Eli Lilly and Company (LLY) Earnings Call Transcript & Summary

Ladies and gentlemen, thank you for standing by. Welcome to the SARS-CoV-2 Neutralizing Antibody Update Conference Call. [Operator Instructions] As a reminder, this conference is being recorded. Now I'd like to turn the conference over to the host, Vice President of Investor Relations, Kevin Hern. Please go ahead.

Good afternoon. Thank you for joining us for Eli Lilly and Company's SARS-CoV-2 Neutralizing Antibody Update. I'm Kevin Hern, Vice President of Investor Relations. Joining me on today's call are Dave Ricks, Lilly's Chairman and CEO; Dr. Dan Skovronsky, Chief Scientific Officer; and Josh Smiley, Chief Financial Officer. During this conference call, we anticipate making projections and forward-looking statements based on our current expectations. Our actual results could differ materially due to a number of factors as noted on Slide 3. The information we provide about our products and pipeline is for the benefit of the investment community. It is not intended to be promotional and is not sufficient for prescribing decisions. I'll now turn the call over to Dave to provide some introductory comments.

Thanks Kevin. And thanks to everyone for joining us today. Over the course of this year, Lilly's response to the COVID-19 pandemic has been shaped by our sincere desire and sense of responsibility to mobilize the full force of our scientific and medical expertise to benefit the global community as we fight the pandemic. In the early days of the pandemic, we had predicted, as did many other experts, that monoclonal antibody therapy could be a high probability way to address moderate and severe patients' illness and bridge society to a vaccine. Pursuing this type of technology was also a great fit for our skills and technology, and it could be available in large quantities by the fall, predicting a potential fall surge back in the spring of this year. So I'm proud today that the work of my Lilly colleagues around the world and the impressive progress we've made in a short period of time. And I'm thankful for the contributions of many who have played a meaningful role in this progress, including our partners at AbCellera and Junshi Biosciences, our partners at the NIH and NIAID, all of the investigators who are participating in our SARS-CoV-2 neutralizing antibody clinical program, and of course, the many patients who have enrolled in the BLAZE-1 study we're talking about today as well as the other studies that are ongoing. I'm greatly encouraged by the partnership across our industry in collaboration with regulators as we collectively move at unprecedented speed to address the significant challenges set before us. Today's new news complements the progress we've already made in developing new treatments for the SARS-CoV-2 virus. These include: Shortening the time to recovery for hospitalized patients using baricitinib in combination with remdesivir in the ACTT-2 trial; establishing proof-of-concept for LY-CoV555 in the Phase II trial of patients in the ambulatory setting; and partnering with Amgen to significantly increase our global manufacturing capacity for COVID-19 neutralizing antibodies. We are pleased with the progress of Lilly's COVID-19 neutralizing antibody program, part of our broader effort to combat the spread of COVID-19. We were first into the clinic with neutralizing antibodies and first to share proof-of-concept data. This morning, we announced additional developments in our program, including that we submitted an initial request to the FDA for emergency use authorization for LY-CoV555 monotherapy in higher risk patients who have been recently diagnosed with mild to moderate COVID-19. We anticipate we could supply as many as 1 million doses of 700 milligrams LY-CoV555 monotherapy before the end of the year. We have new data demonstrating that the combination therapy with 2 of Lilly's SARS-CoV-2 neutralizing antibodies met primary and all key secondary endpoints in reducing viral load, reducing symptoms and reducing the rate of hospitalization due to COVID-19 and ER visits. We intended to -- we intend to submit a subsequent request to the FDA and other global regulators for emergency use authorizations for combination therapy in November, pending clinical trial enrollment once additional safety data accumulate and sufficient supply is manufactured. Today's update marks another important milestone for Lilly and the pharmaceutical industry's efforts to develop new treatments for the SARS-CoV-2 virus. While we are excited with the progress, the recent news in the U.S. of surging cases -- in Europe and U.S., rather, reinforces that the COVID-19 pandemic remains a significant global health concern and underscores the need for treatments and vaccines to combat this virus. So with that in mind, I'd like to turn the call over to Dan to give you a data update on the SARS-CoV-2 neutralizing antibody program.

