hypotheses that come from the human tissue data in another human stem.
ALICE ZHANG: And so that's why we call it an all-in-human system. Then on the clinical side there's also been exciting developments, of course, in gene therapy and cell therapies that fundamentally allow us to deliver the targets in a new way, and then biomarker development and clinical development that allows test them in more efficient ways as well. So I think it's really advances in all of these different fronts that have created this new era for drug discovery neuroscience.
MALORYE BRANZA: Investors have shown a lot of interest in you. So beginning at the start, what have they been attracted to? And how have they helped you?
ALICE ZHANG: So the idea of using human data to replace animal models has really resonated across the board with everyone. I think everyone, ranging from investors to partners, really recognizes their need. I think to date, a lot of the more traditional investors, however, had tended to have a more conservative risk appetite. And then a lot of the platform companies have also been incubated within VCs.
ALICE ZHANG: So that's made it over the last six years an interesting journey for us to really find the right investors. But what I think is really interesting is that the landscape is shifting. And what we've seen in the last few years is this emergence of new high-growth biotech companies that are driven by new technologies. And this new era of rapidly accelerating technologies has fostered of a new set of VCs and investors to become more interested and identify this gap as really an opportunity to invest.
ALICE ZHANG: So those are the investors that we've been really able to bring on board, folks like Section 32 and BlackRock in our most recent round, all the way to strategics, like Lilly and Merck, that really recognize this need for better target discovery, even within their own pipelines.
MALORYE BRANZA: Tell me a little bit about the Lilly deal. I mean, it looks like that is something that's coming to fruition.
ALICE ZHANG: Yeah, so that's, we announced that last, towards the end of last year. That's been a phenomenal collaboration with really, I think, one of the preeminent leaders in neuroscience right now. They actually reached out to us a couple of years ago after doing a landscape of companies doing target discovery in neuroscience and really shortlisted us as one of the potential collaborators. And I think what attracted them to our platform is that the machine learning isn't really just a black box.
ALICE ZHANG: We have the end-to-end capabilities of actually not only identifying a target, validating it, and developing it into a drug. We've actually done that and ourselves with our lead program, which is a target that we identified entirely from the platform. And then we develop into our own proprietary clinical candidate that's entering the clinic at the end of this year.
MALORYE BRANZA: You say it's not a black box. So what is it?
ALICE ZHANG: So how it works is that we start-- I described earlier about this really large human tissue data set, where we've collected transcriptomic, genetic, as well as clinical information. And the first thing we do is we identify groups of genes or gene networks that are driving disease. And we integrate that with genetic data to identify which of these might be causal. So what's interesting here is that, I think, the first generation of genetic targets, leading to some of the biggest gene therapies, like Spinraza, have really been really targeted only to a very small percentage of the patient population, namely the 1% or 2% that really have that gene mutation.
ALICE ZHANG: And so what we can actually do with the platform is identify, what are the actual functional consequences of these genetic mutations? And how do they actually work together in pathways that might be dysregulated, even in patients that don't have these mutations, so to the rest of the 99%? And I think that's what's so promising about how the platform works, is we can take the next step in looking at genetic therapies.
MALORYE BRANZA: What do you think is the major-- when you're out there talking to investors, what's the major hurdle for AI companies?
ALICE ZHANG: I think a lot of, it's the same hurdle for any emergent new technology, right? There's always going to be cycles of excitement and then cycles of cynicism. I think for any new technology, the key question is, can a product demonstrate clinical proof of concept in the clinic, in patients that couldn't have otherwise been identified if not for the platform? So I think that we're starting to see a couple of companies that are putting products into the clinic.
ALICE ZHANG: So time will tell. And we'll see what the results are. But I think a meaningful leading indicator in the meantime has been the consistent interest in pharma companies to partner with some of these AI-driven companies, and in some cases even double down on those partnerships over the course of several years, which I take as a good leading indicator that at least those partnerships are producing something that the companies are benefiting from.
MALORYE BRANZA: Why did you pick the indications that you picked?
