Regeneron Pharmaceuticals, Inc. (REGN) Earnings Call Transcript & Summary

Good morning, everybody, and welcome to Guggenheim Biopharma Strategy Series, Biopharma Next Decade: Views from the Top on Global Strategy and Innovation. Today, we have multiple members of the Regeneron management team, including George Yancopoulos, Chief Scientific Officer, Scientific Founder and the President; Brian Zambrowicz, SVP Functional Genomic and Chief Operation; Aris Baras, SVP, Regeneron Genetics Center; and Christos Kyratsous; VP, Research. We also have Justin Holko from the IR side on us. The format of this session is going to be presentation by Regeneron followed by Q&A. For investors listening to the call, please feel free to e-mail me your questions at [email protected]. So with this opening remark, let me turn it over to Justin for a brief intro, and then we can go into the presentation. Justin?

Thank you, Yatin. And first things first, I'm going to try to share slides. You'll have to let me know if you're seeing them. You think after having done this so many times over the last year, we have it down pat, but please confirm that slides are up and visible.

Yes. We can see them.

Excellent. So great. Before we begin, I would like to remind you that remarks on today's webcast do include forward-looking statements about Regeneron. Each forward-looking statement is subject to risks and uncertainties that could cause actual results and events to differ materially from those projected in the statement. A more complete description of these and other material risks can be found in Regeneron's SEC filings. We do not undertake any obligation to update any forward-looking statements, whether as a result of new information, future events or otherwise. I would like to welcome everybody to today's special events and to thank Yatin and the Guggenheim team for hosting us again this year. Today, we're going to do something a little bit different. And in following with the theme of this event, biopharma's next decade. As you heard from Yatin, joining me today are George, Aris, Brian and Christos. And you'll hear from each of them today. Really, our goal is to highlight our efforts on precision genetics and medicine kind of beyond the antibody as an emerging area of strength for Regeneron. And honestly, the timing couldn't be any better as we and our partner, Intellia, released the first ever in-vivo systemically administered CRISPR/CAS9 data this past weekend. So we'd like to speak to how this data released really is just the beginning and a small part of a more comprehensive narrative and vision that we have for Regeneron as we've got a whole new pipeline of turnkey interventions. Our hope is that everyone will come out of today's event with a new appreciation for these efforts and to enhance Regeneron's position as a preeminent and cutting-edge diversified biopharmaceuticals company with a very bright and multifactorial growth profile for the long term. So with that, let me hand the call over to George.

Thanks, Justin. I hope everybody can hear me, and I'm delighted to be here to discuss how we are reimagining the future of biotech. And as Justin says, it's great to be here, particularly following on the heels of our recent announcement with our partners at Intellia that we have successfully achieved the first human proof of concept for a systemic CRISPR-based therapy. So what we're hoping to convey to you today is how we took the experiences and lessons that we learned in becoming the world's leading antibody and bispecifics company and use them to build our genetics medicine capabilities, starting with our Regeneron Genetics Center, and incorporating a series of novel turnkey therapeutic modalities from siRNA to CRISPR-based gene knockout and insertion to gene therapy approaches. Maybe you can move to the next slide, Justin. So to remind you about our history at Regeneron, we founded and built this company on the dream of the power of mouse genetics, and we invented the most powerful technology to engineer the mouse genome, which we called VelociGene. Even in the age of CRISPR, VelociGene remains the most powerful and rapid genome engineering technology in the world. VelociGene allowed us to test genetic variation in the mouse, that is knocking out of genes or humanization and insertion of modified human genes so as to test and validate potential drug targets. And because of this VelociGene capability, we were able to do this testing at an incredible scale, hundreds of potential drug targets a year. This gave us enormous confidence in the targets we were pursuing and helped explain the remarkably high success rates that we ultimately had in the clinic. But we also recognize that we needed a new turnkey ways of making new medicines based on these genetic insights that we were getting from the mouse studies. For example, one turnkey approach that we developed was we exploited VelociGene to make our VelocImmune mouse. It was the largest genome engineering project in history, where we precisely replaced over 6 megabases of mouse immune genes with their human genetic counterparts to create the most powerful way of making and selecting for the best fully human antibodies rapidly and in a manufacturing-ready way. So combining mouse genetics, high-throughput mouse genetics, with these turnkey therapeutics approaches allowed us to deliver many important medicines from our laboratories, from EYLEA to DUPIXENT to PRALUENT to the highly effective antibody cocktail treatments for epidemics, initially Ebola and, most recently, COVID-19. And our vision was to take these same core principles and use them to build the genetic medicines capabilities of the future. We wanted to extend our ability to elucidate the functional implications of genetic variation in mice by creating a complementary capability to explore human genetic variation through mega-scale human sequencing, all linked to electronic medical records and to also incorporate the right toolkit of genetic and medicines to take advantage of these genetic insights that we were sure to gain from all of these efforts. Next slide. So today, you are going to hear about all of these advances from the individuals who have taken on the challenge and are leading our efforts into the future of genetic medicines, how they themselves, built upon our core principles and what we learned about the power of genetics and turnkey therapeutic solutions, in creating the world's leading antibody and bispecifics company and how they expanded and built on this to create the future of genetic medicines. It has taken 5 to 10 years of deep investments. It is dependent upon us becoming the leading human sequencing and big bio data company in the world and then dependent upon us figuring out how to add novel turnkey therapeutic approaches to deal with the flood of new genetics insights information we are getting from understanding human genetic variation. And so with that, I'll turn it over first to Aris Baras, who built our Regeneron Genetics Center and is helping lead our exciting adventure in genetics medicines. He'll tell us about how we built the Regeneron Genetics Center and its capabilities and about our first turnkey therapeutics approach, that is siRNA approaches built on our collaboration with Alnylam. Then Aris will turn it over to Christos Kyratsous, who you may have heard of already in terms of his efforts to lead both our Ebola and COVID-19 efforts. He's been pretty busy. But believe it or not, his main efforts throughout those epidemics has really been in helping build our genetic medicines approaches. And he will tell you about his efforts working with Intellia on gene deletion and gene insertion but also on our own internal gene therapy efforts that he will be leading -- that he has been leading. Aris and Christos will be supported during this talk by Brian Zambrowicz. Brian has been leading our mouse VelociGene efforts for years, which will continue to be and are continuing to be highly integrated with these human gene medicine efforts. And Brian is also coleading on many of these human gene medicine approaches. I believe that these gentlemen together are creating the future of medicine. So with that, I'll turn it over to Aris.

