Montes Archimedes Acquisition (ROIV)
I’m Vivek Ramaswamy. I'm the founder and executive chairman of Roivant. Prior to founding Roivant, I was an investor in the biotech industry for seven years, where I focused on pre-commercial companies. Prior to that, my background was in molecular biology as an undergrad. I also have a background in law along the way, and I left my career as an investor in 2014 to found a company that was designed to address a lot of the inefficiencies that I had noted through my time and career as an investor. I've been running the company together with Matt for the last several years, our CEO. He's been with Roivant for the last 5½ to 6 years. I'll hand it over to him.
Great, thanks Vivek. I'm Matt Gline, and I'm our CEO. As Vivek said, I joined the company 5½ years ago. I studied physics originally and did my first career as a quant before starting a financial technology company that got subsumed back into a big bank.
I did not want to do that anymore, and I caught the entrepreneurial bug pretty squarely, and so I reconnected with Vivek who I knew from college and came on. I have spent most of the past 5 years as our CFO and took on the CEO role earlier this year. With that, I'll hand it over to Jim, who is the founder of the SPAC and the sponsor.
Yeah, thanks Matt. So, Jim Momtazee, I'm the managing partner at Patient Square Capital, which is a healthcare-focused investing firm. I previously spent 21 years at KKR. I was part of starting the healthcare effort at KKR 20 years ago and ran the healthcare group at KKR for well over a decade.
I'm really pleased to announce this transaction. My history with this company goes back nearly six years now, dating back to my previous role, when we conducted due diligence on the company. This specific deal we've been focused on since October. We started a dialogue with the management of Roivant literally the day after the IPO of Montes Archimedes priced back in October of last year.
So I’m very pleased that we've gotten to this stage. The company's being valued at $5 billion. There's a total of $611 million of new money coming into the company, comprised of the $411 million in trust for the SPAC plus a $200 million committed PIPE financing. There's a substantial contribution from existing shareholders of Roivant in that PIPE financing, plus a number of great new investors who were part of that PIPE.
The company has $2.3 billion of cash. It's financed for the next three years. And I'll speak about Patient Square Capital's intentions. We intend to be very long, patient shareholders. We've got a lockup that reflects that. We asked for a lockup. At least half of our stock is locked up for three years.
We also have vesting on 30% of our stock tied to achieving share prices, part at $15 a share and part at $20 a share. You know, in my career as an investor I've been involved with a number of therapeutics businesses. There's been a certain series of commonalities for those businesses, all different in the details, but some commonalities that for me have been the ingredients for success. They've all been management-centric investment theses, they've all been multiple product companies, they've all chosen in time to both develop and commercialize therapeutics, and they've all been doing things that fundamentally matter – that make a real difference for patients.
I think Roivant fits that model perfectly, and I'm really excited about the computational development capabilities that they have built, both their machine learning and physics-based capabilities and what that's going to mean in terms of their drug development going forward. Let me just touch briefly on valuation.
There's obviously substantial work over a number of months that underpins a value here. I'll give you the building blocks and then we'll reference public datapoints for public comparables. There are three late stage programs, Dermavant, Immunovant, and Aruvant, all of which have clear analogues, and you can see how value has been ascribed to them, either in the public markets or through M&A transactions. I mentioned on the previous slide their development capabilities. When you look at the fourth and fifth columns on this page you will see how analogous businesses and those platforms are valued in the public markets.
And then the far right column would include two fundamental buckets of value. There are technology tools that the company has developed that allow them to develop or commercialize drugs better and faster that are in Vant form. And then there are development programs that aren't quite as prominent as those three on the left. And when you add that all up together that $5 billion valuation seems quite attractive to us at Patient Square Capital.
Great, thanks Jim. Roivant's main mission is to go faster through the drug development process. We used to say we want to cut time and cost. Now we just say we want to cut time because when you go faster through development, you also cut costs.
And the way we do it is both by incentive alignment, by driving behavioral change through the people we attract and the incentives we've put in place for them, as well as the technology platform that we built at the parent company. So let me talk about the incentive alignment model. The way that we're built is like a multi-manager platform for drug developers. That means that we operate in a decentralized way where every scientist, every drug developer, every commercial leader gets skin in the game in the projects that they actually work on, uncapped equity or equity-like upside in their unique projects in a way that you wouldn't see in big pharma where even if they have a success, they don't really participate in the upside.
Conversely, if they have a failure, they may participate in the downside in the form of budgetary or job security risk. We turned those incentives upside down. And what that means is people are able to have their own unique company, their own subsidiary of Roivant, in which they have actual equity. That allows us not only to incentivize the people who are already here, but attract what we view as the best and brightest from both within the industry, as well as beyond the industry. And we're actually pretty focused on recruiting talent from both of those pools, including from data companies in Silicon Valley, talented investment minds and scientifically trained minds from the investment community, as well as even campus recruiting programs, where we're among the only pharma companies of our kind recruiting at top universities. At the same time, at the other end of the spectrum we are building hard technology and tools at Roivant the parent company, which we deploy throughout our Vants, throughout our subsidiaries, to be able to enable them to go faster through the development process.
You can see at the bottom of this slide some of our basic business principles, but everything starts with the first one, our orientation towards creating value, both for patients and for shareholders. And in our model, those two things go together. Go to the next slide. I was going to say, I could have told you all of that so far on the first day that we started the company in 2014, that was our guiding vision on day one. It remains our vision today. Today we believe we've proven the concept. We are well on our way towards developing a number of important medicines. We have put over 40 medicines into development and we have run nine Phase 3 studies. The last eight of those Phase 3 studies were successful Phase 3 studies.
We’ve run many earlier studies as well. That's resulted so far in two FDA approvals and we hope many more to come in the years ahead. We had to make a strategic decision in 2019 as to whether the first class of products we developed was going to be commercialized by Roivant or whether we were going to put it in the hands of another pharma company that already had pre-existing commercial capabilities.
And this was at a time in our history as a business where we were beginning to focus more not just on drug development, but also on drug discovery. So the question was: were we also going to build the plane while we were flying it when it came to drug commercialization? We made the decision to divest that first class of products.
We did a $3 billion cash deal with Sumitomo Dainippon Pharma. We took the cash and we invested in various areas of our platform. And even though we believe that's been a good acquisition for Sumitomo, we're even happier with what it's allowed us to do in taking our discovery and development platform to the next level.
And so today that's what we're going to focus most on is what we've reinvested in and developed over the course of the last couple of years. All told, as I said, we've put over 40 medicines into development across 20 of these Vant subsidiaries that we've built. We have over 800 employees across the group today, over 300 of whom sit at the parent company.
We've always operated from a position of financial strength relative to our stage as a company, and we expect that'll be part of our operating philosophy even as we move to our life as a public company as well. We'll have well over $2 billion, about $2.3 billion in pro forma cash, following this transaction.
We make an allusion on this slide to improving the ROI on pharma R&D, but on the next slide what you can see is the way we've been able to do that is not only through the success rate, but we also believe that we are actually going faster through the drug development process as well. And we now have data points across our trials, when you adjust for therapeutic area, to say that we are going faster than the rest of the industry when it comes to just the execution of late stage studies, including Phase 3 studies. What that means is we're able to reduce costs or reduce time, and when we reduce time, we also reduce costs.
But it's not just the operational efficiencies. We're also going faster when it comes to drug development strategy. Two examples are relugolix for prostate cancer, and vibegron for overactive bladder. Those are programs that both began at Roivant with a single Phase 3 study, measured against the industry standard for many indications, including these, where two Phase 3 studies would be the norm. Those are now FDA approved products today in the hands of Sumitomo Dainippon Pharma. So that gives you a sense of our history. Focused on both going faster through the development strategies we put in place as well as the development execution. And we hope that the careful selection of assets also allows us to enjoy a higher-than-average industry success rate in our trials over the long run going forward.
Go to the next slide.
I’ll talk a little bit about our pipeline and then hand it over to Matt to review the specifics.
We divide our pipeline today into our development stage pipeline – that's been principally built historically through in-licensing other drugs; these are drugs that are either in the clinic or soon to enter the clinic – and that's distinct from our discovery stage pipeline, which are the drugs that we've internally discovered, including through our computational discovery platform and our degrader discovery platform.
We'll talk about each of those in turn, starting with the development pipeline. And for that, I'm going to hand it over to our CEO, Matt.
Thank you, Vivek. So I'm going to go through first some of the later-stage programs in our pipeline, especially some of the ones with more recent updates. And then I'll take a step back and talk a little bit about the platform and how we advance these programs and discover new ones.