ALICE ZHANG: Well, so I think that neuroscience right now is really the most significant opportunity for new technology, particularly in target discovery. If you even just take Alzheimer's as an example, everyone's been really working on the same targets for decades, whether it's beta-amyloid or tau. And without a better understanding of the biology around those targets, those will still continue to fail. And so I think neuroscience in this way is one of the greatest areas of needs for better targets, better disease models, and a better understanding of the biology in general.
ALICE ZHANG: And that's exactly what our platform provides in spades. And plus, I think the other side is that I always like to say that neuroscience is in a Moneyball moment right now, where I think all of these convergence and technologies, ranging from genomics in AI to biomarkers to gene cell therapy, are really coalescing at a point that allows companies to make significant breakthroughs in the field.
ALICE ZHANG: And so one of our values at Verge is courageous ambitions. How we think about it is yes, it's incredibly challenging and historically been a graveyard, definitely. But is it also a potential chance to make a generational impact on the field? That also is true. So for us it's definitely worth it. We have a mindset of swinging for the fences.
MALORYE BRANZA: Well, you brought up the point that there aren't good animal models. And you are trying to present an alternative. But how do you know that your alternative is really making it?
ALICE ZHANG: So we do it in a couple of ways. We think a lot more thoughtfully about how we're using these models to validate the targets. As I mentioned before, thanks to advances in human stem cell technology, we can actually take real human samples and turn them into neurons in a dish and use that to study the biologies of some of these potential targets. And for our lead program, for example, when we actually inhibited that particular target, called PIC5, we are able to restore the cellular death of patient-derived neurons all the way back to even healthy levels.
ALICE ZHANG: So that's one window into the target itself. But we still use animals to look at core questions, such as pharmacokinetics and pharmacodynamics, as well as to develop biomarkers that we can take into the clinic and do more creative, nimble clinical studies that can derisk the target before we move it into a very large study. And so our aim is really to use the model smart, smartly, and thoughtfully, but in general, move human-validated targets as quickly as possible into the clinic, where we can get real robust information about whether or not that drug is working.
MALORYE BRANZA: What do you see as the hurdles that face you?
ALICE ZHANG: I think, like any other companies, hurdles are always scientific, people, and funding. We have hurdles in all of those. I think, of course, scientifically our next big hurdle is to enter the clinic and to demonstrate a proof of concept there in neuroscience, which is certainly a challenging field. We just raised a $98 million Series B. So we're planning on doubling the company in the next year. And so with any startup, always a hurdle of being able to hire rapidly and really maintain our singular culture in the face of hypergrowth.
ALICE ZHANG: And then I think, as I mentioned in financing, being a company really aiming for transformative change, and that looks a bit different than many of the companies out there, it's always a challenge finding the right investors that are really aligned with our values, get the story.
MALORYE BRANZA: What do you have in mind for that $98 million?
ALICE ZHANG: So for the $98 million we plan to do three things. The first is that we'll advance our lead program, which is a small-molecule therapy in ALS, to the clinic this year, and advance it through some key proof-of-concept points. The second is that we'll multiply our preclinical and clinical pipeline so that we have multiple programs that are entering the clinic. And then lastly we'll also planning-- be expanding our platform, not only on the proprietary data side, but also to new verticals, including translational medicine and clinical development so that we can not only identify new targets, but also pair them with a development strategy and a biomarker strategy that allows us to succeed more into the clinic.
MALORYE BRANZA: So the areas that you've chosen, the neuroscience areas, there's overlap with other indications. Is that something that you're taking into account? Or are you really focused on those indications at this time?
ALICE ZHANG: One of the really interesting things about the way we're thinking about neuroscience and neuroscience in general is that when you look at the pathways that are involved in some of these diseases, they're pathways that are also important and go awry in other diseases as well. So for example, our lead program in ALS is a target that restores lysosomal dysfunction, which is really the cell's ability to clear unwanted stuff from within the cell.
ALICE ZHANG: Though that pathway goes awry in neurodegeneration, an interesting and serendipitous finding that was published a couple of years ago in Nature is that this very same target and pathway is also very important in viral entry for SARS-CoV-2, as well as a broad number of other viruses. So I think we also have a second program ongoing opportunistically, where we're also developing small molecules that can be used as a broad spectrum, oral antiviral for use in a similar way across different populations in the future to prevent future pandemics.