Thanks, Dave. I'll start on Slide 5, which shows the 2 antibodies from which we have new data to discuss today. On the left of Slide 5, you see the antibody we call 555. This antibody was discovered by our colleagues at NIH, specifically the vaccine research center as part of NIAID and NIH and they're collaborators at AbCellera. And together with NIH and AbCellera, we've isolated an antibody from the blood of a patient in North America who recovered from the virus and created this antibody. On the right, you see the second antibody. This is what we call 016. It also came from the blood of a patient who survived COVID-19. This patient was in China. He was isolated by scientists at the Institute of Microbiology at the Chinese Academy of Science, working with our collaborators at Junshi. Both of these antibodies are very potent, high-affinity, neutralizing antibodies that bind the receptor binding domain of the spike protein of the virus SARS-CoV-2. They're fully human IgG1s and in cell culture models of virus -- in animal models of virus, including nonhuman primates, they show both efficacy in the treatment paradigm. So when animals that are a model of disease, these antibodies show efficacy as well as in protection paradigms where the antibodies are dosed prior to inoculation with virus. Based on the preclinical evidence in these animal studies, we had a very high level of confidence going into clinical trials, that is what supported our investment in manufacturing as well as parallel investigation across 3 indications, as you can see on Slide 6. We began studies in the ambulatory population. These are recently diagnosed patients with COVID-19, still mild to moderate at home. We started a trial in post exposure prophylaxis. This is in patients who are at long-term care facilities as well as staff at long-term care facilities, where they're experiencing an outbreak, and we're testing whether dosing individuals who have not yet gotten COVID-19 can actually prevent the disease. And in hospitalized patients in partnership with NIH, the ACTIV-3 trial that's testing LY-CoV555 as a potential treatment for hospitalized patients. Today, I'm going to focus on the ambulatory population, the recently diagnosed patients and specifically on the BLAZE-1 Phase II trial. On Slide 7, you can see the basic design of this study. There are 3 parts. We'll focus our discussion today on Part A and Part B, particularly, which is the new data that we're sharing. When you look at the design of this trial in Part A, you can see that we enrolled 3 cohorts on drug and 1 on placebo, 100 per arm. The doses of drug that were tested here were 700 milligrams, 2,800 milligrams and 7,000 milligrams. These doses were selected based on pharmacodynamic modeling and preclinical data that suggested 700 milligrams, the lowest dose that we tested, would actually be a maximally effective dose at neutralizing virus even in the lungs of patients. However, an abundance of caution and to make sure we adequately tested the hypothesis, we escalated doses above what we predicted to be the maximally efficacious dose and tested higher doses. Similarly, we went into combination therapy, shown in the green bars here. We tested 2,800 milligrams plus 2,800 milligrams of each antibody in the same population. We enrolled another 50 placebo patients alongside those combination patients, but the protocol and the analysis I'll show you called for pooling of those placebo patients, although I can tell you the effects we saw were consistent across the first 100 and the second 50 placebo patients. Below the line at the bottom, you see Part C. This is a different patient population. This is just focused on high-risk patients who are more likely to have severe outcomes from COVID-19. That study is ongoing, and I will not present any data from it. On Slide 8, you can see the baseline demographics of the patients that were enrolled in this trial and some of their disease characteristics across placebo monotherapy. And here, we're pooling all 3 dose arms for simplicity and combination therapy shown in the third column. The study population here was slightly more than half female, about 40% Hispanic or Latino, about 5% black or African American. The median age was relatively young at about 45, but there was a significant fraction of patients who are over the age of 65. Similarly, the body mass index on average was about 30, but there was a small fraction of patients who had very high BMIs at 40 or higher. Most patients had at least one risk factor as defined by the CDC for going on to get more severe COVID-19, things like age over 55, BMI over 30 or past medical history. But at baseline, most patients were mild in their symptoms or diagnosed with mild COVID-19. The remainder of the patients were moderate COVID-19. The population enrolled here was a recent onset population. You can see that the mean duration of symptoms, the time from which the patient had their first symptom of disease until they were randomized for infusion with drug or placebo was just about 4.5 days. The mean symptom score was measured on a 24-point scale, 8 different domains where patients were rated as mild, moderate or severe for each symptom. Out of that 24-point scale at baseline, patients were around a 6 or 7 in severity. On Slide 9 and 10, you can see the safety and tolerability data in this clinical trial. Both monotherapy and combination therapy were generally well tolerated. We could not see significant safety concerns, nor did we see clinically meaningful differences in treatment-emergent adverse events across the treatment groups. On Slide 10, you see the treatment-emergent adverse events that occurred in more than 1% of all patients. And again, we did not see differences across the treatment groups. Slide 11 shows the viral outcomes for this study. Viral load in this study was measured by (RT) PCR from nasal pharyngeal swabs. It was conducted at a central laboratory, and it's graphed here on a log scale and the change -- the graph is showing the change in viral load over time. You can see that placebo patients, shown in the red line have -- over the course of 11 days, they drop about 4 logs worth of virus. So 99.99% clearance of virus in the placebo group. And then you can see at early time points, both monotherapy and combination therapy showing a more rapid decrease in viral load. Although towards the end of the study, it is only the combination therapy that has a bigger drop in viral load. You can also see that the monotherapy arms were pretty tightly clustered, whether it was 700, 2,800 or 7,000 milligram dose at day 3 and day 7, although there is what I interpret to be some noise in the data by day 11. And you'll note that we previously had reported just the middle dose as reaching statistical significance because of that spread you see in day 11. For the combination therapy, it did achieve statistical significance at day 11 as well as the other time points at which we tested viral load, day 3 and day 7 were both statistically significant for the combination therapy, as well as another endpoint we looked at, which is simply the area under the curve for this graph from day 1 to day 11. So a clean study here on viral load for combination therapy. But we didn't fully understand what is the meaningfulness of viral load and changes in viral load over time because this was the first study of its kind that measured serial viral load in NP swabs of patients in an ambulatory setting. So Slide 12 shows one of the methods in which we interrogated this question. This is a spaghetti plot. Each line -- each gray line is an individual patient and their log viral load over time. So 9 is -- represents 10 to the ninth or 1 billion viral load, whereas 10 to the third is 1,000 and 0 represents on this graph not detected by our PCR assay. Most of the patients significantly cleared viral load over time, although there were a subset that did not. Shown in red are the patients who had severe outcomes in this study those were defined as hospitalization or ER visits. And you can see that at baseline at day 1, the patients who experienced -- who would go on to experience these significant events but did not have different viral load than the rest of the population, at day 3, they're starting to pull apart. At day 7, we saw a highly statistically significant difference between the patients who would go on to have bad outcomes versus the rest of the population and that's shown here by the Wilcoxon Rank-Sum Test. I note that this is a post-hoc analysis. We did this after we had the data. We don't have a way of adjusting for multiplicity. But the p-value here and the consistency of this effect over time makes us highly confident that this is not a chance finding. Rather, we believe it is true that patients who fail to clear their virus, patients who have persistently high viral load are the ones who are doomed to have worst outcomes from this disease, shown here by hospitalizations or ER visits. That may not be surprising, it's a viral illness. If you can't clear the virus, that means you're at risk for worst outcomes. That finding was