Thank you, George. All good here with the audio. And thank you, Justin, for the introduction. So let's jump into the Regeneron Genetics Center, or as we affectionately call it here, the RGC. So we'll start with some quick facts and then jump into really our goals and applications for how we use human genetics to advance our drug discovery and development programs, as George alluded to, and some really exciting examples we wanted to highlight how we've turned this all into reality, real-world examples. So we started this about 8 years ago, the RGC, a big human genetics initiative at Regeneron, again, based on the foundation and principles that George nicely highlighted and the power of genetics in mouse and human genetics and how it really changes the paradigm in drug discovery and development. Our industry is one that has been marked by a 90% failure rate. And as we look at all the targets of known medicines, approved medicines and experimental medicines, sadly, it's only about 5% to 10% of the genes in our human genome correspond to those drug targets. So clearly, we don't know enough about what our genes are doing, let alone which ones are the best levers for drug targets. I mean that's a really big deal and important differentiating point here. We have the largest database of gene variation linked to health and disease to start to make those connections, understandings and bring forward those drug targets. To do this, you really have to have the right scale. You can't do this in a small fashion, and you can't do this without fully sequencing all of the genes. Our database now is approaching about 2 million individuals who've been sequenced. It's hard to say exactly. But from our friends at Illumina and elsewhere in the field, it's estimated that maybe 5 million people or so have been fully sequenced in the history of next-gen sequencing. So it really puts things into perspective what's happening here in Tarrytown. This does include the largest project to date in the world, which is a 500,000-person U.K. Biobank project. All of our projects are linked to very detailed phenotypic data, health record data, head-to-toe imaging data on lots of individuals, for example. This is an incredibly powerful resource for discovery and development. We've also made tremendous advances in analytics, be it genetics, be it imaging data, be it machine learning and also in robotics and automation. Regeneron has been a leader for decades in these types of automation and robotics, and this didn't really exist in the next-generation sequencing field. So our ability to bring this to the amazing technology advances going on in sequencing and best-in-class sequencing technology platforms was really enabling for us to do this. Next slide, please, Justin. So jumping into the applications that I alluded to. The main areas are really looking at new drug target discovery. And I talked about that bottleneck and the dearth of great drug targets. The way we think about this is really simplifying it into 2 sides of the coin. We've got, on one side, genetic variants and mutations that cause disease. Today, no greater example than thinking about something really relevant like TTR. It's a known gene, right? We know the mutations that cause disease, but there are so many unknowns in drug discovery and development. And think about the power of this database. Is it safe to knock out or knock down this target? Well, we can look again in the world's largest database of gene variation and find those rare individuals that have a loss of function or knockout mutations, and we can have an insight that others can in terms of how safe might this be or what consequences might there be. We can also study the 100 or so mutations that are known for that gene and get a sense of what the true prevalence is or how big of an opportunity could this be. One example we've published on extensively with our collaborators around the world, there's actually a TTR variant that is somewhat common in African Americans, a few percent of individuals, not the rare only 50,000 people in the world. And these individuals have a much higher risk of cardiomyopathy and heart failure. And so we can start to understand is this -- does this make it a bigger opportunity to be able to pursue? So this is the types of things we can do. The other side of the coin is protective mutations, not variants in mutations that cause disease but those that dramatically protect from or reduce risk of disease or progression from disease. And we'll highlight an example like HSD17B13, the first protective genetics story and target and now therapeutic program in the field of chronic liver diseases and NASH. In Regeneron, we've come up with almost a couple of dozen of these protective genetics discoveries here at Regeneron. And a big fraction of those have advanced to drug discovery programs. The other bucket is how we use genetics to help guide our existing programs and drug development, increasing probability of success and precision medicine applications, identifying highest-risk individuals and individuals who have the highest treatment benefit. So we'll go through an example with IL-33 in COPD. And we'll also talk about a really tough field of drug development, cardiovascular outcomes trials, very long, very large trials, expensive and some major learnings we had there that we're now applying everywhere else in NASH, in COPD and in other areas. And of course, we're talking a lot today about these new turnkey therapeutic approaches, and we'll highlight namely RNAi and our great collaboration with Alnylam, genome editing of the knockout variety and the genome insertion variety and a tremendous collaboration with Intellia; and also gene therapies, targeted viral-based gene delivery and expression and a tremendous collaboration with Decibel. Next slide, please. Okay. So we'll have a series of examples here, just along those buckets that I laid out, and we'll get to a real-world examples of turning genetics into therapeutics. The first bucket, again, is novel target discovery. Remember that big bottleneck that we all struggle with in drug discovery and development. Very powerful example here. We look at a disease, right? That's been a graveyard in drug discovery and development, NASH and other chronic liver diseases, no approved treatments, devastating comorbidities and mortality. And here's an example where we studied the largest database of individuals with chronic liver disease and biomarkers of disease. And our first protective genetics discovery here was in the target gene HSD17B13. And as you'll see here from some of the figures from our publication, individuals have a dramatic reduction in all forms of chronic liver disease, alcoholic, nonalcoholic, viral, autoimmune. And I've highlighted there on the bottom bar graph, if you look at the most severe forms, right, the things that might be most interesting, cirrhosis and liver cancer, and you look at individuals who have complete loss of function, full knockouts, this gene is just completely inactivated in their genome. And look at the dramatically lower rates of disease risk, 50% to 70% reductions. So this is a discovery we made around 2017, 2018. And this is a target that is exquisitely and very specifically highly expressed in the liver. It's an intracellular target, which we couldn't address through antibodies. So we quickly struck our first partnership with Alnylam. And the rest is history, I suppose. In less than 3 years, working hand in hand with our collaborators there, we got to the clinic with our HSD17B13 inhibitor. We have Phase I studies in healthy volunteers in NASH underway, and we'll have our first data readouts by year-end. And this is just the first of many. We actually have a few more protective genetics targets in NASH. And therefore, a few more programs now in a very nice portfolio of these genetics to therapeutics programs in NASH with Alnylam. Next slide, please, Justin. We want to give you one more example of targets. I gave something old. And now we'll give you something new. This is really new, another huge opportunity. It doesn't get bigger than obesity perhaps. Nearly 1 billion people will be suffering from obesity and severe obesity. And again, using the principles of discovery that we use for protective genetics variants, we found