The first program we're going to talk about is tapinarof at Dermavant. Dermavant is our Vant focused on medical dermatology and tapinarof is a topical agent for the treatment of psoriasis. It's a topical TAMA, or therapeutic aryl hydrocarbon modulator. It is the only topical TAMA in development that we are aware of.
We in-licensed this program from GSK, with the thesis that it might be a disease-modifying agent for psoriasis patients. And we tested that in our Phase 3 studies, which read out last summer. You can see the data at the bottom of the slide in the bar charts. As you may know, 85% of prescriptions for psoriasis patients are written for topical agents, and topical agents have some shortcomings. Most of those agents are corticosteroids, and not only is their efficacy sometimes not very strong, but also they have significant side effects that make them unsuitable for chronic administration. And so what we saw at our three month endpoint and the main clinical studies at the bottom of the slide is efficacy that was superior to what is generally seen in all but the very strongest of topical corticosteroids, efficacy that is numerically equivalent to or superior to what you might see in, admittedly a difficult cross-trial comparison, but something like Otezla, an oral agent, which does significant sales and is now marketed by Amgen.
And in fact, we see efficacy that is indeed at least the bottom end of the range shown by some of the injectable systemic therapies for psoriasis. So very significant efficacy. However, the most interesting thing to us actually was the long-term extension study that continued to run after the conclusion of the main Phase 3 program monitoring patients on drug for up to 12 months.
We saw that data several months ago and it's summarized in the bottom right-hand corner here. And what it shows is truly remarkable. It shows that 40% of subjects in our trial practically achieve complete psoriasis clearance, a PGA score of zero. They showed that close to two thirds of patients, 64%, achieved PASI75 and 44% achieved PASI90. And these are endpoints that are typically reserved actually only for systemic agents. So there's no tachyphylaxis, the efficacy continues to improve after the end of the main study. And finally, I think most importantly, we ran the study in an interesting way where when patients achieved disease clearance, when they got to a PGA of zero, we took them off therapy until they re-flared and monitored that period, and we saw a remittive benefit of approximately four months. Patients staying completely clear from disease for a four month period on median before they had a flare up again. And this compares with really just a few weeks for most corticosteroids. So something truly never before seen in a topical therapy.
And that comes together with a very tolerable safety profile with very limited side effects of any kind. So a really exciting set of long-term data. We expect to launch this product. We are filing the NDA in the first half of this year and an ordinary review approval would launch the product then next year.
We also have a proof-of-concept study in atopic dermatitis. So we expect to begin our Phase 3 program in atopic dermatitis later this year. So this will both be one of our first launches at a Vant as well as a source for additional clinical data in that period to come.
The second product that I'll talk about is at Immunovant, a Vant focused on the development of an anti-FcRn antibody. So, as you may know, the anti-FcRn antibody class focuses on FcRn, the neonatal Fc receptor, a fundamental immunological pathway that is implicated in a wide variety of diseases where pathogenic IgG is relevant. You can see some of them listed on this page. Our general view is that there are three main competitors here.
There's us, there's argenx, and there's the drug that had been developed at Momenta that was acquired by J&J for $6.5 billion. There's a couple of other programs in development, but we believe that the three of these are furthest along. Our program, which came from a South Korean company called HanAll, is differentiated because it is a subcutaneous injection that was developed from the beginning to be a subcutaneous injection.
It's the only one for which patient data has been published in diseased patients for subcutaneous administration. And it's a form factor that we think will be attractive for subcutaneous administration. We put out Phase 2 data in this drug in myasthenia gravis and thyroid eye disease last year. Earlier this year we paused dosing in our ongoing Phase 2 studies because we had observed an elevated LDL level in patients on drug.
There were no sort of clinical findings related to this. It was just a lab value and Immunovant has spoken publicly about these data. I am not going to say very much more about this because the other thing that we have done is we amended our 13D filing related to Immunovant earlier this spring to indicate that we intend, following the completion of Roivant's public offering, to re-acquire the minority stake in Immunovant. And the other thing that we said is that we are in possession of nonpublic information about Immunovant and its products as part of that updated filing.
So Aruvant, the last of the programs I'll go through in detail, has a gene therapy that we are developing for the treatment of sickle cell disease. It’s a lentiviral gene therapy. It's a really interesting moment in the science and treatment of sickle cell disease in that all of the genetic medicines in development – there's ours, there's the program at bluebird bio, and there's a program that is a partnership between CRISPR and Vertex – all of those programs we expect will have potentially curative efficacy. The bluebird program has shown that in multiple patients, the CRISPR and Vertex program has as well and we've shown it, especially starting with our third patient on process two, as you can see in the data here. The challenge with these programs is both the bluebird program and the CRISPR-Vertex program require intensive myeloablative conditioning through the use of the chemotherapy busulfan, which has significant morbidities associated with it. It requires very long, sometimes months-long hospital stays and carries high risks of comorbidities, including sterility, for example, in women. And what we've recently seen, especially at Bluebird, is that some of these patients in their program, and they said, bluebird on clinical hold, have exhibited malignancies that don't appear to be linked to bluebird's lentiviral vector and may be associated, it's a known risk of busulfan-based conditioning, is an elevated risk of certain cancers.
So with that focus, one of the things that really differentiates our program is it was designed from the beginning not to require busulfan based myeloablative conditioning. It was designed by the investigator at Cincinnati Children's Hospital who developed it to potentially be usable in places like India and Africa with very high sickle cell disease prevalence, where the facilities required for that myeloablative conditioning may not be widely available and it works because the gene encoded in our therapy is a modified form of fetal hemoglobin that has better oxygen binding characteristics and better anti-sickling properties than adult hemoglobin. And so we are able to achieve the same level of curative clinical efficacy we believe, or we will be able to demonstrate the same level of curative clinical efficacy as the other therapies, even though we have a reduced intensity melphalan-based conditioning that we think ultimately may actually be an outpatient procedure, not requiring a hospital stay at all. So we think this will be a significant advantage to our program for patients that they won't have to go through that same form of intensive conditioning.
We've always thought that gives us a shot at being a best-in-class therapy. We also think, as you see delays associated with some of these other programs, including potentially delays related to the safety findings, that there is an opportunity for us to catch up and be closer to first in class, or at least not very far behind our competitors as we continue to develop this therapy. We will get seven patients in our Phase 2 study, all enrolling anticipated this year. Once we have that data that will close out our Phase 1/2 trial, and we expect to launch our pivotal program for this next year.
Now I'm going to take a step back and talk a little bit about the business more broadly. So we have focused on just several of our therapeutic Vants. You can see on the outer wheel of this picture, we have a number of others that we haven't talked about, including a collaboration with Affimed on solid tumor programs. And the bottom here, we have an anti-GM-CSF antibody with a Phase 2 program in sarcoidosis expected to begin in the first half of next year.
I'll talk for just a second about Genevant, which is a company that has a strong scientific platform for the development of novel, lipid nanoparticles for the delivery of mRNA, and there's some really interesting scientific work going on there, including collaborations with Sarepta on the delivery of novel mRNA via LNP into the muscle and a collaboration with Takeda on the delivery into hepatic stellate cells. Obviously mRNA and LNP has been an important focus this year with the COVID vaccines. And that's an area that we're paying close attention to.
So from there, I want to talk about not just the therapeutic Vants themselves, the programs that we're developing, but if you look at the inner gray ring on this chart, I want to talk a little bit about the “how,” how we do what we do.
And the inner gray ring shows the Vants that we've built that are really technology companies, they're companies that have computational tools that make us better at developing or commercializing medicines. I'll talk more about the specific programs later, but we've got Lokavant, which I think Vivek mentioned earlier, which is focused on improving our efficiency in developing medicines, getting us real-time, risk-based monitoring of our clinical trials as we run them.
We have Datavant that's focused on helping us – and it helps hundreds of customers in various areas – but helping us better understand real world patient level data about our patient population in our specific clinical trials and Alyvant, an earlier effort of ours, focusing on using AI and machine learning to improve the targeting of sales reps in commercialization to physicians.
Where I'm going to spend most of the remainder of the time however is on the upper right-hand corner of this picture with VantAI and Silicon Therapeutics, which are Vants that comprise our internal discovery engine for the computational design of new small molecules.
So what Roivant has always done on the left-hand side of this picture, is we have an engine that helps us identify targets and fundamental biological pathways that are of interest to us.
This is done by a three-part team that includes the MD-PhD investor types, it includes translational and research scientists to help design the development strategies, and it includes machine learning and data scientists who help us use various tools, including a tool that we've built called Drugome in searching the map of drugs in development and identifying opportunities within the clinical landscape.