supported by a similar finding, not shown here, on symptoms, where patients who were characterized as having persistent high viral load, not clearing their virus over time also had worst symptoms of disease. This is a very important finding. It gives us a treatment goal, which is, therefore, helping everyone clear their virus more effectively. So on Slide 13, we looked at that question, does treatment with monoclonal antibody help reduce viral load in patients who would otherwise have persistently high viral load or PHVL? So here, using a cut point that we've drawn from the previous analysis, we assessed the percentage of patients who actually have persistent high viral load. The good news is most patients clear their virus. In the placebo group, about 80% of patients significantly cleared their virus at day 7, and 20% were characterized as this persistent high viral load. You can see across the 3 arms of monotherapy, it was about half as many people that had persistent high viral load. That was statistically significant for the pooled population, and you can see the result in combination therapy that was highly significant. Again, though, this is a post-hoc cut point, and we don't have a method to adjust for multiplicity. On Slide 14, you see the important clinical outcome that we measured here, which is COVID-related hospitalizations or ER visit by treatment arm. In the placebo group, the rate was 5.8%. That's at the lower end of the range that we predicted at the onset of the study based on the patient population we intended to enroll, and we did enroll. We expected hospitalization events to be in the range of 5% to 10%. The placebo rate was relatively constant over time in both the first 100 and the second 50 subjects enrolled in this study. A lower event of -- lower rate of serious events was noted in each of the 3 monotherapy arms. You can see here I've pulled together 5 events. They were distributed 1-2-2 across the 3 arms and in combination therapy where there was only 1 event out of 112. The pool data for monotherapy is statistically significant. The pool data for combo therapy is statistically significant. And obviously, when we pool across all treatments versus all placebo, that also reaches that state. We noted when we looked at this data that the majority of the events, 7 out of 9 events in placebo and 4 out of 6 events on therapy, recurred in patients who are either older than the age of 65 or who had a body mass index greater than or equal to 35. That to us begins to define a high-risk population. You can see in placebo, of the 52 patients who met those criteria at baseline, they had a 13.5%, a very high risk of having a serious outcome. But on therapy pooling across arms, that was reduced to 3%. That 10% absolute difference in scores converts to a number needed to treat of about 10. If this data holds up, it would suggest that you need to treat 10 patients to avoid 1 severe outcome. On Slide 15, you can see the impact on symptoms by treatment arm. And shown in the graph on the left in red is the placebo arm. Remember, they started at a symptom score of about 6.5. And you can see that even on placebo in this mild -- mostly mild, but some moderate patient population, that was ambulatory baseline, they cleared symptoms relatively well and ended the study with a symptom score of about 1.5. Meaning on 1 to 2 items, their symptoms were mild. The treatment arms, monotherapy at each of the 3 doses, which are shown on the right but not on the graph, as well as combination therapy had similar and statistically significant improvement in symptoms. The 3 doses of monotherapy were not different on viral load. They were not different on hospitalizations. And once again, they did not appear different in terms of the effect they had on reducing symptoms relative to placebo. Both monotherapy, pooled and combination therapy were statistically significant, better than placebo on the prespecified analysis shown on the right. These data corroborate the hospitalization data. If we have fewer severe events, you may also expect that the average patient would have milder symptoms, and that's exactly what we saw. You can note the effective drug was relatively quick by 3 or 4 days into this study, the treated arms had pulled away from placebo and then remained roughly parallel for the rest of the study. On Slide 16, we summarize the major findings from the study. Both monotherapy and combination therapy were generally well tolerated at all doses. This trial was designed primarily as a safety and biomarker study. However, as I've shown you, we did see very meaningful clinical efficacy signals. Combination therapy looks very impressive on the viral end points. The primary endpoint at day 11 was met as well as the secondary endpoints of day 3 and 7, the time weighted average. Importantly, for both monotherapy and combination therapy, we really helped the outliers. We think COVID-19 is a disease of outliers. It's the people who don't clear their virus naturally, who are at highest risk of getting into trouble with this disease. And both monotherapy and combination therapy showed dramatic reductions in the percent of patients with persistently high viral load at day 7. We also analyzed the prevalence of what are uncommon but naturally occurring variants in the virus. There are several such variants that create a resistance to 555. They block the binding of the antibody. We saw those putative resistant variants to 555 in the placebo group. They are naturally occurring and sometimes turn up in placebo-treated patients with a prevalence of 7%. We also saw them in monotherapy. And on a mature data set, that's in 9% of monotherapy patients. Consistent with our theory that the combination therapy would not have resistant variance, we've not seen any in preclinical experimentation, and the 2 antibodies have different amino acids that they contact and, therefore, different susceptibilities to resistance. We did not see a significant number of resistant variants in combination therapy, less than 1% right now. The clinical endpoints for combination therapy were very similar to monotherapy. They've reduced hospitalizations both -- all 3 dose of monotherapy as well as a combination therapy to a similar extent. And the secondary analysis of change in mean symptom score was very similar across all 3 doses of monotherapy and combination therapy. So the summary shown at the bottom of the slide, combination therapy does appear more efficacious on viral endpoints likely driven by some of these naturally occurring resistant variants. But both monotherapy and combination therapy showed similar improvements on all clinical endpoints that were measured. On Slide 17 shows next steps for this program. From a clinical trial perspective, this study remains ongoing. As I showed you, we're enrolling this confirmatory cohort. We look forward to having data from these high-risk patients soon. The interim results from the monotherapy as well as subsequently the interim results from the combination therapy will be published in peer review journals. We are now planning to initiate a large open-label pragmatic study, which will likely include both monotherapy and combination therapy. We're also evaluating lower doses of drug here. We clearly haven't hit a minimally effective dose. We will go lower and see if that can help us stretch supply even further and help more patients. We do have registration of studies ongoing in other indications as well, as I commented on a treatment study in hospitalized patients with NIH, in prophylaxis, in nursing home residents and staff, the study we're leading in collaboration with NIAID. Until such time as there is an EUA, these clinical trials remain the primary way for patients to access these medicines. We have, as you've heard now, submitted for an emergency use authorization from the FDA for 555 monotherapy in higher risk patients. We'll follow that submission up with a submission for the combination EUA. We expect that to happen in November. We'd like to accumulate some additional safety data and continue to manufacture a combination until then. We do anticipate, based on our clinical trial programs, that for this indication, we could have a BLA submission for combination therapy as early as Q2 2021, focused here on the FDA path, but discussions with global regulators are also ongoing. On the supply side, we have invested at risk. We have large-scale manufacturing underway for both of these molecules. The 555 antibody is a bit ahead. We're currently able to supply 1 million doses of 555 monotherapy at the 700-milligram dose even by the end of this year. Combination supply is a little bit behind. We only have about 50,000 doses available by the end of the year, but that will increase substantially next year as additional manufacturing comes online, including our recently announced collaboration with Amgen. We are pursuing additional partnerships and intend to provide antibodies to resource limited countries as we fight this disease around the world. That ends my presentation. I'll turn it back to Kevin Hern from IR to moderate the Q&A.

