Tourmaline Bio, Inc. (TRML) Earnings Call Transcript & Summary

Good morning, and welcome to today's investor webinar. Thank you for joining us. We will be recording today's event, which can be later accessed on the Events page at Tourmaline Bio's website at www.tourmalinebio.com. [Operator Instructions] I would now like to introduce Tourmaline Co-Founder and CEO, Dr. Sandeep Kulkarni.

Thank you, Daryl. Good morning, everyone. On behalf of the entire team at Tourmaline, I want to welcome you to today's webinar understanding the genetic validation for IL-6 inhibition in cardiovascular disease. We are honored to be joined today by Dr. Dr. Dipender Gill, CEO and Founder of Sequoia Genetics. As he explores the latest advances in leveraging human genetics to inform therapeutic strategies, especially those targeting high-risk cardiovascular patients. I'm also joined today by Dr. Emil deGoma, our SVP of Medical Research and a Board-certified cardiologist; Gerhard Hagn, our SVP, Head of Commercial and Business Development; and Ryan Robinson, our Chief Financial Officer. Before we dive in, I want to quickly address some housekeeping items. As you may know, we'll be discussing forward-looking statements during this presentation. These statements reflect our current beliefs and expectations, but they are subject to various risks and uncertainties that could cause actual results to differ from those discussed today. I encourage everyone to review our filings with the SEC for more detail on those risks. Here's the agenda for today's program. I'll begin with a few introductory remarks. Next, our expert guest, Dr. Gill, will present on how genetic validation is being incorporated into drug development and the related evidence supporting IL-6 inhibition in cardiovascular disease. Then Dr. DeGoma will present an overview of our development program for pacibekitug in cardiovascular disease. Finally, we will end with a question-and-answer session. At Tourmaline, we are driven by our mission to develop transformative medicines that dramatically improve the lives of patients with life-altering immune and inflammatory conditions. In short, we look to advance medicines that have the potential to define new standards of care. Guided by this founding mission, we acquired the rights to pacibekitug in 2022. pacibekitug is a long-acting fully human anti-IL-6 monoclonal antibody with what we believe are potentially best-in-class and differentiated properties, including a naturally long half-life, low immunogenicity and high binding affinity to IL-6. These attributes have been observed to date across 6 completed clinical trials, encompassing approximately 450 study participants in total. We are currently conducting 2 clinical trials with pacibekitug, representing 2 different but compelling therapeutic areas. In thyroid eye disease, we are conducting spiriTED, a Phase IIb pivotal clinical trial. And in atherosclerotic cardiovascular disease, or ASCVD, we are conducting TRANQUILITY, a Phase II trial looking at reductions in key inflammatory markers, which we will discuss in more detail later on. We are well capitalized with cash runway into 2027, enabling us to execute on and deliver clinical trial data for the 2 strategic paths I outlined a moment ago. Today, we will focus on the potential of pacibekitug in cardiovascular disease and in particular, on atherosclerotic cardiovascular disease. At its foundation, atherosclerosis is understood to be a chronic inflammatory process, and there is growing recognition of the role that inflammation plays in driving the occurrence of major adverse cardiovascular events such as heart attack, stroke and cardiovascular death. This inflammatory risk is independent of other risk factors such as LDL and other lipid levels, thereby representing a new source of risk that has been poorly addressed to date. With that backdrop, there are 3 converging lines of evidence, all of which support the potential of IL-6 inhibition in reducing the risk of major adverse cardiovascular events in patients with ASCVD. These 3 lines are human genetic evidence, epidemiological evidence and clinical trial evidence. Today, we will be focused on the importance and predictive power of human genetic evidence. Genetic validation provides a powerful set of tools for derisking mechanisms and prioritizing therapies for late-stage development. We find the many independent analyses providing genetic validation for IL-6 inhibition, including those conducted and published by our guest, Dr. Gill, to be highly compelling and consistent with the other lines of evidence. Taking a step back, what do we mean by human genetic evidence? Human genetic evidence and mendelian randomization studies specifically inform a causal association between genetic variants and outcomes. These tools have become widely used among companies seeking to develop drugs and prioritize targets, particularly within the cardiovascular disease therapeutic area. Moreover, the existence of human genetic evidence is becoming a de facto prerequisite for launching cardiovascular outcomes trials. Simply put, a target that has genetic validation has a higher likelihood of success compared to a target that does not. With today's webinar, we have 3 main objectives. First, to outline how to leverage and interpret genetic validation studies. second, to demonstrate how genetic validation can be used to derisk the development of novel mechanisms. And finally, to review the already robust body of evidence supporting IL-6 inhibition in cardiovascular disease. I would now like to turn it over to Dr. Dipender Gill, Founder and CEO of Sequoia Genetics. With over 250 published papers and significant contributions from Mendelian randomization research, Dr. Gill is recognized as a leading voice in translating genetic data into actionable therapeutic strategies. Dr. Gill, thank you for joining us today.