And I should say Drugome at this point is a collaboration between us and Sumitomo Dainippon as part of the deal that Vivek mentioned earlier. Now, when we find a pathway that we like, a target that we're interested in, what we've done historically is we boil the ocean and we look for drugs in the wild that exhibit that idea.
So, you know, maybe it's at a biotech company or a pharma company or an academic institution. And when we look at what rises to the top and we find the program that we like best, that best meets our thesis, and we in-license it, and we build a Vant around it, that's been sort of the historical model.
What's new for us is a couple of years ago we started to do this and we built increasing conviction in some of our targets. But when we boiled the ocean, nothing rose to the surface, we couldn't find drugs available for in-licensing that exhibited the biological hypothesis that we were seeking to go after. Some of our own internal machine learning scientists approached us and said: hey, I think our technology platform could actually be useful as well, if we modify it and enhance it [so it’s] specifically focused on the discovery of new medicines, new molecular entities that go after these targets. And that gave rise to VantAI, Roivant’s machine learning platform for the discovery of new drugs. And that became the beginning of our entire computational discovery platform into which we've now put three quarters of a billion dollars of investment into a computational toolkit that we think is uniquely set up to discover new drugs.
On the next slide, I'll talk a little bit more about what that looks like. So, what we have now is a true end-to-end set of computational capabilities for the design of new drugs. The first piece of this, as I mentioned before, was VantAI, what we now believe to be a leading machine learning based toolkit for the design and optimization of new drugs.
That was born initially out of some scientists that we had in house. And then we went and built a world-class team focused on developing novel machine learning techniques for new molecular design. And pretty quickly we got focused on this problem of targeted protein degradation, which is a novel modality that involves using small molecules that are bifunctional.
So instead of a single binding site to a protein where they inhibit its active site, they bind to two different proteins, a protein that you want to down-regulate, as you might with a conventional inhibitor, and then on the other side, ubiquitination E3 ligase that's involved in the cell’s natural garbage disposal or recycling system.
And the idea here is instead of down-regulating protein by inhibiting them, you down-regulate them by bringing them in proximity to the recycling system and the body breaks it down. So we concluded pretty quickly that we think this is in some ways the killer app for the computational design of new drugs, because you take a relatively well understood physics problem, the binding of a small molecule to protein, and then you combinatorially explode it, first by doubling it, you're now thinking of two different binding domains, the protein that you care about and the E3 ligase, and the confirmational relationship between those proteins. And then furthermore, because you are degrading the protein instead of inhibiting it, you don't actually have to bind to the active site of the protein. You can bind in many different places on its surface. And so now you can combinatorially search for hundreds of different combinations of geometries in thinking about the relationship between these proteins and then figuring out how to degrade them effectively. So it's a great tool for computational techniques that you can focus on that expansion of problems.
Now, the thing that we quickly realized is if we wanted to be competitive in the field of degraders, we also needed the medicinal chemistry capabilities. And that's where we went out and we acquired this company called Oncopia, that's a University of Michigan spin out. It was run by this guy Shaomeng Wang, who remains a faculty member at Michigan, and it's a company that had shown expertise in developing drug-like degraders with strong properties, that gives us the real medicinal chemistry capabilities in-house to work with these compounds. Shaomeng and his lab at Michigan, we have an exclusive relationship with them for a period of time focused on anything that comes out that looks like a degrader and induced proximity. And we can use those capabilities together with our computational toolkit to be able to design new molecules.
There was one more piece missing from this on the next page. As we got into this, we realized pretty quickly that machine learning as a capability is most useful when you have data. It's most useful when there's information out there that lets you train models on designing new drugs, and protein degraders are a relatively new area.
And so there are some limitations to what you can do with the machine learning based approach based on the data available. And sometimes when you're going after a new problem, you want to be able to go back and start from first principles, so thinking about the actual physics of the situation, again from a computational approach.
Now it turns out starting a new engine for computational molecular dynamics simulations is quite difficult, but again here, we got quite lucky in that we'd built a relationship with this company Silicon Therapeutics that has, we think, the most precise molecular dynamics engine out there. And we've now been able to acquire Silicon Therapeutics.
We have a shared vision for building a company based on this set of technologies, and that's been an extraordinary accelerator in our computational platform. And a big part of that is open to the team. For example, Woody Sherman, whose picture is on the left is now our Chief Computational Scientist who was involved in the development of Schrödinger's drug discovery platform during a long career there before joining Silicon Therapeutics and coming over to Roivant. We also have Huafeng Xu who spent some time at D. E. Shaw Research and was involved in the design of the original Anton supercomputer. And we've now built our own supercomputer using a GPU based cluster up in the Boston area that helps us run these simulations.
So we now have the full picture, the full flywheel. And we can start with computational molecular dynamics when we're approaching a difficult problem. Where there is no clear data to start from, we can design chemistry specifically designed to approach that problem in a bespoke way. We can work with our medicinal chemistry capabilities with Oncopia and with our own chemists to synthesize those molecules and generate data, and then we can use that data to feed VantAI and to continue to train and improve its prediction models so that we can get better and better at designing degraders that have drug-like properties and are attractive. And this really puts us in a unique, competitive position in that there are a number of obviously successful degrader companies with strong degrader medicinal chemistry expertise, but none of them are really focused on using computational tools in the same way that we are.
And conversely there's companies like Schrödinger or Relay that are focused on computational molecular dynamics but haven't built the degrader expertise. And we really occupy a white space between these two sorts of companies where we feel like there's a unique opportunity to be a leader in the field of degraders by being a leader in the field of computational drug discovery.
The proof for us in part here is in the pudding. And we now have quite a broad portfolio of degrader and inhibitors that have been designed through the combination of our medicinal chemistry and computational capabilities. But obviously the furthest along with these programs, for example our androgen receptor program which will be in the clinic later this year, go after validated targets, where there are competitors, for example, Arvinas.
And our goal there is to generate a program that is more potent and potentially hits mutant variants that Arvinas doesn't. And we’ll have more data there in the future as we start that trial, as I said later this year, and then there are targets like CBP/P300 or SMARCA2/4, which have been quite difficult targets to hit, and where we have candidates, in the case of CBP/P300, where we’re relatively close to picking a lead candidate, that show real activity that we are really excited about. So we think this is a mix of targets across different areas that will be a compelling portfolio. And again, it's driven through this synergistic combination of our computational and medicinal chemistry capabilities.
We expect ultimately to ramp up to a rate of five new INDs a year coming out of this program. And that will supplement the in-licensing activities from our core business model that we continue to do on a regular basis for launching new Vants. And maybe, just sort of thinking about the way this might look, you know, you think about AR and essentially CBP/P300 as targets relevant to prostate cancer. If we decided to pursue both in prostate cancer, you can imagine our creating a prostate cancer Vant, which looks like any other Vant that we've ever built, except it happens that the programs were discovered through our internal discovery engine, as opposed to having been brought in by in-licensing.
I spent most of that time just now talking about sort of the top left corner of this page, Silicon Therapeutics, and VantAI, our engine for new drug discovery. What I wanted to highlight here, and I talked about this a little bit earlier, is that our computational platform actually covers a broad range of tools underlying the entire discovery and development and ultimately commercialization process.
I mentioned some of these briefly. There's Drugome which, as I said, is in collaboration with Sumitomo Dainippon, which is the oldest piece of technology built by Roivant focusing on the identification of new targets and market landscapes and trial design. We have Lokavant, which is our engine for optimizing trial operations with real-time trial data analysis, giving us real time risk-based monitoring for trial sites. This is incredibly important for enrolling trials quickly and identifying problem sites early. Lokavant is an example of something that was originally born out of technology built at Roivant for our own trials. One of the CROs that we work with, Parexel, saw the technology and thought it was really interesting and Lokavant was launched and Parexel was one of the original customers of Lokavant. And Lokavant is now developing technology for deployment to Parexel, and in collaboration with Parexel has been able to get access to a significant amount of clinical trial data, not the actual sort of sponsor data, but data about the operations of the trial, the quality of site performance and what makes a good performing site. And that in turn helps Lokavant to better train its own risk-based models.
Then we've got Datavant, a business that we've built to connect patient level real-world health data in a privacy first, HIPAA-compliant manner. So, Datavant has a toolkit that has hundreds of customers at this point and sits behind the HIPAA firewalls of healthcare institutions like payers or lab companies or EMR systems and takes patient level data within those databases and de-identifies it, strips out all the identifiable information, like, you know, Matt Gline’s name and social security number, and replaces it with cryptographically secure hashes that can be used to link data between sources. And so one of our challenges as a drug developer and understanding our patient populations is being able to follow in the US a patient journey between multiple different siloed datasets, and Datavant allows for the linkage of data across those siloed datasets so that we can better understand patient populations.