a target gene, which we'll be disclosing soon, where individuals who have these rare genetic mutations are more than 10 pounds lighter and have almost more than 55% lower rates or protection from obesity. And we quickly paired that with the power of mouse genetics and our VelociGene technology, and we're also able to show that mice that have this knockout in this target gene are also protected from obesity. So we quickly moved multiple therapeutics programs against this target for obesity. We'll be publishing this in the next month. So lots of information here to come around the target, the biology, the story and our ongoing drug discovery and development efforts. Next slide, please. So now we'll switch gears from target discovery and talk about how we're using human genetics for existing drug programs, namely we'll get into how we're picking indications and trying to pick the winners and improving probability of success. And again, we'll also talk about precision medicine and how we can look at indications, difficult ones, understand risk and progression and treatment benefit with much more precision. So first, the IL-33 story, a very competitive field where when we got into this the drug development game and entered the clinic, there were maybe 6 to 8 different competitors, all developing IL-33 blockers and programs. And we were amongst the first to make really important genetics discoveries. And here, we have both loss of function, protective mutations. And these mimic a drug, which is blocking the target. And we also have mutations that are gain of function, where they activate the target in its pathway. And we're able to see, as we're showing in the top right figure there, that the activating or gain of function, so more activity in IL-33, the target actually leads to increased risk of COPD. And these loss of function that mimic the drug are protective, so they reduce risk and protect from COPD. So we saw this pattern in asthma as well. It's no surprise that when we got into the clinic, we had clinical POCs in asthma we reported a couple of years ago. And really excited in COPD, where we don't have disease-modifying therapeutics, that we've now seen a 40% reduction in exacerbations in COPDers who are former smokers, so recent trial readouts and data that's been previously disclosed. And now we're advancing 2 Phase III studies in COPD. And importantly, we're constantly using these approaches to identify new indications and also to identify early, for example, that there were not links -- genetic links with IL-33 in atopic dermatitis. And we've seen where those programs have failed in that indication. So a very powerful tool as you're seeing here, using human genetics and drug development. Justin, if you could advance to our last example and slide for uses of genetics and real-world applications here? So we're again here in the development space in how we use genetics. And now we're talking about how we're using precision medicine and how we're doing smarter trial design. So we chose an example here in cardiovascular outcomes, which is a very difficult space to do development. But the approaches here we're applying everywhere in development and some difficult areas that we're facing now in terms of NASH drug development and outcomes there, COPD drug development, really everywhere. But this is a story that we worked on in previous years and have published the results. And this has to do with our Praluent program and the cardiovascular outcome studies that were 20,000 individuals with cardiovascular disease or more and took over 3 years of outcomes data and actually much longer to run the full trials. So a really great example of the study. What we did was we looked at composite genetic risk score, so really advanced analytics, summing up all of the genetic risk factors someone has, all individuals in the trial for cardiovascular events and all traditional clinical risk factors. So something as simple as your cholesterol levels. As a reminder here, the overall trial was a great success, with 15% reduction in cardiovascular outcomes on top of standard of care. And so it was incredibly striking when we applied these approaches in advanced analytics and saw that they could dramatically enrich in identifying high-risk patients with higher event rates but also those patients who had tremendously higher benefits from treatment. So I'll just walk you through these 4 simple panels of subgroups in the trial. In the top left, you'll see individuals that have low risk, genetic risk or cholesterol, in this case, clinical risk factors. And they had very little benefit, right? Remember, the 15% risk reduction overall for cardiovascular events. And here in that kind of red call-out box, we're seeing about a 6% risk reduction. Amazingly, this is 2/3 of that trial population. Think about that. As you move now to the top right and the bottom left, you're adding risk. You have high-risk individuals, whether they're genetic risk or clinical risk factors, cholesterol. And you're seeing actually far greater risk reduction in the overall trial, the risk reductions in the 20% to 35%. And these groups represent about 1/3 of the trial population. And lastly, if you get to the highest risk of genetic and clinical risk factors, maybe only about 5% of the trial population, but you're seeing a whopping 65% risk reduction. So really striking effects. The important principles to take away here are these approaches can now enable us to do trials with larger effect sizes, think about 65% versus 15%. We can do them faster. These can be precision trials that are less expensive and we get signal, and readouts a lot earlier. So absolutely, this can transform the way we do development and can help us with very difficult fields that haven't been broken in terms of NASH and other difficult fields. And also, we have a lot of insights here we can gain to inform commercial efforts. All right. Next slide, please, Justin. And now we'll transition. I'll do a brief intro here, and then Christos will also introduce many of these new turnkey therapeutic approaches that fit under this Regeneron Genetics Medicines umbrella. On the left here, we have approaches that are inhibiting genes, RNAi for gene silencing and gene editing of the knockout variety, as we mentioned. And on the right, we've bucketed approaches that are restoring gene function. So genome editing where we have gene insertion and also gene therapy approaches, namely targeted viral-based gene delivery and expression. Next slide, please, Justin. The first of these, as I alluded to, is RNAi and gene silencing and going back to the motivations and the core principles that George talked about. So these are validated platforms with multiple drug approvals. They are precision medicines, right, with target specificity and very little, if any, off-target effects. And we can design these therapeutics with exquisite specificity and get to clinic with great speed. Our partners at Alnylam have been terrific, and they've given us rapid path to therapeutics into the clinic for many targets that we can't address with antibodies, like the intracellular targets like HSD17B13 that we highlighted. We can also do very unique things with sRNA and with combinations of our antibodies and sRNA that give us very favorable dosing intervals and patient-friendly dosing intervals. So C5 is a great example with a very large market, but we're very far ahead now with combo programs in myasthenia gravis and PNH, PNH highlighted on the right side there. We've talked about HSD17B13 and also another clinical program there against APP. And we have planned studies in early onset Alzheimer's and a rare disease, cerebral amyloid angiopathy. I'll also highlight this is an exclusive partnership with Alnylam in CNS and eye, a 5-year program with an option to extend, and also select programs in the liver as well. And very excited by the rapidly advancing portfolio and pipeline there. We have a handful of programs entering IND-enabling studies in the clinic in the next year and beyond. So with that, Justin, that's the end of that section. And I'll turn it over now to Christos, as George mentioned, well-known tremendous scientist, technologist and the man behind our Ebola and COVID programs and just a terrific guy as well. So Christos, off to you.