Thanks, Dr. Kulkarni. Absolute pleasure to be here, and it really is an incredible time to be using genetics to inform and prioritize drug discovery and development efforts to the extent that actually, I think we're going to see a real disruption in the drug business, as I put it, where genetics, I think, can play center stage in really improving the efficiency and allowing us to make investment decisions and development decisions that most effectively bring efficacious therapies to patients. I plan on talking for approximately 25 minutes, and I think we'll start off with a bit of background about human genetics and drug development, best illustrated with a few published examples before focusing a little bit more on the paradigm of interleukin 6 signaling and the human genetic evidence related to that. First off, let me offer a little bit of background about myself. So I'm a hospital physician by background, specializing in clinical pharmacology and general internal medicine. I'm also an academic with my research focusing on how best to leverage human genetic data to inform drug discovery and drug development. And in this work, I spent 3.5 years at Novo Nordisk, where I initially was involved in setting up the genetics department before later transitioning to explore how we can leverage human genetic evidence more widely across the portfolio. Since then, I moved into consultancy, where as you correctly described, I have set up Sequoia Genetics, which is a consultancy that works with pharma, investors and biotech on most effectively leveraging genetic insights to efficiently develop drugs. So if we take a step back and we look at the drug development paradigm, I think it's fair to say that it is a relatively inefficient process. On average, the FDA might approve between 30 and 50 drugs every year. And for the drugs that are developed, it takes, on average, more than 10 years and cost more than $1 billion to develop that drug. Why do we see such high failure rates of more than 90% sometimes for drugs entering clinical phase study? Well, a lot of that relates to the types of evidence we're using to inform our decisions. Historically, a lot of these insights have come from animal studies, which may not necessarily translate to humans that are the target organism we're interested in here. And further, insight coming from epidemiological associations may not necessarily infer causality, whether a risk factor relates to an outcome may also be because of factors such as confounding or reverse causation. Human genetics offers a number of advantages to help overcome these limitations. Firstly, the data relate to humans, the target organism we're interested in. And secondly, because genetic variation is randomly allocated at conception, whether you receive one variant or another is a random process. This means that the allocation of genetic variants is not sensitive to confounding factors in the same way that epidemiological associations are, and this, therefore, allows us to draw causal inference based on the genetic data. What's very exciting is in the last 5 to 10 years, we've seen a massive explosion in the availability of large-scale human genetic data to the extent that we now have both the breadth and depth of data that allows us to leverage this information to draw meaningful insights that can help inform and prioritize drug discovery and development efforts. Part of this is related to the improved efficiency of sequencing the human genome. Back in 2003, when the first human genome project was undertaken, it costs something like $3 billion human to undertake that exercise with roughly 1 gigabyte of data generated. If we now compare that to modern technologies, we can sequence a human genome in approximately $100, and we have now unimaginable scales of data available to form these types of analyses. This really does come together to offer us the types of insights on relevant disease outcomes, biomarkers, clinical endophenotypes and molecular traits that we can leverage to inform on the necessary aspects of drug development to generate meaningful insight. It's really become apparent in the last few years how powerful this can be when exercised the right way. So what are the basic principles related to this paradigm? One of the major advantages of randomized clinical trials is that they randomize allocation to treatment. And this way, because of the randomization, whether an individual received the treatment or not is not a function of potential confounding factors, and this allows us to draw causal inference. By this same analogy, using genetic data, whether an individual receives one variation or another is also a random process that is not subject to environmental confounding. Where that genetic variation mimics the effect of a drug target perturbation, we can use it as a proxy or a mimic for that pharmacological effect that we might be trying to introduce using drug therapy. And so we can leverage this genetic variant as an instrument for studying the effects of perturbing that target pharmacologically. And similarly to in a trial, because it's randomly allocated, we can infer causal effects of perturbing that drug target. And actually, now that we have this vast array of genetic association data, we can leverage such genetic instruments for drug target perturbation to inform on various aspects of clinical development. And these include insights such as potential adverse effects that might help inform Phase I study, potential biomarkers of target engagement and mediating mechanisms, efficacy that might inform primary outcomes as well as secondary indications and finally, repurposing opportunities. So even if a drug is efficacious for its