Thanks, Dan. We'd like to take questions from as many callers as possible, so we ask that you limit your questions to 2. William, could you please provide the instructions again for how to join the Q&A session, and then we're ready for the first caller.

[Operator Instructions] Our first question will come from the line of Riley Griffin from Bloomberg News.

I have 2 questions for you all. The first and foremost is, if you do indeed get an emergency use authorization, how will the antibodies be distributed so that people can use it promptly when it is most likely to work? And the latter is, given the recent data, are you currently in discussions with the U.S. government's Operation Warp Speed for supply?

Yes. So we'll go to Dave Ricks for both of those. Dave?

Yes. Thanks, Riley. Important questions. Of course, we've been in contact with the Warp Speed team, as well as many other U.S. agencies throughout the entirety of the development program, and those conversations are ongoing. As you may know, we did not sign a pre-data deal, if it were a deal where they would pay us to keep working on this. We've been doing this ourselves. But we do agree with many that during a pandemic and during a situation where we will likely have more demand than supply, unfortunately, it's best to partner with the government to ensure a fair allocation within the country. Additionally, we will be working with countries outside the U.S. for distribution, particularly in hotspots where we see a significant viral outbreak. Those conversations will follow today's announcement of the EUA request going in. And so we do envision around the world partnerships with a number of governments in the early days of this being available and to agree on a protocol for safe and effective distribution to appropriate patients, which as Dan just highlighted, the higher risk patients. Through that means we hope that patients pay nothing or almost nothing out-of-pocket and that it will be available for patients to qualify.

The next question will come from the line of Meg Tirrell from CNBC.

I'm wondering if you can just talk a little bit about how you're characterizing high-risk patients in the EUA application. And also kind of what you're expecting back from the FDA in terms of speed on evaluating this?

Thanks, Meg. Dan, take both of those, please?

Yes. Thank you for those questions, Meg. So in this study, I showed a cut of data that showed age greater than 65 or BMI greater than 35. That's sort of a crude way to get it at high-risk patients. Of course, there's a wealth of data out there that suggests for much larger studies, which patients are likely to do poorly and end up hospitalized. I think it makes sense to focus limited supply in antibodies on those patients. I think the precise definition of that population will come with discussions with the FDA, which of course, will need to balance sort of the equitable distribution of drug and availability of drug with helping those who need it the most. Your second question is about time lines with FDA. Of course, we know and based on our interactions, we've seen this division that the FDA, the scientists are working incredibly hard. I think no different than -- it's not just an industry, but the agency is working around the clock, 7 days a week, trying to help fight this pandemic. Having said that, I think adequate and deep scientific review inevitably takes time. We've submitted a lot of data to the agency, and our expectation is that it will be a careful and thorough review at the agency.

The next question will come from the line of Terence Flynn from Goldman Sachs.

This is Dan on for Terence. Could you please just discuss if these data increase your confidence in seeing an impact in the hospitalized setting and in the prophylactic setting and when you may be able to share data from both of those settings?

Thanks. Dan, we'll go to you for those.

Yes, thanks for the question. Of course, they must increase our confidence. If we'd had a negative study in this population, our confidence would be lower. So it has to be good news. But these are different indications in different populations. So I can't sort of promise success here. I think in the hospitalized patients, particularly, it's unclear how much of the disease burden as the patient progresses, particularly in intubation and worst outcomes, is driven by persistently high virus and how much of it is driven by aberrant immune response, given positive results from immune modulatory drugs late in the disease course, such as our own baricitinib, which we announced in collaboration with NIH as well as drugs like dexamethasone. Clearly, there's a component laid in the disease of -- immune system that is causing problems. On the other hand, perhaps earlier in hospitalized patients, there's evidence that antiviral mechanisms can play in that. Uncontrolled viral proliferation is still a problem in some patients. So we're encouraged, but I think we have to see the results from this very important trial. The prophylactic indication is one that we've always had the most confidence about. When antibodies for viral illnesses work in the treatment setting, to my knowledge, they are always -- or is almost always work in the prophylactic setting. It's easier because viral loads are lower at that time period. That study is ongoing. It's a large trial. It's event-driven. You can think of this as a bit like vaccine trials because we have to wait until there's been a certain number of events post randomization to unblind the study and see if those events were actually in placebo or in treatment arm. So we're optimistic, but it could still be some time before we see that data.

[Operator Instructions] Your next question will come from the line Peter Loftus from Wall Street Journal.

I'm wondering if you could say more about what the potential cost of this would be, the monotherapy or the combination therapy, and not only to patients out of pocket, but just generally speaking, how much it would cost per patient? And would this be something that you're providing on a nonprofit or at cost basis?

Thanks, Peter. We'll go to Dave for that.