MALORYE BRANZA: So it sounds like, I mean, what kind of people are you looking for it to work for you?
ALICE ZHANG: So we're hiring across the board, scientists across the board. We're doubling all of our functions over the next year, so computational biologists, in-vitro and in-vivo scientists. We're also importantly going to start building out our kind of next part of our stack, which is clinical development. So we'll be hiring for a chief medical officer, as well as clinical development folks to help us shepherd our next couple of programs into the clinic.
MALORYE BRANZA: And in terms of your vision, do you see it as a neuroscience company? Or do you see it as broadening?
ALICE ZHANG: Yeah, at the end of the day, we actually see ourselves as a platform that has the potential to transform drug discovery across the board. And that's how we're building it out. We've integrated technologies, not just in target discovery, but increasingly in chemistry and clinical development. And the platform itself is really targeted or disease agnostic. So really, any complex disease that has multiple genetic factors is something that would be well suited for the platform.
ALICE ZHANG: We focus in neuroscience because we wanted to start with an area of expertise, but also because that's where we see the biggest potential for the platform really transforming the treatment landscape. But in the future, we'd also consider moving inside of neuroscience as well.
MALORYE BRANZA: And what drove you particularly to seek this particular interest?
ALICE ZHANG: Well, so I was actually working on this project as my MD PhD. But when I started the MD PhD, my goal was always to make as large of an impact on patients at the end of my lifetime. And just as I went through both medical school and graduate school, on the medical side, while I recognized the impact was really profound on families and individuals, it was challenging as a pure MD to really see the number of patients to make a really large impact.
ALICE ZHANG: And on the academic side, while there was the potential to really make profound discoveries that transform the field, the day to day of how the system was oriented was more towards publications and less directly tied to patient impact. So it's kind of been a convoluted path. But ironically, starting a company has been the most direct fulfillment of that original goal of mine to join the MD PhD.
ALICE ZHANG: And it's one where when I first started it, I just saw the promise firsthand of using these types of approaches. And when we put the first target that we predicted in my PhD into mouse for a nerve injury, it immediately accelerated regeneration about four times faster than the leading standard. So when I looked at the field in terms of what are companies out there that are truly using systems biology and computational genomics to drive discovery, there are very few.
ALICE ZHANG: Most companies were really using computational methods as support tools for their existing scientists. And so I really saw an opportunity out there and just made the leap.
MALORYE BRANZA: What would you think would be the sign of the next stage of success for Verge?
ALICE ZHANG: Well, we're putting our first drug into patients at the end of this year and next year, which has always just been a personal dream of mine, to really take some of these fruits of computational biology and start translating them into products that go into patients. So, I mean, so the biggest areas of success are really being successful in the clinical development in showing that the drug is safe and nontoxic and showing some indications that it's hitting the target, that it's activating the right biologies as well, as well as overall growing the pipeline and the team in tandem.
MALORYE BRANZA: So you have done tremendously on the finance side. Is that an area where you're going to continue right now? Or are you going to show something before you ask for more money?
ALICE ZHANG: [LAUGHS] Well, right now we're heads down, really building the team and the science and advancing the pipeline. But in biotech, fundraising is always a perennial, continuous job. But we're really well capitalized right now. We have a great partnership in hand to really execute on our goals. So my main focus will be really executing on those goals.
MALORYE BRANZA: Now, in terms of that partnership, what are you getting back?
ALICE ZHANG: What are we getting back in terms of--
MALORYE BRANZA: So it's a partnership. And you're delivering a technology.
ALICE ZHANG: OK, what, yeah, right. So how the partnership works is that Lilly has access or the right to develop up to four targets from the list we generated. What's unique is that we've gotten the chance to actually retain our first two programs, our lead program in ALS and a second program. And so we own that entirely. But what we essentially did was we could take the remainder of the target pool that we wouldn't necessarily have the bandwidth to prosecute and partner them with a leader like Lilly that's advancing them from multiple shots on goal.
ALICE ZHANG: So not only do we get access to the new modalities and the expertise of Lilly to help us advance those and validate the platform, but we also get economics on that as well. So we got $25 million in near-term economics, as well as up to $706 million in potential milestones.