primary indication, what other opportunities are there for using that drug to maximize its impact for health care. All of this, I think, should still be taken into the wider context. So while genetic data can be incredibly powerful for informing on drug discovery and development, it shouldn't be used in isolation. Clinical trials will always be essential for assessing safety, pharmacological properties, dose finding, efficacy. And indeed, they remain the gold standard for informing clinical practice and approval of drugs. However, human genetics do offer considerable advantages and can be triangulated with the existing plethora of animal studies and cohort studies they use to inform and prioritize drug development efforts. And so in this way, I think it is becoming more and more common practice that where human genetic insights are available and can be meaningfully integrated, they should be used in this way and combined with the existing prioritization of evidence that is put together in informing drug development decisions. And as I say, human genetics can be very powerful for answering the plethora of questions that are integral to most effectively developing drugs. Whether a genetic variant mimicking the drug target relates to a specific outcome can inform on the efficacy of that target for the outcome. And this also allows us to draw comparisons on mechanisms. We can also use it for identifying biomarkers as well as mediating mechanisms and then heterogeneity across population subgroups. For example, how do the genetic variants mimicking a drug target perturbation? How do their associations vary across population subgroups? Is there evidence of dose response relationships? Can we use this to prioritize which tissues are most relevant? For example, is it genetic variants predicting expression of that gene in certain tissues that most strongly relate to the outcomes that we're interested in? And further, how does this relate with other risk factors or other interventions? Are there interactions at play? Are these additive? Are these multiplicative? And what does this tell us about potential combination therapy? So really, the methods and data sources now have become so advanced and powerful that when used correctly, they can be incredibly informative for improving the efficiency and potential success of drug development efforts. And actually, I can't emphasize this point enough. While the data themselves now are vast and abundant as well as the methods sophisticated, success with this paradigm of using genetics to develop drugs effectively falls on triangulating across those relevant specialties. So while the genetic data and statistical methods are there, we really do have to make sure that we're using those to answer the right questions, we're integrating the relevant biology, and we're interpreting the findings from those statistical models in a way that they can meaningfully impact and translate to successful drug development. And that actually is very much a multidisciplinary approach. So we would work with statisticians geneticists, epidemiologists, data scientists, biologists, drug development experts. And all of that expertise must come together seamlessly to most effectively ask the relevant questions, design the appropriate analysis and interpret the results in a way that meaningfully and tangibly has impact positively to improve the drug development paradigm. I'm now going to spend a bit of time talking through some examples that have illustrated some of these principles. A lot of these are translationally relevant, so I think they'll be easier to relate to as tangible examples of the paradigm. The first example I'd like to focus on a little bit is Factor XI. So Factor XI is a circulating protein. It is a coagulation factor, and it corresponds to a particular gene, the Factor XI gene. There are genetic variants at this gene that relate to higher or lower levels of circulating Factor XI protein levels. In the study on the left, we use this genetic variation to show that variants at the Factor XI gene that relate to higher circulating Factor XI levels. So therefore, they serve as an instrument for higher Factor XI levels. They do relate to higher risk of ischemic stroke, but didn't have any strong or significant association with either myocardial infarction or risk of intracerebral hemorrhage. Put another way, this genetic evidence supports that increasing Factor XI levels will increase risk of ischemic stroke and therefore, support that actually reducing or inhibiting Factor XI would serve as a potential therapeutic opportunity for reducing risk of ischemic stroke. These findings were taken further by a separate group, some of them were based at the pharmaceutical company, Bayer, and they used such genetic variation and explored its association with different diseases. So this time, they orientated the genetic variation to mimic the effects of lowering Factor XI. And they found that individuals that had variation mimicking lower Factor XI levels had lower risk of venous thromboembolism and lower risk of ischemic stroke. When considering ischemic stroke subtypes, it became apparent that this risk was most predominantly driven by lower risk of cardioembolic stroke. They also looked at other outcomes, including myocardial infarction and major bleeding and showed that genetically predicted alterations in Factor XI levels weren't strongly associated with risk of either of these outcomes. So taken together, the genetic evidence does support Factor XI as a potential therapeutic target for thrombotic cardiovascular disease, including ischemic stroke, particularly cardioembolic stroke and also potentially venous thromboembolism. Now