This is useful in a variety of ways for us, including it's being deployed in some of our clinical trials to help us understand our actual patient populations, and ultimately may be useful for renting real world evidence to payers as we want to think about the impact that our medicines have on the patients who get them.
So the last piece of technology on here, Alyvant, is an earlier piece of technology for us. It's a piece of technology that is focused on using machine learning and AI to optimize call plans for sales reps, so that as they call on physicians, they can call the right physicians in any given day.
And that's a piece of technology that's newer for us. It may be relevant ultimately for our launch of tapinarof, which is happening, as I mentioned, earlier next year. But right now we are learning how to do that better through partnerships and co-promotions including a partnership with EVERSANA, a company that has a contract sales organization.
I'll wrap up. This is our management team on the top of the slide. It's got a broad range of people across a variety of different functions. And as Vivek mentioned, even beyond that we are excited about the broader folks in the company who come from a variety of backgrounds. And Vivek mentioned earlier some of the different places that we recruit from that go beyond what a traditional pharma company might do.
And you can see on the bottom many of our existing institutional investors, a number of these are participating in this de-SPACing by participation in the PIPE as we've announced, and we're excited to have their continued support as we make our journey to being a public company. And from here, I'm going to hand it over to my colleague, Frank Torti, our Vant Chair, who will take you through some of the specific details of our programs at our Vants.
So good afternoon. My name is Dr. Frank Torti. It's a pleasure to be speaking to you today. I wanted to take you through some of our Vants in a little bit more detail. I am the Vant Chair of Roivant Sciences. In that role I’m the chairman of the board of all of our biopharmaceutical businesses, responsible for building those teams and responsible for those Vants. Look forward to telling you a little bit more about them today.
I wanted to start with Dermavant. At Dermavant we are building a global leader in immuno-dermatology, and I think this starts, and it starts with all of our Vants, with building a great team. We endeavor to build world-class teams across the Roivant family, that bring the best from entrepreneurial biotech as well as large pharma expertise and marry them into a highly effective and agile team to advance development of really innovative molecules. If you look at the experience set here of Todd Zavodnick, former CCO, President of Revance Therapeutics, had global leadership at Zeltiq, was responsible for over $1 billion commercial franchise at Galderma. Couple that with the former global head of pharmaceutical development, Phil Brown at Galderma, Chris Chapman, a deep commercial expert, Dave Rubenstein, a deep dermatology scientific expert with deep knowledge of our lead molecule tapinarof and I think that rounds out a leadership team we're really excited about and it's emblematic of the kind of quality of leadership we try to bring in all of our Vants to advance these important medicines.
So I want to tell you a little bit about Dermavant and its lead asset tapinarof is where I'll start. So I want to talk to you today about tapinarof. This is our lead molecule. It is a novel once daily steroid-free modulator of the aryl hydrocarbon receptor. It is a new mechanism in dermatology and something we're very excited about. And in a field that is often marked by incremental innovation, this is a novel molecule, it is a novel mechanism of action, and we think represents a real step forward in the treatment of patients with psoriasis and atopic dermatitis.
You can see on the slide a number of the components of its efficacy here, but if we think just fundamentally what is it doing, it is decreasing inflammation. It is reducing oxidative stress and it is increasing or restoring the skin barrier. And those mechanisms writ large, I think drive the kind of really exciting efficacy that we see with the product.
Tapinarof targets two of the largest markets in immuno-dermatology, psoriasis and atopic dermatitis. These are markets projected to reach $25 billion in the US and $37 billion globally by 2026, they are the most important markets in dermatology. And I think that to have one product that can speak to both of these markets and provide efficacy across both of them is a real commercial advantage, and one of the reasons we at Roivant were excited by the product when we first in-licensed it.
Psoriasis, for those of you less familiar with the disease, is a chronic inflammatory skin disease. It is characterized by these red patchy lesions that you see in the photograph here. It affects approximately 8 million people in the United States and the bulk of the patients have mild to moderate disease.
Existing treatments are largely corticosteroids. These are the topical first-line agents and given to the vast majority of patients. They are marked by a number of side effects that limit the duration of therapy, including skin thinning and otherwise, and I think the dermatology field has been looking for some time for something that could have steroid-like or better efficacy without the side effects.
Biologics are the next step up in the treatment paradigm. Those are effective, but have both high costs and high side effects, and they're limited to the more severe patient population. Tapinarof was studied in mild, moderate, and severe patients in its Phase 3 trials and has efficacy that we’ll speak to across all three areas and we think that sets up its position as a foundational treatment for psoriasis in the future.
This is our Phase 3 program design. We ran two replicate studies of approximately 500 patients each, and those patients rolled into a long-term open label extension. I'll speak to the efficacy and safety results from both the blinded portions of PSOARING 1 and PSOARING 2, as well as the long-term extension, what we call PSOARING 3, I'll speak to all three of those studies now.
These are the primary efficacy results from the PSOARING double-blind portion, and [in] two, again, replicate Phase 3 trials, tapinarof demonstrated superior PGA response rates at week 12 versus vehicle. Those P values are 0.001 and 0.001, respectively.
I think if you look at the pictures in the photograph, it'll give you a much better intuition for the magnitude of effect. The patient on the left that comes in with those red legions at a baseline PGA, that's Physician's Global Assessment, of that lesion score of three. And at week 12, you can see the PGA zero, PASI zero that's complete clearance, but you can also see by week four, the substantial response in that patient, and this is an actual patient from the study. And that's indicative of the magnitude of response that patients who go from a PGA two or three to a zero can achieve with this drug. So on the right, you'll see the, again, the headline results, tapinarof again, delivered a 35.4 and a 40.2 percent treatment success in PSOARING 1 and PSOARING 2 respectively. And based on this data, we anticipate submitting an NDA in psoriasis in mid-2021.
It was reported in our press release and other public disclosures that tapinarof also hit home [on] all secondary endpoints in the PSOARING program, in PSOARING 1 and PSOARING 2 in particular. We were excited by that consistency across multiple endpoints. And I think that consistency across endpoints really speaks to the power of the drug and the efficacy of the drug and the predictability of the drug.
And then as we think forward to the commercial landscape, we think those attributes speak well to the ultimate commercial potential. These are the PASI75 scores that are detailed here. Again, you can see in PSOARING 1 a 25.9 degree delta and PSOARING 2 a 40.7 degree delta. I think it's interesting to reflect on the fact that PASI scores were initially developed to evaluate the efficacy of systemic therapies for psoriasis. Many topicals, certainly older topicals, do not even measure PASI scores – PASI75, 90s and 100 in particular – in their clinical data. And to be able to measure a response of this magnitude and deliver an efficacy of this magnitude, it again speaks to the differential nature of the efficacy of this product and why we're so excited about it.
The Phase 3 program delivered a favorable safety profile with a low rate of study discontinuations due to AEs. The most common adverse events were folliculitis, nasal pharyngitis and contact dermatitis. The majority of these were mild or moderate. We had no clinically relevant effects on lab values or vital signs and no treatment related SAEs, severe adverse events.
One of the things that I think is important to notice is when you think about did any of these side effects really matter to patients? You know, our clinical advisors have suggested to us [to] look at the discontinuation rates and there's intelligence and information in that, in those rates. And if you look at the discontinuation rates due to adverse events like folliculitis or contact dermatitis at less than 1.8%, less than 2%, I think you can see that the vast majority of patients where these mild AEs did occur elected to continue on with the drug.
This is the PSOARING 3 long-term extension study design. I think one of the most interesting things about this study in addition to its design was that over 90% of eligible patients who completed the pivotal trials elected to roll over to a long-term extension, I think that is a number that in itself speaks to both the efficacy of the product that patients received in the Phase 3 program, as well as the tolerability and interest of patients to continue therapy.
And in the long-term extension all patients received tapinarof, and it had one or two unique features, which I want to highlight because it will speak to the data that will come. One of the unique features of the long-term extension was that when patients reached a PGA zero in the long-term extension, we stopped treatment for those patients. We then followed those patients until they reflared. Of course, they will reflare when they are off treatment for [a] prolonged period of time, and then once they reached to PGA of two or greater, they were restarted on therapy. What that gave us was the ability to measure a remittive effect and a duration of therapy off treatment that we think is unique in our ability to speak to actual data and the longevity of the efficacy for a patient who is treated and has a strong response [to] tapinarof. So in addition to having kind of headline efficacy data for this population, we also have that ability to speak to the remittive effect. And I'm going to take you through some of that data now.