Sure. Pete, thanks for the question. Obviously, an important but complicated question. As -- just to reiterate, we do want to make sure that patients have no or very, very low out-of-pocket costs anywhere in the world to receive this therapy, should it be approved. I would say on pricing, a couple of things come to mind. The concept of doing a cost or cost-plus something is a difficult one because, of course, defining cost is a difficult exercise, particularly given the R&D situation where it's front-loaded, it's at risk, if the therapy fails, how do you account for those costs, et cetera. So we're working through that. The one overriding principle that we've decided on is that whatever we end up charging, it should create value for society beyond Lilly. So that -- whatever the cost offset, probably direct cost offsets, that can occur upon reduction in hospitalization or ER visits or other problems associated with COVID-19 that we should clearly have a clear value story that creates value, not just for us, but for everyone else in the system. The second principle we're following, which we'll talk more about as we engage more deeply with foreign nations, is to have a tiered pricing scheme where we don't create big differences between countries. We don't want to allocate this product based on ability to pay or even to the highest bidder. Rather, we're going to predefine tiers based on GDP per capita or metrics like that and really ask wealthy nations to pay more than poor countries. And then finally, we are working actively with several philanthropic partners on making this drug available in the so-called Gavi countries or the low- and middle-income countries as defined by the WHO. Several of those countries have severe outbreaks going on. They clearly don't have the means to pay something like the U.S. or the U.K. or Japan would be able to pay. And so we're looking at a more philanthropic approach in those markets. More information on that coming soon.

The next question will come from the line of Geoff Meacham from Bank of America.

I just had one on data and one on commercial. So Dan, I know hard to say, but what's your perspective on the correlation between persistent viral load and symptoms or hospitalizations? I'm just trying to figure out what's predictive and maybe what metric is the most meaningful as you develop. And then on the commercial front, where do you guys imagine the broadest use of antibody therapy, I would think in infected patients and perhaps those not doing well, but compare this to prophylaxis or mild patients that are maybe more [ asymptomatic ].

Thanks. We'll go to Dan for both of those.

Yes. Sure. So the first question there was about the correlation between persistent high viral load and poor outcomes, hospitalization, ER visits or symptoms. I think you're sort of asking what's cause and effect here. Hard to know for sure, and this data don't explain it or can't prove it one way or the other. But I think it's rational to assume that there are a variety of factors that would lead a patient to have poor clearance of virus. It could be that their immune system is less well suited to react to the virus, or it takes a little bit or longer time to ramp up. That's probably what leads to PHVL. And then PHVL itself is clearly a marker for worst outcomes. That could be because it's related to colonization of the lung. So we're measuring viral load in the nasal pharynx. It's a surrogate for what we probably really care about, which is virus in the lung. But I assume that patients who have colonization of the lung and resultant pneumonia and poor outcomes are going to be the ones that have persistent high viral load. So the goal is to stop that from happening, knock the virus back in its tracks, give the immune system time to clear it out prior to the patient getting pneumonia. I think that's likely the sequence of events that we're seeing in this trial. With respect to sort of the patient opportunity and which patient subsets we can help the most, I think that is yet to be seen. Right now, we can see an effect in early, recently diagnosed patients. We still have by and large mild disease and preventing them from hospitalization. So that's the key way we can help patients today. As more data come out, we'll address those other opportunities as well. Of course, the hospitalized population is serious, and we need to help those patients any way we can. But that's a smaller impact that one can have once they're already in the hospital. Keeping people out of the hospital is really a huge impact. Prophylaxis, you asked about also, that's mixed in there with vaccines. We expect, and I think in some ways, this data may make us more confident that vaccines, which raise a similar immune response against the spiked protein, may also be ultimately successful. And there, they obviously will offer longer-term protection than a monoclonal antibody. Still, there may be some patients who are left behind or don't have good immune responses to vaccines. And ultimately, the prophylaxis here with a passive approach such as this could be helpful.

Next question will come from the line of Seamus Fernandez from Guggenheim.

Great. So a couple more technical questions. So Dan, can you help us understand what experimentation was done with the Junshi antibody versus 555? I just want to -- you're confident that 016 is not actually carrying all of the efficacy here, and I'm sure that you guys have preclinical data to suggest that. And then the second question is as we look at the individual data sets, I've gotten a number of questions coming in myself on the choice of the 700. And I assume that this is just basically, as you looked at the viral load, as you looked at the outcomes and then the events that basically what you were seeing was overlapping confidence intervals across the entire data set, and that's really what drove the decision to move forward with 700 rather than a decision to just go broadly. And then just one final question. On resistance, are we seeing less resistance with the combination? Or is resistance still a potential challenge that you need to manage for these?

Good. Thanks for your question, Seamus. So I try and remember and hit them in order. So the first one was on preclinical or nonclinical characterization of the 016 from Junshi versus the 555 from AbCellera and NIAID. These are both very potent antibodies. I think in preclinical experimentation, 555 may have some advantages in potency. But really, these are both real options. In terms of the clinical data and the difference in the combo and the monotherapy, really a lot of that difference can be accounted for in Virology based on those resistant variants. So we know in preclinical experiments that they have nonoverlapping sets of resistant variants. So having the 2 of them together probably knocks down a virus even if it is one of those resistant variants. That's particularly important in the later time points when viral load in everyone is a bit lower. And if there's something left in the presence of 555, it's likely to be one of those resistant variants. So the data that we saw, with the combination sort of perfectly matched our theory that adding second antibody mops up that remaining virus. We don't have data on 016 alone. And so I can't sort of directly address your question, but I feel quite confident in the hypothesis I stated. With respect to the dose selection here, as I said, our preclinical modeling and then even once we have this clinical data, we have exposure response modeling now, all support that these 3 doses are not different. That's across virus measures, across persistent high viral load measures, across hospitalizations and across symptoms. There were small differences between the 3. Sometimes 700 was better. Sometimes 2,800 was better. We don't interpret any of those differences as meaningful. So given that we haven't established a minimally effective dose, it does make sense to proceed with the lowest dose. If there were any safety issues, we haven't identified a specific drug-related safety issues right now that are dose-dependent or anything like that. But if there were a lower dose, would be better. But really, most importantly is the lower dose, it allows us to manufacture more and help more patients in the face of very similar efficacy. And then finally, with respect to the resistant variants, yes, you're correct. These antibodies are complementary, and we are not seeing those resistant variants in the combination therapy arm, as I noted, less than 1%.