at this point, actually, I'd like to just highlight a nuance. Just because the genetic evidence supports the target is likely to be efficacious, that doesn't mean that a drug targeting that protein will be effective in clinical practice. There are still other considerations that are important above and beyond the potential efficacy of the target. And some of those might, for example, relate to the pharmacological properties of the specific drug. What is its half-life, what is its affinity, what is its distribution, a lot of the principles relating to its pharmacology. Secondly, what is the design of the trial? What is the duration of the trial, what is the selection criteria for the patients, what is the specific outcome we're looking at? What is the duration of the follow-up? At what time point in disease or risk are we intervening and for what duration are we continuing the intervention and at what dose? So a lot of these factors, genetics may not necessarily directly inform. What the genetics might tell us is whether a target is likely to be efficacious and in which direction it's likely to be exerting its effects. There are still a lot of other factors that are required -- that require consideration before we can maximize our chances of a successful clinical trial. So again, genetics is one element, potentially very powerful, but it shouldn't be considered in isolation as being definitive. The second example I'd like to talk about is recently become an incredibly popular one, and that is of GLP-1 analogs. So there is the GLP1R gene. This is the receptor that is targeted by GLP-1 analogs. And if you look at this gene, what you do observe is that there's genetic associations there supporting that variation at the GLP1R gene is related to lower risk of type 2 diabetes and lower body mass index. Taken together, this would serve as genetic evidence supporting efficacy of GLP1R agonism for reducing diabetes liability, improving glycemic control and lowering body weight. And indeed, this is what we've observed in clinical trials of GLP-1 analogs being used for the treatment of obesity or for improving glycemic control in type 2 diabetes patients. In the study on the right, we leveraged such genetic variation mimicking the effects of GLP1R agonism, and we explored potential efficacy for heart failure. What we found is that leveraging the genetic variation mimicking GLP1R agonism, we found that those variants or individuals that carried such variation had a lower risk of heart failure. Further, we found that this lower risk was greater in magnitude than might be anticipated when considering glycemia variants from throughout the genome. Taken together, this genetic evidence supports that GLP1R agonism is likely to be efficacious for reducing the risk of heart failure. We went further in this study and explored GLP1R variants and their relation to parameters of cardiac MRI function. And specifically here, we looked at left ventricular ejection fraction. And consistent with the association of low risk of heart failure, what we found is that the variants mimicking GLP1R agonism are associated with higher left ventricular ejection fraction, but in contrast, the variants associated with glycemic control more generally did not have a strong association with glycemia. This adds to the previous experimental evidence using the genetic data to support that not only is GLP-1 agonism likely to reduce risk of heart failure, it's likely to improve left ventricular ejection fraction, simply offering further insight that GLP-1 agonism may be efficacious not only for all-cause heart failure, but also with heart failure related to reduced left ventricular ejection fraction. So again, an example of where genetic evidence has been used to inform and prioritize clinical development, in this case, repurposing of existing drugs for novel indications where they may be incredibly efficacious. We can go further as well. So here, I want to give an example considering anti-hypertensive drug classes, specifically ACE inhibition, beta blockade and calcium channel blockade. Taking a similar approach, we can go to the genes coding for the protein drug targets. In this case, ACE, the beta blocker gene and the various subunits of the calcium channel blocker gene and leveraging genetic variants at those genes that relate to changes in blood pressure, we can explore potential effects of perturbing these targets. What we show is that leveraging those genetic variations, we can predict using the genetic approaches that there is a similar reduction in cardiovascular disease outcomes, namely coronary heart disease and stroke as that we observe in clinical trials, meta-analyses of clinical trials using these drug classes. So again, serving as a positive control that the genetic data do support what we know clinically about perturbation of these respective drug class targets. And then we can go further. We can say, okay, look, that's what we already know from clinical trials. We can use that as a positive control. But what can this tell us that is novel. And in this particular case, we leverage these genetic instruments for these respective drug classes using a methodology called phenome-wide association study, where we, in a hypothesis-free setting from an agnostic analysis will say, considering all the outcomes for which we have genetic data in this cohort, do we identify potentially unanticipated novel indications or any potentially unanticipated adverse effects? Again, being a very powerful way to allow the data to tell us where there may be opportunities that have not yet been considered to really maximize the impact of drugs for benefiting patients and society. Continuing with