So this is our Phase 3 PSOARING extension data. These are interim results. This was a pre-specified interim analysis. Once a certain number of patients had reached a certain duration of therapy that we set up at the beginning of our trial – and I'm going to speak to the efficacy, the durability, the remittance, the safety and the tolerability of the product – I think all five of those attributes we were able to evaluate in this data set, and all five of them I think we have very interesting data to share.
To start with the efficacy, I think this is really a highlight of this dataset, 39.2% of our PSOARING 3 patients achieved a PGA score of zero during the PSOARING 3 extension, that degree of efficacy for a topical therapy we believe is unprecedented.
It's very hard to find topical therapies that even report PGA zeros, or PASI100s, and a complete clearance of disease, let alone reaching an almost 40% efficacy mark on that endpoint. Further, 57.3% of patients who entered the study with a PGA of greater than two achieved a zero or one at least once during the study.
And when you step back and look at the integrated analysis of efficacy on PSOARING 1, 2, and 3, based on this interim PSOARING 3 analysis PASI75 was achieved in 63% of the patients, 63.5 and PASI90 was achieved through 44.2% of the subjects. I think again, if you were to benchmark those against topical therapies [it] would be very difficult to find any topical therapy that is better than that, or even similar, to those numbers.
When we think about durability and remittive effect, all efficacy endpoints show continued improvement beyond 12 weeks, which suggests no tachyphylaxis, no reduction in efficacy over time. We didn't see a loss of treatment effect even with intermittent use. And again, as I alluded to on the prior slide, we had a four months median duration of disease control after discontinuation of therapy.
Speaking to I think a package of very strong efficacy, very strong durability, very strong remittive effect, and then coupled with no new safety or tolerability signals, a similar AE profile to the pivotal studies, well tolerated in all skin locations with extended exposure. And I think this kind of package rounds out the tapinarof data package and it’s why we're so excited about the future for this product.
So I want to move now to atopic dermatitis. We think tapinarof offers a novel mechanism of action for the atopic dermatitis market. Atopic dermatitis is a chronic inflammatory skin disease that affects more than 9.6 million children and about 16.5 million adults in the US. The vast majority of the patients have mild to moderate disease, and there's real need in the patient population for, again, long-term, safe, topical therapies that minimize the risk to especially pediatric patients of systemic agents or from long-term steroid use, again in children.
These are the results from the Phase 2b tapinarof atopic dermatitis trial. You can see at week 8, 49% of tapinarof patients versus 13% of patients on vehicle achieving the primary endpoint here of an IGA score of zero or one with a greater than two grade improvement. It is important to note that the vehicle response in atopic dermatitis is a real therapeutic response so vehicles have an emollient effect and do have an impact and do have a response in atopic dermatitis trials. Despite that, I think you see a nice separation from vehicle here and this gives us a lot of confidence going into our Phase 3 study of tapinarof in atopic dermatitis. And we're excited to get that started this calendar year.
Concluding on Dermavant today, I think there is a promising earlier stage pipeline: cerdulatinib, a novel JAK inhibitor, DMVT-504, a drug for the treatment of hyperhidrosis and DMVT-503 for the treatment of acne. We're excited about both tapinarof and the broader portfolio that we've assembled at Dermavant as well as the team that we have, they're a good company executing at a really high level. And with that, I'm going to end my comments about Dermavant. Thank you.
I want to turn now to Immunovant, this is our company focused on enabling normal lives for patients with autoimmune disease. As I did with Dermavant, I think it's important to highlight the strength of the team that we've assembled here, led by Pete Salzmann our CEO. Pete is a former global development leader in immunology. He's had both immunology commercial as well as immunology development expertise. And I think that brings a unique perspective to how to help us think about how to maximize the value of a molecule like 1401 in a class like the anti-FcRn space.
And then we have a deep bench of scientific talent from Michael Elliot, our Chief Scientific Officer, previously VP of immunology and scientific and innovation at J&J, as well as Rita Jane, CMO, Pam Connelly, CFO, Julia Butchko, Chief Development and Technology Officer. This team has really focused on developing IMVT-1401 in really two ways: 1) in indications where we can be best in class, where there's an established proof of mechanism, and 2) in indications where there's clear biologic rationale, but no in-class competition where we can be first in class. So let me turn to the next slide and we'll get into a little bit of the programmatic details.
One of the really exciting things about Immunovant is the breadth of the markets that are mediated by excess IgG. FcRn inhibition lowers IgG levels, and so it is potentially useful in any disease that is mediated by excess IgG. You can see here the three initial indications Immunovant has targeted and that initial opportunity of 364,000 patients approximately. If you put even a round number for rare disease, a ballpark estimate against that initial opportunity, and you say it's a hundred thousand dollars for a patient directionally in a rare disease, you can easily reach a multi-billion dollar opportunity in just a few small indications, and I think one of the things we're really excited about as the future as we develop Immunovant further in the future is the ability to pick the right indications, to think about clinical risk benefit and think about places where IMVT-1401 is able to provide unique benefit to patients and we really do believe that this marketplace for diseases mediated by excess IgG is large, expands beyond these listed indications, and presents an enormous white space to go create a really important product and a really important company going after these diseases.
To cover the mechanism briefly, IMVT-1401 promotes IgG degradation. That works really in one simple way: FcRn prolongs the half-life of IgG. And so inhibiting FcRn promotes IgG degradation, and that is the mechanism through which our drug acts.
So these are our Phase 1 data, and they show our IgG reduction. In our Phase 1 data we produced clinically meaningful and predictable IgG reductions. You can see here in the graph after four doses, the consistent and predictable response, both in 680 milligrams delivered subQ, and 340 milligrams delivered subQ, and then placebo is above. And we think both the potency of the molecule as well as the predictability of the onset and of the recovery of IgG are useful attributes of the molecule that get us excited about its performance.
The results from our Phase 1 SAD/MAD cohorts of 99 subjects, total dose in those two studies, show that IMVT-1401 was generally safe and well tolerated in Phase 1. The most common AEs were mild erythema and swelling at the injection site.
There were no headaches observed in the 680 mg cohort. There were albumin changes, as noted on the slide, and there were no drug related SAEs. Recently, Immunovant voluntarily announced a pause in its dosing for the ASCEND GO 2 and ASCEND WAIHA trials due to elevations in total cholesterol and LDL observed in those studies. The details of those releases are outlined here in the slide and further in Immunovant public filings, and I would direct you to those filings for further information.
Coming to the diseases which IMVT-1401 is treating, the first disease is myasthenia gravis. Immunovant has the only subcutaneous anti-FcRn agent that has delivered results and reported those results in myasthenia gravis. This is a rare autoimmune disease. It impacts about 66,000 people in the US and is characterized by weakness of voluntary muscles, including the ocular, facial, oropharyngeal, limb, and respiratory muscles.
And I think while there are treatments outlined below, for MG, myasthenia gravis, an unmet need persists. And about 10% of MG patients are currently refractory and about 80% of these patients failed to achieve a complete and stable remission. So in addition to the side effects of existing therapies, there [is] certainly a need for new therapies in this disease and We're excited about the preliminary Phase 2a data that Immunovant has generated.
So to take you to the ASCEND MG, these are the top line results from our Phase 2a study in MG. We had a 3.8 mean improvement in MG-ADL. That's the activities of daily living score in myasthenia gravis, an eight point mean improvement in MGC, another important scale in this disease, a 40% deep responder rate on MG-ADL versus placebo, and a 40% deep responder rate on MGC again versus zero for placebo.
These are maybe transformational levels of response for patients, and we're really excited about both the magnitude of response that we see as well as the number of patients we see who have what could potentially be a life altering change in their clinical course. In the Phase 2a study 1401 was observed to be safe and generally well tolerated.
Our topline results are depicted graphically here. Again, you can see there the impact on MG-ADL, QMG, and MGC; three different scales that are used to assess disease severity, and a consistent response across all of them.
Alright, so 1401 for thyroid eye disease. This is the only subcutaneous anti-FcRn in clinical development for thyroid eye disease. Thyroid eye disease is also called TED or Graves' ophthalmopathy. This has about 15-20,000 patients with active TED every year. It is a largely incident disease market, which I think is a very interesting feature because it is a secondary feature of Graves' disease and driven by hyperthyroidism. The pool of patients is about 15-20,000 new patients reported with active TED every year. Clinical features include eye bulging, which is proptosis, a classical feature of the disease, as well as eye pain and double vision and the light sensitivity. It can be sight threatening.
There are limited treatment options for thyroid eye disease and I think the uptake of a recently introduced product called Tepezza, where they sold over $800 million in the first year of sales, speaks to the remarkable market appetite for new therapies in this disease state, and a remarkable opportunity that exists if you can make a difference for these patients.