[Operator Instructions] Your next question will come from the line of [ Leigh Ann Winick ] from CBS News.

I'm just wondering in light of the President receiving a Regeneron antibody cocktail, I'm wondering if the Lilly antibodies are being used for compassionate use and how you think they can complement the Regeneron versions?

I'm sorry, [ Leigh Ann ], I missed the end of your question. Could you restate it?

Sure. So I was just saying, is there compassionate use for the Lilly antibodies and how do the Lilly antibodies work differently compared or complement what the Regeneron product does?

I see. Okay. The second question, the basic strategies are the same, and we're rooting for Regeneron's success as I'm sure they are for ours, because the main constraint here is manufacturing capacity. And many have opined on this, but it seems important to get as much material as available as possible to prevent the hospitalizations that Dan was describing. Neither company plus all our partners could produce enough for the world right now based on the incidence of the disease. So low doses is a great strategy to spread that limited supply further. That's another answer to the question about why 700 and why we're going to explore even lower doses. But we certainly hope they succeed, and the strategies are nearly identical, although the drugs are different. And we'll have some different properties, but likely correlate in their probabilities of success, et cetera. We had not opened -- I don't know the details of Regeneron's choices. It's not uncommon in drug development that one establishes sort of an official compassionate use program. In parallel with controlled studies where patients are randomized, we had not done that. And the main reason we had not done that wasn't the potential need for compassionate use, but rather the incredible need for controlled clinical data and the urgency of developing that data. Sometimes setting up those programs can distract from recruitment to controlled programs. There is a vehicle, a single patient IND pathway. The FDA allows for any study drug that is available for patients who are interested in this therapy. We have not advertised that, and it's a little bit of a cumbersome procedure because we have maintained a long -- that this drug should produce randomized data. And when it does, as we're displaying today, it should be broadly available via the emergency use authorization procedure, which was designed for a pandemic and designed to approve drugs that appear safe and effective and could help. That's why we've applied for one, and that's why we expect to get an emergency use authorization, first for mono and then later in the fall for the combination. I hope that answers the question.

The next question will come from the line of Louise Chen from Cantor.

Congrats on the data. So first question I had was, do you have any thoughts on your combo data versus Regeneron's cocktail data? How do you think about different subpopulations like baseline viral loads and how that might play out in the real world? And then second question I had was, I know you mentioned the resistant patients, but what other patient populations do you think will be best treated with mono versus combo therapy?

Thanks, Louise. We'll go to Dan for both of those.

Yes. Thank you, Louise. So the first question was asking me to make cross-company, cross-trial comparisons with Regeneron, which is hard to do. I just point out that on the whole, we see a lot of similar trends in the data, including reduction in viral load, reduction in symptoms, reduction in medical events. That's good. I think your second question was on subpopulations and probably noting that Regeneron's analysis emphasized the serology negative population at baseline. It could be that we have a somewhat different population here, some of the serology that's still trickling in here. But our baseline serology positive rate is quite a bit lower than what they reported, sort of in the 10% to 15% range, I believe. We don't have yet a subgroup analysis. And probably, there'll be too few patients to see whether one of those groups is better than the other. We reported here effects on the whole population. So everything I've shown you is across all the patients enrolled rather than a subgroup analysis. So I think in a small data center, we just have to be careful about cutting this data too many different ways. The one thing that we showed you was that the hospitalization occurred mainly in people who are older or obese. So that's the one subgroup that we look at here. And I think it's probably the -- interesting population just given the wealth of data that shows those are risk factors for more severe outcome. In terms of who should get the mono versus the combo, I don't think there's any way of knowing this at baseline really that is practical in any sense. The strategy here is that in the next 3 months, we have 1 million doses of monotherapy. That's what we've applied for emergency use for. That's what, if it's granted, will be available for patients. Over time, we'll learn more if these resistant variants turn out to be as I might hypothesize, sort of partial treatment failures, then probably the combination therapy will be a longer-term solution for everyone. More data to come there, but we're really excited about the consistent clinical effects we're seeing here with both monotherapy and combination therapy, which so far aren't different from each other on clinical outcomes.

Maybe, Dan, I can just add a practical point, too, which is given the difficulty of testing in today's environment, the selection of high-risk patients of -- based on age and weight seemed simple to us, and it does stratify significantly. So in a practical clinical setting is something that could be applied immediately and thus the basis for our data cut that way.

Next question will come from the line of Carolyn Johnson from Washington Post.

If you obtain the EUA, will the outpatient trials continue or -- and how will you persuade patients to volunteer and get more data about which subpopulations benefit? And also, is there a risk to using a monotherapy given the resistance that you saw or how do you think about the clinical implications of that?

Thanks, Carolyn. Dan, for both of those, please?