the example of antihypertensive drugs, a particular population for which it is -- sometimes can be more challenging to find effective treatments is pregnant women. So in this population, sometimes because of theoretical risk related to the pregnancy, well, theoretical and practical risk related to the pregnancy, it can be more difficult to undertake trials quite understandably. In this scenario, human genetics, again, can be used to help prioritize and inform decisions before taking on potentially risky trials. In this study, we explored potential interventions for treating and reducing risk of preeclampsia. Again, using a similar approach to that described in the previous study, we leveraged genetic instruments for different anti-hypertensive drug classes and compared those with the genetic variation predicting blood pressure control more generally. What we found is that the genetic variation mimicking the effect of beta blockade was associated with a lower risk of birth weight for the first child, while in contrast, the genetic variants mimicking calcium channel blockade did not have any such association. We also looked at other outcomes, including gestational diabetes and effects on risk of preeclampsia more generally. It was only the beta blocker drug class for which the genetic evidence supported an effect on birth weight in contrast to the calcium channel blockade genetic instruments. So taken together, this data might support that there is a discrepancy in how these different drug classes affect birthweight of the first child in contrast to how they're altering blood pressure and pre-eclampsia risk more generally, again, providing insight to help inform and prioritize how we might pursue further clinical trials to explore what is the most appropriate treatment strategy to use. With this, I want to spend a bit of time now focusing on interleukin-6 signaling, which, of course, is incredibly relevant to today's webinar. We are very fortunate with interleukin-6 and that there is genetic variation at the receptor that seems to robustly mimic the effects of inhibiting signaling. So at the interleukin-6 receptor gene, there are numerous genetic variants that seem to mimic interleukin-6 receptor signaling inhibition, and such variation is also associated with biomarkers of reduced interleukin-6 signaling, namely lower CRP, lower fibrinogen and higher circulating interleukin-6 levels. This offers us a great opportunity because we can then leverage this genetic variation in this Mendelian randomization paradigm and use that to help prioritize potential efficacious outcomes where interleukin-6 inhibition may be effective. And actually, this was first done in a wide angle study of cardiovascular outcomes, where genetic variation related to lower interleukin-6 signaling was associated significantly with lower risk of various atherosclerotic cardiovascular disease outcomes, including myocardial infarction as well as aortic aneurysm, specifically abdominal aortic aneurysm. So this represents from human genetic evidence that interleukin -6 signaling inhibition will be efficacious for reducing risk of atherosclerotic cardiovascular diseases. And actually, the example of interleukin-6 is relevant because it's actually represented a very high quality of genetic evidence that has successfully predicted clinical trial settings with clinical trial results in a number of settings. The first example I want to talk about is that of polymyalgia rheumatica. So again, this is an inflammatory condition, and we can leverage the genetic variation in the interleukin-6 receptor gene to predict what the effects of interleukin-6 signaling inhibition will be in clinical practice for this outcome. In this study, we leveraged this genetic variation, and we showed that individuals that have genetically predicted interleukin-6 inhibition through their genetic predisposition had a lower risk of polymyalgia. What was really exciting about this is that after we published the study, some months later we had clinical trial data supporting that indeed the genetic predictions were true, where tocilizumab was shown to be effective in the treatment of polymyalgia rheumatica. So this is one example where the genetic evidence published prospectively successfully predicted efficacy of an intervention that was later shown in clinical trials to work as the genetic supported. The second example is that in COVID-19. So pandemic situation, real rush to find efficacious therapies to reduce the massive burden of morbidity and mortality associated with COVID-19. There was already some speculation that the exacerbated or increased inflammatory drive in COVID was driving a lot of that pathology. And so it made sense to explore potential interventions or therapies that might mitigate some of this inflammation. At the time, we took the same approach, and we leveraged a genetic variation mimicking inhibition of interleukin-6 signaling. And we found that individuals that have such genetically predicted interleukin-6 signaling inhibition had lower risk of COVID-19, lower risk of hospitalization when contracting COVID-19 and lower risk of severe COVID-19 that required ICU or intubation. So we published this, and we said, look, there is genetic evidence to support that inhibition of interleukin-6 is likely to be efficacious in reducing the progression or severity of COVID-19. And indeed, some months after that, there was the landmark release of the Recovery trial data that supported in clinical trial setting that interleukin-6 inhibition is efficacious for reducing risk of severe COVID and the morbidity and mortality related to that. So 2 clear examples where genetic evidence, specifically related