MALORYE BRANZA: Is there anything else you want to add about your company and its prospects?
ALICE ZHANG: I mean, I just think it's an incredibly exciting time in biotech right now. I think the landscape is changing quickly. I think when I first started and I talked to my investors, I was really the first type of CEO. I look very different from many of the other biotech CEOs. But I think in the last few years, I've just seen more and more exciting companies and a resurgence of interest in founder-led biotech.
ALICE ZHANG: And so that's just been something I think that's been really hopeful and optimistic for me. And I'm excited to see what's come.
MALORYE BRANZA: Thank you so much for your time. It's been great talking to you. We look forward to seeing what you deliver. OK?
ALICE ZHANG: Thanks.
MALORYE BRANZA: Thank you. [MUSIC PLAYING]
Segment:0 .
[MUSIC PLAYING]
MALORYE BRANZA: Thank you very much for joining us and for talking to us about one of the most exciting companies in AI that we've seen so far and telling us more about your journey. And I wanted to start at the beginning, which is what made you think of this?
ALICE ZHANG: So I was in grad school when I started the company around five or six years ago. And at the highest level, I really had seen just how much technology has really transformed almost every aspect of our lives, from the way we move to the way we eat and communicate. And even in biotech, there have been massive improvements in efficiency and automation at key steps of the drug development process. But despite all of these massive improvements, costs have still continue to increase.
ALICE ZHANG: And as someone that came from neuroscience, I saw firsthand one of the biggest bottlenecks in drug development in neuroscience is at the end of the day, animal and cell models are simply just not great predictors of whether or not a drug will work in a human. And that's especially true for complex diseases. And so when you get increases in efficiency, you essentially just get larger and larger quantities of poor data.
ALICE ZHANG: So when I started the company, it was really born on the premise that in order to succeed in humans, we really need to be starting in humans. So what we do is instead of testing individual hypotheses in animal models, we use data from human tissue as a starting point in drug discovery, which we believe better captures the complexity of disease better than animal or cell models.
MALORYE BRANZA: And how much human tissue do you have? And where do you get it from?
ALICE ZHANG: So we have now over 6,800 individual samples. And that's growing every day. What we've done is we've gone out and partnered with over two dozen different universities and brain banks, where we can source and access thousands and thousands of patient tissue from diseases like Parkinson's disease, Alzheimer's disease, and ALS. And we also have an in-house team, because we've learned firsthand some of the challenges of actually processing that data.
ALICE ZHANG: So we actually source the samples in-house. We dissect it ourselves. We put it through really rigorous quality-control metrics. And then we actually then sequence the full transcriptome, as well as the genetic information. Oftentimes you also have clinical data on these patients. So we really get a longitudinal snapshot across multiple dimensions of each individual patient sample.
ALICE ZHANG: And that all feeds into a machine learning platform.
MALORYE BRANZA: Has anything happened technologically over the last few years that has made this possible? Or was it always it's possible and just nobody did it?
ALICE ZHANG: Yeah, absolutely. I think one of the most exciting things about the field right now is that we're at this moment where multiple technologies are converging. So for our own work, what's made it possible is, of course, the plummeting cost of sequencing over the last two decades, but then also increasing access to human tissue, so the proliferation of some of these biobanks, and then on the back end also the development of human-based cell models, so human-induced pluripotent stem cells that actually allow us to take skin cells from some of these patients, turn them into their own brain cells, and then actually test the hypotheses that come from the human tissue data in another human stem.
ALICE ZHANG: And so that's why we call it an all-in-human system. Then on the clinical side there's also been exciting developments, of course, in gene therapy and cell therapies that fundamentally allow us to deliver the targets in a new way, and then biomarker development and clinical development that allows test them in more efficient ways as well. So I think it's really advances in all of these different fronts that have created this new era for drug discovery neuroscience.
MALORYE BRANZA: Investors have shown a lot of interest in you. So beginning at the start, what have they been attracted to? And how have they helped you?
ALICE ZHANG: So the idea of using human data to replace animal models has really resonated across the board with everyone. I think everyone, ranging from investors to partners, really recognizes their need. I think to date, a lot of the more traditional investors, however, had tended to have a more conservative risk appetite. And then a lot of the platform companies have also been incubated within VCs.