Yes. So Carolyn, the first question was will the trials continue, yes. Our intent is to continue trials. Of course, we have a number of trials ongoing, as you saw on that first slide. Many of these trials offer monotherapy versus combo therapy. Some of these trials are -- include patients who are -- wouldn't be classified as high risk. And so that would be a population that wouldn't have access under EUA. And then some of these trials are in different indications, which also wouldn't be qualified under EUA. I think if anything, perhaps EUA could stimulate enrollment in these trials, probably even in initial days under emergency use authorization. It may be difficult for patients to uniformly access drug and get set up for infusions and things like that, whereas the clinical trials offer a ready way to do that. So if anything, we expand our emphasis here on clinical trials even through an EUA period. With respect to your question on is there a risk from these resistant variants, we haven't seen it. I think in our analysis, even in the presence of resistant variants, the outcomes look not different for monotherapy versus combination therapy. But I guess, we further characterize that over time. I'd just point out that resistant variants crop up even in placebo-treated patients. So as part of your normal immune response to virus, it can make different variants, some of which can be resistant to different antibodies. We haven't seen and are interested to learn more about potential resistant variants to other therapies. For example, remdesivir or convalescent plasma, it's quite likely those are out there. We did extensive sequencing here. And so we're able to sort of fully characterize the variants in virus over time.

Next question will come from the line of Steve Scala from Cowen.

I have 2 questions. Why did Lilly collapse all the monotherapy doses when presenting the clinical endpoints but not one presenting the viral load data? And what specifically is the effect of the low monotherapy dose on hospitalizations? And then the second question is, were the hospitalization rates seen in the placebo arm consistent with the epidemiologic data in the U.S. to date?

Thanks, Steve. We'll go to Dan for both of those.

Okay. I can't probably answer a why question, but I can tell you what the rates were in each of the 3 arms for monotherapy. It was 1, 2, 2, I think I said it was the rate of hospitalizations or ER visits in low, mid and high dose. With respect to the -- that's how the 5 events were distributed across the 3 arms, which were roughly equally sized. So it turned out 700 only had one, but I don't interpret that as meaningful. I interpret them as not different. On Slide 11, I think it was, which was the -- no, that's the viral load slide. The -- is it? 15 is the symptom slide? And although the graph was too crowded showing the 3 symptom lines, you can see the numerical results on the right side of the slide there. It actually turned out that the 700-milligram dose looks numerically very good. Again, don't interpret these 3 doses is different, although that one was slightly more statistically significant than the others. It was very consistent across the monotherapy doses.

Placebo response, Dan, on outcomes.

Yes. Sorry. Thanks for reminding there. Actually, your second question was on placebo response rates. When we sketched out the study and started it, we predicted a 5% to 10% rate of hospitalization of placebo group based on all of the sort of population level data that's available in the United States. We fell a little bit on the low end of that. Probably outcomes could be a little bit better for people in clinical trials, but it was not inconsistent with what we expected. I think the treatment arms, on the other hand, are really quite different than what anyone would predict from the natural history of this disease.

[Operator Instructions] The next question will come from the line Remy [indiscernible] from HBC News.

So I wanted to follow up on the question of time line. Has the FDA given you any indication of how long it will take to complete its review? Will it be days or weeks? And my second question is whether while conducting these studies in nursing homes, you've monitored overall case numbers in the involved nursing homes? If so, do you have a sense as to whether there were fewer overall case numbers or proportions when more of the nursing homes residents were enrolled in the study?

Thanks. We'll go to Dan for both of those.

So the first question again is on time lines. I just point out that we've been working with this review vision for months now at an incredible pace, really. I think exciting to see the engagement between regulators and companies here in the face of a public health crisis. And my expectation is that will continue. As I said before, they're working as hard and as fast as they can. And we support them with the information as quickly as we can. Yes. What was the second question? Sorry, I didn't write it down.

The nursing homes and what you're seeing?

Yes. Is there a...

Yes. Too soon to say. I think we track the total number of events rates, but we don't look at that by institution. Or obviously, it's for blinded sort of studies, so we can't know the answer to that.

Your next question will come from the line of Vamil Divan from Mizuho Securities.

So just one on the EUA discussion. Can you just comment on sort of the extent of safety data that you submitted? And you said there's something around [ 150 ] patients that have now been treated with 555 and monotherapy [ and combination ]. How much of that has been submitted? And what's the sort of longest follow-up period you have on these patients? And also, is the monotherapy EUA for the 700 milligram or is it the 2,800 or both? And then the other question I had was just around the Part C of this BLAZE-1 trial. So it sounds like, if I got the numbers right, about 2/3 of these patients in Part A and B were already in that high-risk cohort. So I'm just trying to get as to how is Part C different from what you already saw in Part A and B? Or is it just sort of running impression and other trial, just get some more data, but similar sort of population, about 2/3 of this group that's already high risk.

Thanks, Vamil. We'll go to Dan for both of those.

Yes. So for the first question, which was on the extent of safety data submitted to the EUA, of course, we'll have summary analysis of all of the safety data that we've collected. But some patients, as you observe, are in ongoing trials. There were, I think, 300-plus patients on monotherapy. In this trial, they have at least 1 month follow-up now. And I think importantly, 1/3 of those patients actually have exposures of 10x the level 7,000 milligrams versus what we're applying for, which was your second question, we're applying for the 700 milligram. So we have a reasonable safety database here. Of course, it will expand over time, and we would closely watch safety under an EUA. But given the characteristics of this antibody and the data we've seen to date, we do think this is an appropriate safety database to pursue to EUA. I think that was your first and second question. Your third question was just on, I think, the difference between the Part C and Part A and B. These are higher risk patients. Some of them would have been eligible for Part A and B, as you point out, I don't know the exact percentages. But the goal here is to have an enriched population so that we see more events. Of course, we don't want anyone to be sick and have a bad event, but the goal here is to more rapidly come to a conclusion by reaching for a population that's more likely to have hospitalizations or ER visits. And that study is underway.

Next question will come from the line of Navin Jacob from UBS.

Yes, Navin Jacob. Three, if I may. Number one, just the resistant variants between -- were there any -- were you able to sequence the variants? And how different are they between monotherapy or between the drug arms and placebo? And does it look like there's any one specific type of variant coming out of the drug arm? And if you know anything about those -- the relative fitness of those -- that variant or those variants, that would be helpful. And then, were you able to track baseline serostatus? I know there's some questions on viral loaded baseline, but just specifically on serostatus? And does it track with viral load and hospitalization rates, if you were able to make some correlation there, that would be helpful. And then last question, sorry if I missed this, but are you working on or do you anticipate working on a subcutaneous version of these antibodies?