to inhibition of interleukin-6 signaling have prospectively predicted clinical trials for those same outcomes with the same intervention, again, demonstrating the power of genetics for informing and prioritizing drug development methods. We can go further. And as we previously described the Phenome-wide Association study approach, we can do something similar with the interleukin-6 signaling inhibition instrument. And that's exactly what was done in this study. So we leveraged the genetic variation, mimicking interleukin-6 signaling inhibition. And we said, look, in a hypothesis-free setting, phenom-wide, can we explore what novel indications or potential adverse effects might be of this modality. And what we found in the hypothesis-free analysis is that individuals that had genetically predicted inhibition of interleukin-6 signaling had lower risk of atherosclerotic cardiovascular disease, including angina, myocardial infarction and other atherosclerotic cardiovascular disease subtypes. So even in a hypothesis-free study, where we say, look, without any preconceptions about where it may be efficacious, what are the outcomes that are prioritized, atherosclerotic cardiovascular disease really did come up as one of the significant associations relating to lower risk. In the same study, we were also able to explore potential adverse effects. So does genetically predicted interleukin-6 signaling inhibition associate with higher risk of any unwanted outcomes? And what we found was that there was an association with certain types of infection and certain types of allergic and inflammatory disease. So what we found was an association with higher risk of cellulitis and urinary tract infection and also an increased risk of eczema or atopic dermatitis. Again, offering us insight before even undertaking any clinical study of what we might be mindful of when pursuing interleukin-6 inhibition, both in terms of efficacy but also potential adverse effects that we should be cognizant of. And similarly, just like we can undertake a phenome-wide association study, we can also do this with biomarkers, whether those be circulating metabolites or proteins. And this can be particularly effective for prioritizing a biomarker strategy, particularly in early phase trials such as Phase I or Phase II. So in the study, we leveraged genetic variation mimicking interleukin-6 inhibition, and we said, considering the available biomarkers, what is prioritized? And what we found was that by far, the strongest association was with lower CRP. So genetically predicted interleukin-6 inhibition signaling really does associate with lower CRP, making this perhaps a preferred and easily clinically accessible biomarker by which to measure the target engagement of interleukin-6 inhibition therapies. And the last study I want to talk about on interleukin-6 and as part of this talk is one where we can start to use genetics to explore potential heterogeneity across population subgroups. So assuming that we have a target in mind that we believe is very likely to be efficacious, what is the population of individuals most likely to gain greatest benefit, right? And can we use genetics to help inform on that? So here, we went to the U.K. biobank population and we took genetic variants mimicking interleukin-6 inhibition. And we said across individuals in the U.K. biobank, is there a particular population subgroup where we see greatest benefit or greatest association of interleukin-6 signaling inhibition variants with lower risk of cardiovascular disease? Is there a population that we should be prioritizing in other words? What we found is that actually across traditional risk factors like age, kidney function, BMI as a measure of obesity, cholesterol levels and blood pressure, there wasn't any consistent heterogeneity, right? So perhaps with the exception of perhaps very high LDL cholesterol, there was generally a very homogeneous association of the interleukin-6 signaling inhibition variation and cardiovascular risk. The one exception was with CRP. Where we actually found evidence that the higher the absolute CRP levels, so in other words, that might be interpreted as the highest residual inflammation, the greatest the absolute cardiovascular disease risk reduction. So this would help a translational perspective, this might offer insight to suggest that actually, if we really want to see the greatest benefit of interleukin-6 signaling inhibition, we might want to prioritize individuals that have that greatest residual inflammation. In other words, those that have the highest baseline levels of high-sensitivity CRP. So with that, whistle-stop tour through how genetics is really changing the paradigm of drug development, how it's positively disrupting the ecosystem of drug development, how it can be incredibly powerful but it really does need to be integrated in the right way. We've got to ask the relevant questions, and that's got to take in the background biology. We've got to integrate it with the robust and appropriate data sources and statistical methods. And then we have to translate that into a meaningful insight, appreciating the power of genetics and everything that it can offer, but also its limitations, the modeling assumptions it makes and the various other forms of evidence that we should be looking to triangulate across to really maximize the converts success going forward. And of course, related to that, the plethora of very robust data related to interleukin-6 inhibition and cardiovascular outcomes. So with that, I thank you all for your time today. It's been a pleasure, and I'd like to hand over to Dr. Emil DeGoma, SVP of Medical Research at Tourmaline. Thanks so much.