Thanks, Aris. Justin, can you move to the next slide? The next technology that we want to highlight today is performing genome editing using CRISPR/Cas9 in order to perform a knockout, getting rid of the gene. Using CRISPR/Cas9, the enzyme machinery here, we performed a precise guarding the genome. And again, the goal here is to do permanently delete a gene. The first example of that is our TTR program in collaboration with our partners in Intellia. And of course, as several speakers mentioned earlier, this is the first human proof of concept that we achieved for the first systemic CRISPR-based therapeutic. And we announced the data a couple of days ago this weekend. What we saw is that a single dose of the drug that we call Intellia 2001 led to dose-dependent reduction in serum TTR levels. And what you can see on the graph here on the right, using 0.3 mgs per kg of the drug, we achieved a mean serum TTR reduction of 87%, and one of the individuals achieved a TTR serum reduction of 96%, almost complete elimination of circulating TTR protein. And no serious adverse events were observed during the observation period of 28 days during this trial. We are very excited about this approach, not only because of TTR but also because this provides a proof of concept for the platform. And we believe that data like this increase our probability of success for both our other knockout programs using the same rationale, same technology, but also the insertion programs that we're going to describe to you in the next slide. Regeneron has exclusive rights to Intellia's CRISPR technology for therapeutic targets that are targeting the liver. We have more than 20 programs in preclinical evaluation, active work happening in this program. And in addition to that, Regeneron is licensed to commercialize up to 10 ex vivo CRISPR products in defined cell types. Justin, next slide, please. So as I mentioned before, we are also using the CRISPR/Cas9 system in order to perform gene insertions in the genome. And here, we combined the precision of cutting the genome using CRISPR/Cas9, and then we are delivering a gene using an AAV and adeno associated viral genome, and we are basically getting insertion of this genome in the cut where we are carrying out with CRISPR/Cas9. This is a technology that we codeveloped with our collaborators at Intellia. And the goal there is to perform a permanent modification in the genome in order to start expressing a new gene. We are utilizing this technology for 2 hemophilia applications to express Factor IX and Factor VIII. And we have a lot of exciting preclinical data today. As you can see on the top of the icon panel here, we can achieve therapeutic Factor IX levels that are stable through 1 year. You can see a dose dependence here. When we are increasing the dose of the drug we are increasing the amount of circulating Factor IX levels in mice. And expression of Factor IX can be stable. And it lasts more than a year, as you can see in this example here. And of course, it's more than what is needed to achieve therapeutic levels. More importantly, the Factor IX levels persist following liver growth and regeneration. And in order to show that, we performed a model of a rapid liver growth by removing 2/3 of the liver and then allowing the 1/3 to grow back. As you can see here, when we are using traditional AAV gene therapy at the bottom left, and if you can follow the yellow bars, after we removed 2/3 of the liver and the liver starts growing, the AAV genomes start diluting out. They get lost. And then eventually, you lose expression. The expression of Factor IX does not come back. However, with the green bars, you can see that CRISPR-based insertion allows us to have permanent expression after liver regeneration because we have inserted this -- the gene in the genome, so these gene replicates together with the genome as the liver regenerates. And when we cut 2/3 of the genome, the liver grows back. And then Factor IX expression is maintained throughout the -- this experiment. So we believe that, unlike AAV-based gene therapy, CRISPR-based insertion is very promising in indications when you want to target a tissue that grows over time, when you want to target dividing cells. The Factor IX insertion program for hemophilia B is quickly advancing towards IND-enabling studies. And together with Intellia, we have several additional noted programs with preclinical work ongoing. Next slide, I want to highlight one example of a more "traditional" gene therapy. This is a targeted viral base gene delivery and expression that we are performing in collaboration with Decibel. And the goal here is to express a gene that is called otoferlin. What we know is the generic absence of otoferlin in hair cells of the inner ear cause profound hearing loss. It is estimated that about 20,000 patients in the U.S. and EU5 have loss of the gene, and that's the cause of their hearing loss. And we also expect that the pace in diagnosis to increase over time due to the recent adoption of genetic testing in that. So we should be able to find all the individuals that are affected by this otoferlin deficiency earlier and earlier in life. The goal here is to deliver a wild-type functional otoferlin gene in the appropriate cells in the inner ear. The important thing here is that these cells are non-dividing, so we don't expect expression to get diluted over time. What we have shown, and as you can see here at the top right, you can see a normal mouse at the bottom, and you can see the wavelengths of hearing, seeing that we can measure the hearing in the mouse. All the way at the top left, you can see that when the mice are deficient for otoferlin, you're basically getting a flat line during this test because the mice cannot hear. And then as you are expressing more and more otoferlin the hair cells of these mice, you can restore hearing. And you need at least 20% of your hair cells to be expressing otoferlin in order to restore hearing. So you can clearly see this dose response, but that also defines the therapeutic target for us. So we know that when we achieve more than 20% expression in hearing cells, we can restore hearing in our preclinical models and hopefully in the future in humans as well. So at the bottom right, you can also see that we were able to achieve expression of otoferlin in nonhuman primates. And what we are detecting here is the human otoferlin, as you can see with the purple red dots in the nuclei, and you can see here in blue, of hair cells in primate ear after we deliver locally the AAV-expressing otoferlin in the ear of these primates, again, demonstrating that we can express otoferlin in a primate. We expect the clinical trials for this program to start in 2022. And just like with all the other examples that we showed you, this is a proof of concept for the entire platform. We show that we can target cells in the year. Otoferlin is one of the many examples of genetic diseases that are causing hearing loss. So we believe that we can utilize similar technologies to treat other genetic diseases as well. And with that, I'm going to hand it back to George for some closing remarks.