Thanks, Navin. We'll go to Dan for all of those.

Okay. Thanks. So the first question was on resistant variants. And I think it's a complicated situation because there are so many variants of virus that naturally occur, even in the placebo group. I get the number wrong, but probably there's more than 1,000 variants that we characterize just in the placebo group. So these things are normal, and they happen. If you look closely, you can find them. We're focused here really on a handful, I think. Probably really just one particular resistant variant that was present in a few more patients in drug-treated arms than placebo-treated arm. We don't see any difference. Certainly, it's not a more fit virus in any way -- in any of our experiments. Importantly, though, we also have data that the natural immune response effectively neutralizes this variant. So we have done those kinds of experiments using samples from, for example, placebo patients. We also know that all of the patients that I've seen at least by day 29 become seropositive, so they generate their own immune response, which clears virus wild-type variant equally well, and they disappear. So that's all good news, and that's sort of how I think about the variance. In terms of serostatus at baseline, you asked about, that is your second question. As I said earlier, we have a relatively small fraction who are positive by the serology assay we used here, which is the Roche Elecys assay, which is a commonly used highly automated assay. So I don't have any subgroup information. I did look at the hospitalized patients and to my recollection, some of the hospitalized patients were serology negative at baseline, others may have been serology positive. So I don't know if that's going to be a perfect predictor of hospitalization. And as Dave mentioned earlier, it's just so much easier to focus on the risk factors that we can see immediately like age or body mass or chronic medical conditions. And then finally, you asked about subcutaneous. We are exploring other routes of administration. The first objective here is to get to a much lower dose. That may be possible, we don't know yet. Those experiments are ongoing, and those clinical trials are ongoing. We also don't know about Tmax and how important that is and whether a rapid onset of action is needed or subcu is fast enough. We should have answers to those questions really in the next couple of months. And I'm hopeful that we can go lower in dose, and I'm hopeful that we'll be able to make a subcutaneous dose that works just as well, but we have to test that.

The next question will come from the line of David Risinger from Morgan Stanley.

Congratulations on the news. So my 2 questions are first, you disclosed ER visit or hospitalization events. Can you provide perspective on hospitalizations alone, which may be a more rigid metric on clinical benefit? And second, could you remind us about the economics with your partners, including details on how Lilly needs to share profits with the partners?

Thanks, Dave. We'll go to Dan for the question on hospitalizations and then Josh for the economics of partners.

Thanks. The prespecified composite endpoint in our trial was actually ER visits, hospitalizations or deaths. There were no deaths in any of the arms here. In terms of ER visit or hospitalization, many of the hospitalizations started out as ER visits, but nearly all of the ER visits eventually turned into hospitalizations. I think there were 2 initial study that didn't result in hospitalization.

Thanks, Dan.

Thanks, Dave. In terms of the structure of our agreements, they're pretty straightforward. We share -- we'll provide royalties to AbCellera and Junshi on any sales that we book as a function of this. Junshi does have rights in China for their antibody. Otherwise, we're sort of around the world, we'd be the lead partner and pay royalties back as we would do in other sort of normal situations.

The next question will come from line of Umer Raffat from Evercore.

This is Mike DiFiore in for Umer. Congrats on the data. I have just 2 clarifying questions on viral versus clinical improvement. Number one, regarding the monotherapy dose response, like why did the higher 7,000-milligram dose of monotherapy not show the same level of antiviral effect than either mono or combo therapy, each of which were at lower doses? And is there some level of inverse or U-shaped dose response associated with 555? And number two, and apologies if I missed this, but not to beat the dead horse, despite having a higher viral clearance, did the combo therapy only have a marginally better clinical efficacy versus monotherapy simply based on the combo covering additional resistance variants? And if so, like would it be fair to expect a bigger clinical difference in time if those additional resistant variants become more prevalent?

Thanks, Mike. We'll go to Dan for both of those.

Yes. So your first question was on dose response. I think we showed that in the dotted lines on Slide 11. All 3 doses look very, very similar at the early time points. I wouldn't over-interpret the day 11 time point here. We see some of the spread here is likely to be noise. At this time point, the average patient in this study had a sample that was at a level of positivity that if we replicated at 10x, it might be negative half the time and positive half the time. So it's right at the edge for the average patient of the limit of detection of our PCR assay. I also -- although on the graph, it really looks like the combo is doing much better at the late time points, those are large logged differences on small amounts of virus. So once the viral load has gone down from, say, 1 billion copies per mil to 100,000 per mil, the difference related to smaller declines of virus may be less clinically meaningful. I think what's really important for patients in what both monotherapy and combo therapy are able to do here is to help those patients who never get away from the really high viral load and knock them back so they look like everyone else. I think reducing someone who already has a low viral load to a very low viral load is interesting. We see that the combo can do that, but I doubt that's clinically meaningful. And in fact, our data didn't show any clinically meaningful for those kinds of reductions in viral clearance at the late days. I think that probably answered both of your questions at once.

Thanks, Dan. Umer (sic) [ Mike ], thanks for your call. We'll go now to Dave for the close.

Thank you. In closing, the company remains resolute in our commitment to battling COVID-19. And we are encouraged with the speed at which we have been able to advance potential treatments to address the significant unmet medical need. And we look forward to continuing leveraging our capabilities and resources to sustain the progress in the fight against this virus as well as other diseases. We thank you for participating in today's call and your interest in the company. Please follow up with our Investor Relations or communication teams if you have any additional questions we weren't able to get to. Have a good rest of your day. Thank you.

That does conclude our conference for today. Thank you for your participation and using AT&T conferencing. You may now disconnect.