ALICE ZHANG: So that's made it over the last six years an interesting journey for us to really find the right investors. But what I think is really interesting is that the landscape is shifting. And what we've seen in the last few years is this emergence of new high-growth biotech companies that are driven by new technologies. And this new era of rapidly accelerating technologies has fostered of a new set of VCs and investors to become more interested and identify this gap as really an opportunity to invest.
ALICE ZHANG: So those are the investors that we've been really able to bring on board, folks like Section 32 and BlackRock in our most recent round, all the way to strategics, like Lilly and Merck, that really recognize this need for better target discovery, even within their own pipelines.
MALORYE BRANZA: Tell me a little bit about the Lilly deal. I mean, it looks like that is something that's coming to fruition.
ALICE ZHANG: Yeah, so that's, we announced that last, towards the end of last year. That's been a phenomenal collaboration with really, I think, one of the preeminent leaders in neuroscience right now. They actually reached out to us a couple of years ago after doing a landscape of companies doing target discovery in neuroscience and really shortlisted us as one of the potential collaborators. And I think what attracted them to our platform is that the machine learning isn't really just a black box.
ALICE ZHANG: We have the end-to-end capabilities of actually not only identifying a target, validating it, and developing it into a drug. We've actually done that and ourselves with our lead program, which is a target that we identified entirely from the platform. And then we develop into our own proprietary clinical candidate that's entering the clinic at the end of this year.
MALORYE BRANZA: You say it's not a black box. So what is it?
ALICE ZHANG: So how it works is that we start-- I described earlier about this really large human tissue data set, where we've collected transcriptomic, genetic, as well as clinical information. And the first thing we do is we identify groups of genes or gene networks that are driving disease. And we integrate that with genetic data to identify which of these might be causal. So what's interesting here is that, I think, the first generation of genetic targets, leading to some of the biggest gene therapies, like Spinraza, have really been really targeted only to a very small percentage of the patient population, namely the 1% or 2% that really have that gene mutation.
ALICE ZHANG: And so what we can actually do with the platform is identify, what are the actual functional consequences of these genetic mutations? And how do they actually work together in pathways that might be dysregulated, even in patients that don't have these mutations, so to the rest of the 99%? And I think that's what's so promising about how the platform works, is we can take the next step in looking at genetic therapies.
MALORYE BRANZA: What do you think is the major-- when you're out there talking to investors, what's the major hurdle for AI companies?
ALICE ZHANG: I think a lot of, it's the same hurdle for any emergent new technology, right? There's always going to be cycles of excitement and then cycles of cynicism. I think for any new technology, the key question is, can a product demonstrate clinical proof of concept in the clinic, in patients that couldn't have otherwise been identified if not for the platform? So I think that we're starting to see a couple of companies that are putting products into the clinic.
ALICE ZHANG: So time will tell. And we'll see what the results are. But I think a meaningful leading indicator in the meantime has been the consistent interest in pharma companies to partner with some of these AI-driven companies, and in some cases even double down on those partnerships over the course of several years, which I take as a good leading indicator that at least those partnerships are producing something that the companies are benefiting from.
MALORYE BRANZA: Why did you pick the indications that you picked?
ALICE ZHANG: Well, so I think that neuroscience right now is really the most significant opportunity for new technology, particularly in target discovery. If you even just take Alzheimer's as an example, everyone's been really working on the same targets for decades, whether it's beta-amyloid or tau. And without a better understanding of the biology around those targets, those will still continue to fail. And so I think neuroscience in this way is one of the greatest areas of needs for better targets, better disease models, and a better understanding of the biology in general.
ALICE ZHANG: And that's exactly what our platform provides in spades. And plus, I think the other side is that I always like to say that neuroscience is in a Moneyball moment right now, where I think all of these convergence and technologies, ranging from genomics in AI to biomarkers to gene cell therapy, are really coalescing at a point that allows companies to make significant breakthroughs in the field.
ALICE ZHANG: And so one of our values at Verge is courageous ambitions. How we think about it is yes, it's incredibly challenging and historically been a graveyard, definitely. But is it also a potential chance to make a generational impact on the field? That also is true. So for us it's definitely worth it. We have a mindset of swinging for the fences.