Thank you, Christos. And hopefully, once again, everybody can hear me. I hope we have communicated the consistency in our principles and approaches and why there's so much reason to be excited about our future in genetic medicines. It's here and now. It's yielding near-term opportunities. And we think it's going to be yielding opportunities, dozens and dozens of them over the years to come. I hope you understand that our strategy, in general, is not one of in-licensing single opportunities. Instead, our strategy involves creating synergistic partnerships that can synchronize with what we can do internally and which we can help further empower and build on, resulting in world-leading turnkey therapeutic solutions that can yield entire pipelines, all going after targets elucidated and validated by genetics, giving us the highest chance of success in the clinic. And the collection of these capabilities give us enormous mix-and-match capabilities that we believe is unapproachable by the rest of the industry. For example, whether it's mixing a class-leading antibody with a class-leading sRNA or putting together some of these other modalities in gene therapy that you just heard about. And I hope you're as excited and inspired as we are about the future. And with that, we'll open it up for questions.

Great. Thank you, George, and thank you, team, for that great presentation. Truly cutting-edge science that we are seeing. The pace of innovation is incredible. Just a few questions, actually. I got some from clients and some I have prepared. Maybe we'll start with George on that front. I'd be curious to know how you are thinking about modality choices for some of the Alnylam target whilst in light of the recent Intellia data, how you are weighing RNAi versus the genome editing approach for targets where you can potentially use both these modalities.