ASCEND GO-1 was our proof-of-concept study of 1401 in thyroid eye disease. The results of that study showed a 65% mean reduction in total IgG from baseline, 57% of patients improved by two or more points on the clinical activity score, 43% of patients were both proptosis responders and clinical activity score responders and 67% of patients with baseline double-vision saw an improvement in that double vision. In this study, the drug was observed to be safe and generally well tolerated.
The last indication that Immunovant has disclosed is warm autoimmune hemolytic anemia. This is a disorder of red blood cells and marked by red blood cell destruction. It has an estimated prevalence of 42,000 patients in the US and 66,000 patients in EU. The disease has a nonspecific presentation occurring over weeks to months and characterized by fatigue, weakness, pallor, shortness of breath. There are no FDA approved therapies for WAIHA and only one third of patients maintain sustained disease control once steroids are discontinued. Most of the patients require either long-term steroid treatment or additional therapies, and there remains a large unmet need beyond steroids, blood cell transfusions, immunosuppression, and ultimately splenectomy, a surgery to remove the spleen, in the kind of end of the current treatment paradigm, so another nice opportunity for an FcRn agent to make a difference for patients that have a lot of need.
Moving on, I'm going to talk now about Aruvant. Aruvant is focused on developing gene therapies for rare diseases, particularly sickle cell disease with its lead program where we aim to develop a potentially curative regimen for that disease, with the more patient friendly conditioning regimen and I'm going to tell you a little bit more about that as we go. Like our other Vants, we've gone to great lengths to assemble a really world-class team here led by Will Chou, our CEO, former global commercial head of Kymriah at Novartis as well as lymphoma clinical development of Kymriah at Novartis. Palani Palaniappan, our Chief Technical Officer who comes to us with over 25 years of tech ops experience and a real expert in the manufacturing and CMC related to gene therapy that is so critical to both developing and commercializing those products.
One of the really interesting things about Aruvant is the story of how the company came together. Our key scientific advisor, Dr. Malik, and inventor of the technology, was focused on research related to making a gene therapy more accessible in the developing world. And one of the things that she realized in that quest was that full ablation of the bone marrow and that whole conditioning regimen was something that could never work in the developing world where you just can't put a patient into a hospital for 40 or 50 days, to have them to be severely neutropenic for 20+ days, that would never get uptake in that world. So she spent many years working on a novel gene therapy construct to try to address some of those challenges.
If I take you to the next slide, with that backstory I think it'll give you a little bit more context for what we actually have at Aruvant and how it is differentiated. Before I get into the differentiation technically though I want to tell you a little bit about the disease and for those of you not as familiar, sickle cell disease is a genetic disease caused by abnormal sickle hemoglobin. It leads to homolysis, vaso-occlusive events where sickled red blood cells obstruct circulation. This can cause severe pain, ischemic tissue injury, stroke, organ damage, and premature death. The average age of death for a sickle cell patient in the US is 44 years old.
And these particular VOEs, vaso-occlusive events, or VOCs, vaso-occlusive crises, are what a sickle cell patient lives with day in, day out, week in, week out. And [that’s] what we are trying to cure with our therapy. HBF, fetal hemoglobin, is the most potent anti-sickling globin for the treatment of sickle cell disease.
This has been a long-studied construct. There's an old drug called hydroxyurea, which increases the expression of HBF, that kind of gives a lot of the scientific credibility and duration of evidence for the idea of expressing HBF and its importance and its ability to reduce sickle cell events.
And the clinical benefit of increasing HBF is extensively described then in the literature with HBF levels greater than 8.6% associated with improved survival, HBF levels greater than 20% associated with the 2-to-4 fold reduction in hospitalization and HBF levels greater than 30% resulting in asymptomatic disease in some circumstances.
So when you put this all together and then you look at the market opportunity, this is a large gene therapy market and we estimate about a forty billion dollar market opportunity with a known mechanism of action, if we can deliver HbF effectively. And I think the next slide will show you that we have been able to do that.
So what are we actually delivering? We're actually delivering a proprietary modification of that HbF payload. What did we actually do? We took the G16D, this is the proprietary modification mutation, and that gamma globin increases the relative fraction of hemoglobin tetramers that are HbF versus HbS compared to be on modified gamma globin.
So what does that mean? What that means is that this is a higher potency construct. And why does that matter? If you could see the potency in the panel on the right, you see the diamonds in yellow. What you see there is the degree of human homolysis or the degree of reticulocytes, go higher, these are immature red blood cells when the degree of homolysis is higher because you have a higher turnover with red blood cells. So for a given degree of HbF-holding HbF reasonably constant around 30%-as you see in that circled area, you could see native HbF, those are the lighter red diamonds, and then you can see the G16D modification, those are the darker diamonds at the bottom. And so what you're seeing is fewer reticulocytes with the G16D modified hemoglobin being delivered. And ultimately what that is evidence of is a more potent construct that has the ability to deliver a better therapeutic effect in people. So when you combine the proprietary G16D modification, and its resultant increased potency, if you go to the next slide, there's one more piece of the story at Aruvant that is important to understand, and that is we have a proprietary stemness enhancer to facilitate engraftment, and what that means is we promote hematopoietic stem cell self-renewal and inhibit differentiation, so that you get more true stem cells transduced and transplanted, thus for any given product and VCN, that's vector copy number, there's a higher chance of engraftment and long-term durability than without the stemness enhancers. So as we put it all together, and as we were reviewing it at Roivant, initially, we had a proprietary construct and proprietary stemness enhancer, increased potency. And then if you go to the next slide, the last piece of this puzzle for us was the potential to provide a more patient friendly gene therapy, via the delivery of this gene therapy via reduced intensity conditioning. And it is our belief that reduced intensity conditioning may provide a significant clinical benefit. And I want to walk you through-some of these are not head-to-head comparisons-but I want to walk you through some of the existing literature on the difference between fully myeloablative conditioning and reduced intensity conditioning.
So on the left, we see busulfan-based fully myeloablative gene therapy conditioning, or other conditioning for oncology indications. Just a few points out of this list to note, you can see days in the hospital, 44 days in median, neutropenia recovery time, 20 days, ovarian failure, that means sterility for women of childbearing potential [of] 70 to 80%, and potential for outpatient administration is therefore very low.
When you turn however to melphalan, this has reduced intensity conditioning that we use at Aruvant, you see instead of 44 median days in hospitals, zero to five days in the hospital, again, in the literature at large, you see neutropenia recovery time, 20 days versus seven days, ovarian failure, 70 to 80% for busulfan, 30 to 40% from melphalan.
So when you step back, and we stepped back at Roivant, and they said again, potentially more potent construct and proprietary stemness enhancer, and the ability to engraft to non-fully ablated marrow, that combination of things got us really excited about Aruvant and really excited about what we could deliver for patients going forward.
One of the first companies in the space, bluebird bio, recently made an announcement about MDS and AML and two of their patients. We want to just share a few thoughts in that announcement before we move to our clinical data . First it is documented that sickle cell disease patients are at an increased risk for malignancy, and that high doses of chemotherapy are a known risk. So fully myeloablative busulfan-as was used in the bluebird studies and other gene therapy and gene editing studies-it has been demonstrated in the literature that higher doses of alkylating agents lead to higher degrees of risk for MDS and AML.
And it is possible that those things in combination can exacerbate this sickle cell disease, existing malignant predisposition in those patients. So I think there's some reasons to think that the background rate of malignancy might be higher, but that a conditioning regimen has the potential to play a role in these kind of emerging and serious adverse events.
There’s also a long record of lentiviral viral safety that's been established. I think bluebird has laid out a clear path to determine whether their vector was the cause, and they have thus far taken the position that it is not and, and I think, importantly, not all lentiviral vectors are the same. So, our lentivirus has different enhancers, a different transgene, and it has a lower target VCN (vector copy number), given its higher potency.
We think these adverse events remain to be fully adjudicated by the company. But I think, importantly, to us remind us of our initial thesis at Roivant and Aruvant, which is that more patient friendly conditioning is certainly a benefit and, the more we can do to advance this therapy to patients the more we think we can bring something to patients that can both deliver the efficacy that they need, with the tolerability and safety profile that has the potential to be enhanced versus other options in the field.
This is a schematic of our ongoing Phase 1/2 study. We've put the details here for your reference and we will go to the next slide for description of the early results.