MALORYE BRANZA: Well, you brought up the point that there aren't good animal models. And you are trying to present an alternative. But how do you know that your alternative is really making it?
ALICE ZHANG: So we do it in a couple of ways. We think a lot more thoughtfully about how we're using these models to validate the targets. As I mentioned before, thanks to advances in human stem cell technology, we can actually take real human samples and turn them into neurons in a dish and use that to study the biologies of some of these potential targets. And for our lead program, for example, when we actually inhibited that particular target, called PIC5, we are able to restore the cellular death of patient-derived neurons all the way back to even healthy levels.
ALICE ZHANG: So that's one window into the target itself. But we still use animals to look at core questions, such as pharmacokinetics and pharmacodynamics, as well as to develop biomarkers that we can take into the clinic and do more creative, nimble clinical studies that can derisk the target before we move it into a very large study. And so our aim is really to use the model smart, smartly, and thoughtfully, but in general, move human-validated targets as quickly as possible into the clinic, where we can get real robust information about whether or not that drug is working.
MALORYE BRANZA: What do you see as the hurdles that face you?
ALICE ZHANG: I think, like any other companies, hurdles are always scientific, people, and funding. We have hurdles in all of those. I think, of course, scientifically our next big hurdle is to enter the clinic and to demonstrate a proof of concept there in neuroscience, which is certainly a challenging field. We just raised a $98 million Series B. So we're planning on doubling the company in the next year. And so with any startup, always a hurdle of being able to hire rapidly and really maintain our singular culture in the face of hypergrowth.
ALICE ZHANG: And then I think, as I mentioned in financing, being a company really aiming for transformative change, and that looks a bit different than many of the companies out there, it's always a challenge finding the right investors that are really aligned with our values, get the story.
MALORYE BRANZA: What do you have in mind for that $98 million?
ALICE ZHANG: So for the $98 million we plan to do three things. The first is that we'll advance our lead program, which is a small-molecule therapy in ALS, to the clinic this year, and advance it through some key proof-of-concept points. The second is that we'll multiply our preclinical and clinical pipeline so that we have multiple programs that are entering the clinic. And then lastly we'll also planning-- be expanding our platform, not only on the proprietary data side, but also to new verticals, including translational medicine and clinical development so that we can not only identify new targets, but also pair them with a development strategy and a biomarker strategy that allows us to succeed more into the clinic.
MALORYE BRANZA: So the areas that you've chosen, the neuroscience areas, there's overlap with other indications. Is that something that you're taking into account? Or are you really focused on those indications at this time?
ALICE ZHANG: One of the really interesting things about the way we're thinking about neuroscience and neuroscience in general is that when you look at the pathways that are involved in some of these diseases, they're pathways that are also important and go awry in other diseases as well. So for example, our lead program in ALS is a target that restores lysosomal dysfunction, which is really the cell's ability to clear unwanted stuff from within the cell.
ALICE ZHANG: Though that pathway goes awry in neurodegeneration, an interesting and serendipitous finding that was published a couple of years ago in Nature is that this very same target and pathway is also very important in viral entry for SARS-CoV-2, as well as a broad number of other viruses. So I think we also have a second program ongoing opportunistically, where we're also developing small molecules that can be used as a broad spectrum, oral antiviral for use in a similar way across different populations in the future to prevent future pandemics.
MALORYE BRANZA: So it sounds like, I mean, what kind of people are you looking for it to work for you?
ALICE ZHANG: So we're hiring across the board, scientists across the board. We're doubling all of our functions over the next year, so computational biologists, in-vitro and in-vivo scientists. We're also importantly going to start building out our kind of next part of our stack, which is clinical development. So we'll be hiring for a chief medical officer, as well as clinical development folks to help us shepherd our next couple of programs into the clinic.
MALORYE BRANZA: And in terms of your vision, do you see it as a neuroscience company? Or do you see it as broadening?
ALICE ZHANG: Yeah, at the end of the day, we actually see ourselves as a platform that has the potential to transform drug discovery across the board. And that's how we're building it out. We've integrated technologies, not just in target discovery, but increasingly in chemistry and clinical development. And the platform itself is really targeted or disease agnostic. So really, any complex disease that has multiple genetic factors is something that would be well suited for the platform.