Yes. I think that it's an incredibly exciting but also enviable position to be where one can mix and match the right tools for the right problem. For example, I do not think that one would want to be using a modality where you'd be treating millions and millions of people with a relatively early genetic engineering approach that I believe has to be vetted first before it can go to the level of using millions and millions. So for example, I would advocate, for example, in these rare disease settings or these growing disease settings, whether we're talking about TTR or hemophilia or so forth, whether it's using a knockout approach or a knock-in approach, that these are perfect opportunities for these cutting-edge new genetic engineering approaches. However, if it's a disease where you might potentially be treating millions, I think it deserves to be vetted a lot more deeply first. And approaches like antibodies or like siRNAs, for example, are much more amenable to those. And so I think that for each one, and case in point, we're in the position where we have all the tools in the toolkit. We can decide in which setting is it best to use an antibody, in which setting is it best to use an siRNA, in which setting is it best to use a genetic disruption or a genetic insertion and where we might actually want to mix and match these to get, let's say, total ablation, but not necessarily genetically. C5 is a perfect example. You -- I do not think want to create a human being that is permanently deficient in this critical complement pathway because we know one of the ways we want to allow patients when they occasionally and rarely do get an infection is to allow the normal system to sort of come back. So we have all these capabilities. We have all the choices. I think it's a very enviable position. Each one we think deeply about. We look at the genetics. We use the approaches that Aris was outlining to make these sorts of decisions, and we're doing them on a case-by-case basis.

Very helpful. Then maybe just focusing on the Intellia collaboration. Can you maybe just talk about the strategic goals? Obviously, the recent data from 2001 unlock the liver. Can you maybe talk about the tissues that you see gene editing going next? Are there tissues or organs which cannot be accessed to with this platform? What is your vision of this whole platform in general?

Yes. Right now the definitive applications are limited, we believe, to liver and to the ex vivo settings that we briefly talked about. However -- and we didn't have time to talk about it today, and maybe Justin will organize a follow-up meeting. Just as we've been investing deeply in what you've heard about for the last 5 to 10 years, we have also believed that the question that you raised is the true limitation of these sorts of approaches, whether they're CRISPR-based approaches, where they are the so-called more traditional viral delivery gene therapy-based approaches. The limitations in all of them is how to get it precisely into the cell of interest. And those discoveries have yet to be made figured out and turned into a practical fashion. That is something that we have been deeply investing in, that is how to target all of these therapies into one particular cell of choice that we believe is the huge bottleneck and the limitation to really widespread use of these approaches outside of the liver or ex vivo space. And that is something that I said that hopefully maybe Justin can organize a follow-up meeting in the not-too-distant future, where we highlight all the targeting approaches that we've undertaken. And just to give you a little preview into that, as you might imagine, we are leaders, obviously, in antibody bispecific approaches. And we believe that those types of reagents are the key types of reagents that will allow us, coupled to these various gene modification approaches, to allow them to be delivered right into the right cell of interest.

It may be worth noting that Intellia has continued to work on their LNP technology. And recently, they presented at a scientific meeting that they're able to hit bone marrow and hematopoietic stem cells. So they are also continuing to develop the technology.

Can you just -- Brian maybe or Christos, if you want to opine on just some of the learnings that you could apply from the ATTR program to the hemophilia program because that's where you have the partnership with Intellia, including other targets as well?

I think the biggest read-through for us is that we know we can make a cut, specific cut in the genome and hepatocytes. And so that makes us really excited about the insertion knock-in type programs. Christos talked about Factor VIII and Factor IX. And there's every reason for us to believe now that those programs should work. And that really opens up a huge range of diseases that one could go after using the liver as a factory for drugs.

Yes. And the biggest learning from the TTR program is the efficiency and the specificity of the technology. And by understanding what is the percentage of cells that are being modified in the liver allow us to calculate back exactly what we would need for insertion products, for Factor IX. Because there you need to deliver both CRISPR machinery and the AAV, so you need to combine 2 brands.

Okay. So the next question is focuses -- focusing mainly on the RGC. And the question is, like how do you ensure there that your database reflects the ethnic racial and genetic diversity if you are using a lot from the U.K. Biobank? And how is the database different from other pharma large-scale population-wide sequencing effort? And then the other continuation of it is that, are you using this platform to prospectively enrich the patient population coming out with the companion diagnostics so that you have a true precision medicine approach?