These are data from the first three patients today. You can see patient one with durable engraftment through 36 months, patient two with durable anti sickling level through 36 months. Importantly, those were our first patients dosed with the first manufacturing process. You can see that the F cells at 57 and 43% at 12 months were lower than our patient three, where those F cells were 96%. Process 2 is our next step in the evolution toward a commercial manufacturing process, and we'll outline for you at the end of this deck some of the specifics, but as we brought in a team that's very experienced in manufacturing and CMC, and really focused on getting a commercial grade process in hand, you can see, I think, a clear improvement in the expression level of HBF here at 10 months, you can see the product clearly above the 30% threshold for the absence of symptoms that's been reported in the literature.
And then if you go to the next slide, you’ll see how this correlates clinically. So on the next slide, you can see if I direct your attention to the bottom, patient three, let me start there. This is a patient who came in, before treatment had had six VOEs that required hospitalizations in the 24 months before the treatment, and post-treatment they've had zero at 10 months. That's a 100% reduction obviously. And the total number of vaso-occlusive events, not just the hospitalized vaso-occlusive events for that same patient, again, two years prior to therapy, 12, 10 months after therapy, zero, a hundred percent reduction.
You can also see in patients one or two already a very early and encouraging set of efficacy metrics with a , 86 to a 100% reduction in hospitalized VOEs and a 93 and 85% reduction in total VOEs, respectively.
New patients, when they came into the trial, they were very sick, right? You can see it, with that first patient, 41 vaso-occlusive events in the two years prior to entering the trial and a 93% reduction, even as our first patient with our most academic process. So severe reduction and elimination of severe vaso-occlusive events, this is the FDA-acknowledged primary endpoint for sickle cell disease registration. We think patient three shows us the path forward where we can achieve, potentially in patients, a complete elimination of these events. We're really excited about the path forward for the company and that there's early data and I would note to you, if we go to the next slide, that process two is not the end of our optimization of our product or our process. You can see those first, the process one patient, the target VCN or 0.33, roughly for those patients, you know, moving to a process to where we targeted the VCN of about one.
And again with that VCN of about one and that patient, we're already achieving a complete clinical cure. And then as we move onto process two to process three and commercial, you can see the things that we are optimizing across a number of different parameters, including the apheresis, the vector purity, transduction enhancers, transduction conditions, etc. etc.
So we think we have both a very good line of sight to producing really well optimized product for the clinic, but also really exciting data already in hand that speaks to potentially transformational clinical efficacy with the reduced intensity conditioning paradigm, that we think patients and providers will prefer in the future.
So with that, I'll wrap on Aruvant. Thank you for your time.
Hello, I'm Mayukh Sukhatme, President and Chief Investment Officer of Roivant, and I want to take just a few minutes to review our computationally powered drug discovery engine.
As Matt noted earlier, we have taken a unique approach to our drug discovery process, which really melds the capabilities and track record that we have built and now demonstrated on the in-licensing front for many years, which is grounded in applying an investment lens to the overall process.
First, we apply this investment lens to target identification. As we ramped up our own efforts on discovery, we noticed that most discovery companies don’t have this investment perspective on the targets that they should be pursuing. That’s a unique talent base within our company, and something that powers our in-licensing efforts already. Then we have an iterative cycle across different aspects of our de novo drug discovery effort.
We have both a machine learning-based platform, built specifically for in silico design and optimization of protein degraders and other small molecule binders, and the leading computational physics platform for in silico design and optimization of any small molecule, powered by our own proprietary supercomputing cluster. As you move to the third column, you’ll note that we have an in-house facility fully equipped for biophysics, synthetic chemistry, crystallography, and biology. Again, that tight integration is key, as it provides a nice feedback loop to augment our molecular dynamics simulations and generate high resolution crystal structures.
And then we have world-class talent specifically in degrader medicinal chemistry. We already have not just novel PROTACs, but also novel E3 binders, and experience synthesizing now thousands of heterobifunctional degraders and glues across tens of targets.
All of these then feed into our development engine to rapidly bring the program through all phases of development and to patients. This has already been an area of great strength for Roivant overall, and you have seen the execution and successes of those programs which have been the case across multiple therapeutic areas, multiple drugs, multiple therapeutic modalities, and multiple Vant teams – and I think that’s a testament to the people, the programs, and the way in which we execute.
We don’t think any other company has all of these pillars. It’s really having all of these different aspects and ingredients, and then infusing it with a Roivant investment-centric, asset-centric approach, that really sets us apart, and we hope that will be increasingly evident over time. Having all these capabilities really allows us to be asset-centric and chemistry agnostic. So if the right answer is a small molecule inhibitor, we can do that. If it’s a degrader, we can do that too. And if it’s a different modality than that, we can go out and do that as well.
Let me do a bit of a deeper dive into two distinct yet highly complementary prongs to our computational discovery technology platform. As Matt noted earlier, most computational discovery companies fall into either computational physics-based approaches, or machine learning based approaches. Nobody really has been focused on both.
First, let’s define the technologies with a bit more detail. So what do we mean by “computational physics”? How does it work? Computational physics predicts how molecules will interact, using quantum physics to computationally model the forces and energies of the atomic and sub-atomic particles that comprise the molecular system. This is the approach favored by companies such as Schrödinger.
The key to success, and really the coin of the realm in computational physics-based approaches, is what’s called binding free energy calculations and the accuracy and speed of those calculations. That serves as the quantitative proxy for the binding affinity of two molecules at various poses. Put simply, this tells you how well you are modeling reality of the interface between the protein and a binder.
Next, what do we mean by machine learning as applied to drug discovery? Machine learning also serves to predict how molecules interact. The rough methodology, as you likely know, is to create software to mathematically recognize patterns from experimental training data on how molecules interact. The more data you have, the better these models get. The key to success is to be able to access, ingest, and accurately train data for the problem at hand.
Across these two different approaches, what you hope to achieve is the following. First, a higher likelihood of identifying novel binding pockets on previously undruggable targets, and second, an ability to iterate via in silico assays, which speeds things up and makes each design cycle more efficient. We can decompose atom-by-atom contributions to binding through computational physics, enabling more effective improvements to chemical structure. And we can predict pharmacokinetic properties through machine learning.
Ultimately, we expect all of this to both accelerate hit-to-lead and lead optimization, getting our drugs from concept to clinic more quickly. And even more importantly, provide us with unique targets, binding sites, and chemistries.
We have already reviewed why our combination of all these capabilities under one roof makes us differentiated as a discovery engine in full. Here is some information about what is special about each of our capabilities even in isolation versus their respective competitive landscapes.
So first, in computational physics, we believe, as a function of the acquisition of Silicon Therapeutics, that we have the leading computational physics/molecular dynamics company with the most precise simulation capabilities. We have every bit the speed and accuracy of Schrödinger on binding free energy calculations, and our proprietary supercomputing cluster and experimental data differentiates us beyond that.
This allows us to do some things uniquely well, such as predict binding affinity of a ligand and a protein, predict conformational dynamics of a protein as it shifts from active to inactive state and vice versa, and to identify novel binding sites on a protein.
The team at Silicon is world-class in this field. Woody Sherman, whom you’ve heard about earlier, [joined] Roivant as Chief Computational Scientist upon the completion of the acquisition.
Next, for machine learning, we have built machine learning models for protein degradation and ADMET prediction. These have been trained now on more than 5 years of proprietary degrader-specific experimental data and millions of carefully curated protein stability datapoints.
What does that allow us to do? As two small examples, it allows us to graph representations of known protein-protein interactions to design new degraders that can effectively stabilize target-E3 interfaces, and comprehensively map the ubiquitin proteasome system to identify degron motifs at scale. We think this will lead to novel binding locations, novel warhead design, novel linker and E3 ligand design, and engagement with novel E3s.
Hopefully all of this gives you some sense of how we will be able to model the dynamics of a protein we’re interested in, to think about the surface of that protein and look for novel ways to engage with that protein, including the use of allosteric binding sites and degraders.
Our toolbox allows us to really throw open the doors of a much broader target set than has been addressable before. By way of illustration, here are just a few large classes of proteins – the challenge – and what our edge is in going after these targets. It’s worth contextualizing all of this. The industry has made progress on inhibiting certain types of signaling proteins, but that scope is really quite limited. In most cases, the industry has been confined to small molecule inhibitors of active sites. That’s a really small subset of the universe. About 80% of the proteome is in categories of totally undrugged targets.
Now, why is that? Remember, with a traditional small molecule inhibitor first you need a nice active site pocket that an inhibitor can sit in, you need that pocket to be unique to limit off target effects, and you need to be able to dose your drug high enough to sit in all the pockets. You need a very high receptor occupancy to have a drug effect. And then finally, in oncology, you need to be able to contend with mutations, such as constitutively on mutations, mutations in the active site pocket, and so forth.