ALICE ZHANG: We focus in neuroscience because we wanted to start with an area of expertise, but also because that's where we see the biggest potential for the platform really transforming the treatment landscape. But in the future, we'd also consider moving inside of neuroscience as well.
MALORYE BRANZA: And what drove you particularly to seek this particular interest?
ALICE ZHANG: Well, so I was actually working on this project as my MD PhD. But when I started the MD PhD, my goal was always to make as large of an impact on patients at the end of my lifetime. And just as I went through both medical school and graduate school, on the medical side, while I recognized the impact was really profound on families and individuals, it was challenging as a pure MD to really see the number of patients to make a really large impact.
ALICE ZHANG: And on the academic side, while there was the potential to really make profound discoveries that transform the field, the day to day of how the system was oriented was more towards publications and less directly tied to patient impact. So it's kind of been a convoluted path. But ironically, starting a company has been the most direct fulfillment of that original goal of mine to join the MD PhD.
ALICE ZHANG: And it's one where when I first started it, I just saw the promise firsthand of using these types of approaches. And when we put the first target that we predicted in my PhD into mouse for a nerve injury, it immediately accelerated regeneration about four times faster than the leading standard. So when I looked at the field in terms of what are companies out there that are truly using systems biology and computational genomics to drive discovery, there are very few.
ALICE ZHANG: Most companies were really using computational methods as support tools for their existing scientists. And so I really saw an opportunity out there and just made the leap.
MALORYE BRANZA: What would you think would be the sign of the next stage of success for Verge?
ALICE ZHANG: Well, we're putting our first drug into patients at the end of this year and next year, which has always just been a personal dream of mine, to really take some of these fruits of computational biology and start translating them into products that go into patients. So, I mean, so the biggest areas of success are really being successful in the clinical development in showing that the drug is safe and nontoxic and showing some indications that it's hitting the target, that it's activating the right biologies as well, as well as overall growing the pipeline and the team in tandem.
MALORYE BRANZA: So you have done tremendously on the finance side. Is that an area where you're going to continue right now? Or are you going to show something before you ask for more money?
ALICE ZHANG: [LAUGHS] Well, right now we're heads down, really building the team and the science and advancing the pipeline. But in biotech, fundraising is always a perennial, continuous job. But we're really well capitalized right now. We have a great partnership in hand to really execute on our goals. So my main focus will be really executing on those goals.
MALORYE BRANZA: Now, in terms of that partnership, what are you getting back?
ALICE ZHANG: What are we getting back in terms of--
MALORYE BRANZA: So it's a partnership. And you're delivering a technology.
ALICE ZHANG: OK, what, yeah, right. So how the partnership works is that Lilly has access or the right to develop up to four targets from the list we generated. What's unique is that we've gotten the chance to actually retain our first two programs, our lead program in ALS and a second program. And so we own that entirely. But what we essentially did was we could take the remainder of the target pool that we wouldn't necessarily have the bandwidth to prosecute and partner them with a leader like Lilly that's advancing them from multiple shots on goal.
ALICE ZHANG: So not only do we get access to the new modalities and the expertise of Lilly to help us advance those and validate the platform, but we also get economics on that as well. So we got $25 million in near-term economics, as well as up to $706 million in potential milestones.
MALORYE BRANZA: Is there anything else you want to add about your company and its prospects?
ALICE ZHANG: I mean, I just think it's an incredibly exciting time in biotech right now. I think the landscape is changing quickly. I think when I first started and I talked to my investors, I was really the first type of CEO. I look very different from many of the other biotech CEOs. But I think in the last few years, I've just seen more and more exciting companies and a resurgence of interest in founder-led biotech.
ALICE ZHANG: And so that's just been something I think that's been really hopeful and optimistic for me. And I'm excited to see what's come.
MALORYE BRANZA: Thank you so much for your time. It's been great talking to you. We look forward to seeing what you deliver. OK?
ALICE ZHANG: Thanks.
MALORYE BRANZA: Thank you. [MUSIC PLAYING]
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