Okay. Great questions in there. So yes, genomic diversity is very important. And we can point to -- if you go back to the example of targets, right, you can go back to examples of genetic mutations that are enriched in certain populations, whether that's sickle cell disease or cystic fibrosis, right? So studying many diverse different types of populations allows you to find things that you couldn't find elsewhere. Same thing on the protective genetic side of things. So protective PCSK9 variants were first discovered because they were enriched in African Americans, right? And we have dozens of examples of where things are enriched in one group versus the other. I guess it's not well known, but our database is actually the most diverse that exists out there. So we have nearly 2 million people sequenced, and we have the largest subsets of that, that have been sequenced for African Americans or African ancestry, for Asian American or Asian ancestry. We did a very large study of 150,000 people in Mexico City, right? I mean this is the largest study ever of individuals of Mexican, Hispanic, Latino ancestry. So in fact, we do have a very large diverse database. It's not perfect, but we're committed, as part of our growth to get to 5 million or tens of millions of people over the years sequenced to dramatically enhance the diversity and representation in our data sets. You had asked other questions about how we build this and how it's different compared to other biopharma companies. We just didn't get a chance to go into it today, and we usually do when we go in depth about the RGC and how we've built this. It's been a massive effort, not just on the research and science side but also on the collaboration side. We have now about 110 collaborations around the world, where we're securing DNA samples and health information from properly consented volunteers. And we add about 20 or 30 of these projects a year. So while we talk about U.K. Biobank, that's just 1 of over 100 projects and rapidly growing. And these are large population studies like we just talked about, but they're also actually mostly disease-focused data sets, like the NASH ones we talked about that enabled that discovery, that have deep data and longitudinal data on that disease. So that is quite different. And in fact, as you've seen from -- or as you will see from the history of the RGC and its building partnerships, many biopharma companies now, almost a dozen have partnered with us in select areas to invest and co-fund and build specific projects in their interest areas. So our approach is quite broad and quite differentiated. I believe your last question was around the ability -- yes, companion diagnostics. So when a program needs a companion diagnostic, right, we can absolutely help with that, and we have a great precision medicine team at Regeneron to do that. Sometimes the targets and the programs work so well in everyone that a companion diagnostic is not needed. But I'll just point you to the fact that the cardiovascular outcome study we talked about. You should know that we're doing that approach for every development program. We're sequencing in every study. And we're applying those advanced analytics and trying to find -- if it happens to be in the underlying genetics and biology of those diseases, we're trying to find those examples we have high-risk and high-benefit individuals. So if the opportunity presents itself where a companion diagnostic would be absolutely game-changing for our development and commercial strategies, we're absolutely prepared to do that.

Just to emphasize a couple of Aris' point, just simplify them. As he said, the U.K. Biobank is only 500,000 of an over 2 million person database that we will have by the end of the year. So it's important. But as Aris said, we have the Mexican collaborations, Pakistan collaborations, all sorts of diverse collaborations. And we will be announcing, hopefully, shortly additional collaborations that Aris has been building and trying to get over the years. And just to be clear, there is no other independent pharma effort that remotely comes close to the scale and diversity of this effort. There is just nothing else comparable in pharma or anywhere else in the world. I mean, this is the largest big bio data set that's linked to human sequencing that's ever been created and that exists.

George, a question for you just on a broader scale. Obviously, a lot of scientific synergies there with these new modalities or new technology. Can you maybe talk about what needs to happen organizationally in order for you to capture it? Or is it already happening? And as you integrate these different platform, what is your view for some of these technologies, rather keeping them as a partnership versus owning them or buying them outright so that you can effectively integrate?

Well, we certainly agree that integration is key, and it is a challenge. And of course, you can always do better at everything. But that said, we have been working to integrate all of these approaches, as I said, over the last 5-plus years. And these efforts have all been highly collaborative and integrative between what's being done at our partner's shop and with us. I mean we view our partners essentially as extensions of our laboratories. And our folks, led by the leaders that you've heard from, are working hand in hand in all of the collaborations that we're talking about. I think that our strategy very much depends on these partners being independently structured and incentivized. We don't want to do what, for example, BMS did to Medarex. We think Medarex was a great company. It could have been a great competitor of ours in the human antibody space. But for those of you who've been around long enough to remember, BMS bought them for essentially their first 2 antibodies, their PD-1 and the CTLA-4 antibodies. And you haven't heard anything about that technology since then because they brought it in-house and essentially killed the company. So we don't want that to happen. We want to have the ongoing debate, the ongoing arguments. Trust us, we argue every minute of every day with our partners about every experiment. We do some of the experiments. They do some of the experiments. We share in all of that. All that integration is happening on a moment-by-moment basis. And it's led, like I said, by the guys that you heard from today. Can we always integrate better? Yes. But this is what we've been trying to do, and we've been trying to do this for more than 5 years. We don't want a partnership where we contract things out to somebody and we hear about it and we see what's happening in the clinic years later. We are part of building the technology. We're the ones who are helping create and empower it and making it even better than what it was. And we're hand in hand working hard with our partners to make sure that every lesson that we've learned in our 32 years we impart upon them to increase their chances of success. We think that, that is key to all of these relationships that essentially we're seeing them as extensions of who we are. But by keeping them independent, we're keeping them highly incentivized and able to fight us on each step of the way because we think that's part of the scientific process. We fight internally, and we argue and debate all the science with our partners in the same exact way.