Some companies are trying to expand that universe via using degraders. That will help with unlocking efficacy for proteins that have functions apart from a signaling, or catalytic function. Other companies are trying to expand that universe using computational approaches. That might point you to more selective drugs, or ways to appreciate locked and unlocked conformations, and potentially novel binding sites.
Again, we think we’re in a position to go after the full universe. We think we can go after every one of these target categories: phosphatases, transcription factors, signaling proteins, and even intrinsically disordered proteins. We can do this in a chemistry-agnostic way. There are going to be targets for which we want to degrade it. There are going to be other targets for which we might not need a degrader, and we can go after both.
Here are a list of some of our targets, to help give you a sense of the programs we are pursuing. Some of these are early, and I will say that we will not typically be providing regular updates on these programs – this is intended to be a partial snapshot in time of what is a robust and dynamic discovery effort that will be a perpetual source of innovation in the coming years. As you can see even from this list, it is a pretty broad and deep pipeline of preclinical discovery molecules, both small molecules and degraders, across multiple therapeutic areas. The furthest along of those is in IND enabling studies now and will enter clinical trials this year.
Here is a bit of a deeper dive to help contextualize our excitement around the listed opportunities, and the potential indications and patient populations. In the interest of time, I won’t review all of these, but before discussing the experimental data on a couple of our near-to-clinic programs, I wanted to call out a couple of other programs here now.
First, CBP/P300. CBP/P300 is a target with strong scientific rationale and we see a broad range of potential indications for the program. Initial data on our lead candidates suggests highly potent and selective activity in vitro in AR-positive prostate cancer, heme malignancy models and in cell lines with CBP loss of function mutations
There are a couple of notable CBP/P300 small molecule inhibitor programs, from CellCentric and from Forma. They will generate clinical data for their inhibitors within the next 12-24 months. Now we think that those programs are likely constrained via modality, and they have been largely focused on prostate cancer alone. We think there is a strong case for superiority of CBP/P300 degraders vs. inhibitors, both because we know that CBP/P300 has a scaffolding function, which won’t be impacted by an inhibitor, and because also in our hands experimentally we see a differential effect when comparing an inhibitor to a degrader. So we think that these inhibitors will end up being incomplete proxies for what a degrader can accomplish, and we think that the applicability of a degrader will go beyond prostate cancer.
We aim to develop both dual degraders of CBP/P300 as well as degraders of each isoform specifically, as applicable to the specific tumor types we ultimately pursue.
As noted, we think applicability includes going after prostate cancer including AR splice variant subsets, potentially also ER positive breast cancer, select heme malignancies, particularly B cell lymphomas, multiple myeloma, AML, and solid tumors. And finally, tumors with loss of function mutations in either CBP or P300. These are so-call synthetic lethal contexts. As an example, CBP loss of function mutations are seen in up to 30% of diffuse large cell T cell lymphoma, and a similar percentage of follicular lymphoma.
Next, a few words on SMARCA 2/4. We believe our program has potential in a genetically defined subset of solid tumors, one example of which is SMARCA4-mutant non-small-cell lung cancer. SMARCA2 and SMARCA4 are proteins with similar functions related to chromatin remodeling. Tumors with loss of function of SMARCA4 become dependent on SMARCA2 for their survival; within this context, degrading SMARCA2 can induce tumor cell death.
Many types of solid tumors have SMARCA4 loss of function mutations, including SMARCA4-mutated non-small-cell lung cancer, which is around 10% of non-small-cell lung cancer overall, and thus is large enough itself. There is also a tumor-agnostic path, since SMARCA4 is mutated in about 5 to 10 percent of bladder, esophageal, endometrial, and other cancers.
Now, as with CBP/P300, we will aim to develop both dual degraders of SMARCA 2/4 as well as each isoform specifically, as dependent on the specific tumor type of interest, and we have high conviction, and high enthusiasm for this target overall.
Continued on this page is more detail on some of our programs. Again, we think that there are a number of attractive targets addressing high unmet needs across a range of therapeutic areas.
Our potential best-in-class AR degrader is expected to initiate Phase 1 later this year. We have an orally administered lead program with excellent drug-like properties, broad mutant coverage, and we think the potential to move upstream in the prostate cancer paradigm.
There remains a great unmet need in prostate cancer. This is a branded equivalent of a $10 billion commercial market. To an outside observer, it might appear as though this is a crowded market, with lots of big players. But actually the historical precedent is there for disruption. Over the past 10 years a new class of agents was created, which we’d call the second generation androgen signaling inhibitors, or ASIs. Those include drugs like Xtandi and Zytiga, which created this enormous market by displacing Casodex because those drugs served as [a] step function improvement. We are hoping to do the same thing again now. AR degraders represent a third generation of therapies, which could provide a step function improvement over second-generation ASIs.
We have now synthesized many hundreds of androgen receptor degraders with distinct chemistries. Our lead molecule degrades both wild type AR and AR mutants.
On the right, you’ll see data from a VCAP xenograft tumor model. You can see that this is a model that is highly resistant to enzalutamide – there is effectively zero difference between vehicle and enzalutamide in this model. In contrast, you’ll see a dramatic tumor growth inhibition effect with ARD-1671 as well as another distinct backup candidate, ARD-1676.
While apples to apples data comparisons aren’t easily done, we think this compares favorably to data from similar experiments on the Arvinas lead compound, ARV-110, and the Bristol Myers Squibb compound.
We have seen dramatic reductions in prostate weight at very low doses, even 1 mg/kg, in higher species such as dogs – this is consistent with the expected pharmacodynamic effect and is consistent with our picture of good PK/PD and good bioavailability across species – something that is not consistently seen across the landscape.
Finally, we have shown good degradation in cell-based models of mutant forms of AR, including T878A and L702H.
If that data translates into the clinic, we see 3 distinct paths for our AR-directed program. First, in ASI-refractory patients with amplifications and splice variants, which is at present a large and growing market. Second, in ASI-refractory patients with AR ligand binding domain mutations, which presents potentially a fast path to market using a precision oncology approach. And then finally, in ASI-naïve patients irrespective of AR alteration, which is an enormous market with a very long duration of therapy in the ASI-naïve setting.
Another of our near-to-clinic programs is STAT3. STAT3 is a transcription factor that has been implicated as a direct driver of multiple tumor types and contributes to an immune-suppressive tumor microenvironment, suggesting an important role in immuno-oncology.
It's historically undruggable, despite over 20 years of industry effort, largely due to specificity and potency challenges. We have highly potent and selective STAT3 degraders in lead optimization – you can see the low nanomolar potency in the Western blot on the lower left, and the selectivity for STAT3 as seen in the volcano plot in the lower middle.
On the right, you see evidence of deep responses in a xenograft leukemia model, MOLM16, with an activated pathway. You can see the dramatic increase in mean tumor volume in the vehicle arm in blue, but in contrast rapid and complete tumor regression for SD-436, our lead STAT3 degrader, at all doses, even down to 5 mg/kg.
We intend to develop our STAT3 degrader in select cancers with intrinsic hyper-activated STAT3 signaling and in tumors where STAT3 degradation can unlock anti-tumor immunity.
Finally, I wanted to make reference to a target that has been viewed as very difficult to target historically, KRAS, and give you a taste of how our technology can lead to something different.
As is well appreciated, KRAS is known as a very difficult protein to target. It has a very flat surface architecture, its own picomolar affinity for GTP/GDP making competitive inhibition difficult, and lacks known allosteric regulatory sites. So far, the breakthrough has been on getting highly potent drugs for a specific mutation – G12C or more recently G12D. These drugs bind in the same pocket.
Our ability to better model the system allows for design improvements. For example, our team has found novel hotspots. These were identified via advanced molecular dynamics simulations that capture protein flexibility, entropy, and water. By appreciating these novel hotspots, we might be able to address some of the design challenges with drugs so far. For example, removing the limitation of the covalent cysteine linkage for non-G12C KRAS variants. And for the G12C inhibitors on file with FDA or in late-stage development, they only bind to the inactive GDP-bound form of mutant KRAS, and resistance mechanisms to these drugs have already been identified, requiring the need for combination therapy. There is certainly room for improvement, and taken collectively, KRAS mutations represent over 15% of all solid tumors, making the total addressable market very significant.
There isn’t much more that we can say at this point, but hopefully this gives a sense of how our platform can be applied to truly difficult problems and yield novel insights – which we hope will lead to novel programs that can be advanced through discovery and into the clinic at an accelerated pace.
With that, I’ll conclude this section. Thank you very much for your time and interest.
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