Very helpful. Then with regard to the Alnylam collaboration, so we see now that you are going into some of the neuro applications of it like masking and gravity. Could you talk about the potential of the technology to go into some of the retinal areas or eye? What are -- are there any limitations there? And then how quickly we could begin to see some sort of a disclosure or data on that end?

Yes. Of course, any time you go into a whole new area, there are new challenges. But this is exactly why we want to collaborate. And these have been very collaborative efforts. As you might imagine, many of these starts with Brian Zambrowicz' shop. He creates genetically humanized animal models, which are the ones that we're using to test, whether it's the Alnylam siRNAs or the Intellia potential therapeutics. They're all tested in the humanized models that we're creating in the various tissues that we want to test them. And this is a highly interactive process. And we are learning every step of the way. And yes, we hope to in the relatively near future be talking to you about programs in the eye that we have co-developed with our partners, where we are hoping we will be able to announce that we have successfully achieved hitting in the target cells of interest in these structures with therapeutics that are targeting things in the eye or in the CNS. Once again, we create these collaborative models. We work together, and we now have the opportunity, whether it's siRNAs, whether it's a CRISPR-based approach, whether it's a gene therapy, viral-based delivery approach using targeting or non-targeting, all these things we're constantly doing. And hopefully, we will be rolling out our pipeline in all of these areas, whether it's brain and neurodegenerative diseases, whether it's eye and assortment of diseases there, whether it's muscle or other diseases or other tissues throughout the rest of the body outside of liver, together with, we believe, a very exciting and large portfolio in the targets and the sites that are amenable today like we've talked about, like liver, like ex vivo or like, as Brian brought up, maybe in vivo, some stem cell approaches as well.

Got it. George, so maybe spend some time or infinite amount of time on the genome editing and the silencing approach. Just maybe talk about your vision of the gene therapy or gene therapy approach. Obviously, a lot of interest in the area. And we have seen limited success there. So are there specific areas that you think are unique or untapped where you can leverage the RGC and successfully navigate where others have not been able to do so?

Yes. You're absolutely right. I mean it all starts with the genetics and having the right target, and that's where the RGC comes in. And that's why we believe historically in our programs so far, particularly over the last 5 to 10 years, where we've had the capability of the RGC. But before that, based on mouse genetics, that we are picking the right targets. We're having a high degree of success. But the technologies themselves also have limitations in bottlenecks. And in terms of gene therapy, as we've described today, one type of gene therapy is when we're delivering it to the liver, either to correct the deficiency, like you heard with Factor IX and Factor VIII, or where we're going to be using the liver essentially, as Brian described, as a factory to produce a biologic that is going to work elsewhere. . So we're excited about those novel approaches that we are really exploring and leading in with our collaborators, but also with the viral-based gene delivery. As I said, we know many of the limitations in those fields. One of the major limitations is you can't get the vector to the cell type that you want of interest while also simultaneously avoiding the immune system's ability to detect and clear your virus. These are exactly the sorts of things that we've been working on that, hopefully, maybe in a follow-on presentation, you guys will be hearing about how we are addressing those bottlenecks and how we believe that we're going to be taking viral-based gene therapy to the next level as well.

Okay. One specific question from investor. This is regarding the obesity, the novel targets in obesity. Could you talk a little bit more about how you are thinking about it? Is it more of a siRNA approach or more of an antibody sort of a combination? Just maybe if you can give a little bit more color.

Well, sure. I'll turn it over to Aris in a second. But this is an example of a target, which, when we reveal it, you'll find out, it actually is a target that is amenable to multiple technologies. And we're going to be trying to take on all of those technologies, even though it also happens to be a target, as you might expect, for something that controls appetite that's found in the brain. So with that and to talk about all the modalities that he's helping us undertake in this, I'll turn it over to Aris.

Yes. No, thank you, George. That's the big point. It will all be more clear in just a little bit. But this is a gene and target in a class of genes and targets that have been successfully drugged many, many times in the biopharma industry. So we know it's tractable. And to George's point, this is addressable by multiple approaches. So we absolutely have put pedal to the metal in terms of antibody approaches, some of these genetic medicines approaches, siRNA, and even more traditional approaches like small molecule approaches. And we'll have to see. This field, obviously, there's a huge unmet need. There have been tremendous late-stage successes recently where some of the most exciting late-stage programs are giving 10%, 15% weight loss over a couple of years. But when you talk about severe obesity, a lot more is needed. So we're really excited about bringing really strong validated genetics targets, protective targets, where we believe and have a high confidence of success with multiple of these approaches.

Okay. Thank you. I think with this, we came to the end of our allotted time. I thank everybody for listening in to the master, for listening in and to the Regeneron team for making us -- walking us through the presentation and this insightful dialogue. Thank you so much.

Thank you, Yatin. And we will have the slides posted on our website for those who want to reference them after the call.