Thank you, Dr. Gill, for providing a primer on how human genetic studies inform drug development and for reviewing the genetic validation of IL-6 inhibition in cardiovascular disease. As Sandeep mentioned at the beginning of the presentation, there is a convergence of evidence supporting the therapeutic potential of IL-6 inhibition for cardiovascular disease. In addition to human genetic evidence, epidemiological studies and prior clinical trials also provide supportive information. Our team is working to further contribute to the growing literature on IL-6 in cardiovascular disease with several manuscripts underway. Turning to epidemiological evidence. I'll touch on recent data regarding hs-CRP. To review, C-reactive protein is a protein produced primarily by the liver in response to inflammation. It is biologically linked to IL-6 and a key downstream biomarker of IL-6 pathway activity. Prior clinical trials of IL-6 inhibitors have shown impressive reductions in levels of CRP, and this includes pacibekitug, which has shown deep reductions in CRP in its 6 previously completed studies with low-volume, infrequent subcutaneous administration. High-sensitivity C-reactive protein is a widely available, standardized and inexpensive blood test that can accurately quantify levels of CRP to identify patients with systemic inflammatory cardiovascular risk. Multiple studies across different populations and cardiovascular outcomes have shown that hs-CRP is a powerful predictor of risk. I'll highlight here one recently presented landmark study, an analysis of the women's health study. Dr. Paul Ridker presented these data at the European Society of Cardiology Congress in London, and results were simultaneously published in the New England Journal of Medicine. Since 1993, the women's health study has followed a large cohort of initially healthy women. In almost 28,000 women, hs-CRP, LDL-cholesterol and lipoprotein(a) were assessed at baseline. And over the span of 30 years, some of these women had a heart attack, stroke or coronary revascularization procedure or died from cardiovascular disease. Dr. Ridker and team's analysis showed that hs-CRP, LDL cholesterol and lipoprotein(a) were each significantly associated with Major Adverse Cardiovascular Events or MACE. Notably, hs-CRP outperformed both LDL cholesterol and lipoprotein(a) in terms of risk prediction. Women in the highest quintile of hs-CRP had a 70% increased risk of MACE compared to those in the lowest quintile. Elevated hs-CRP levels have been associated with a greater risk of ASCVD, as I noted in the women's health study summarized in the previous slide. Elevated hs-CRP levels have also been associated with a higher risk of heart failure events and other adverse cardiovascular outcomes. Dr. Gill noted human genetic evidence implicating IL-6 in coronary artery disease, peripheral artery disease, atherosclerotic ischemic stroke and abdominal aortic aneurysm. In other words, available evidence supports the therapeutic potential of IL-6 inhibition across a range of high-risk cardiovascular patient populations. The prevalence of inflammatory risk identified by elevated hs-CRP is high, as indicated by the shaded bars, encompassing millions of patients in the U.S. alone. We're excited to investigate the potential for pacibekitug in ASCVD, and our Phase II TRANQUILITY study is underway. The Phase II study is a randomized, double-blind, placebo-controlled trial evaluating quarterly and monthly subcutaneous dosing arms of pacibekitug in approximately 120 patients with elevated hs-CRP and moderate to severe chronic kidney disease at baseline. The primary pharmacodynamic endpoint of TRANQUILITY is hs-CRP at day 90, and we will also be assessing other pharmacodynamic biomarkers of IL-6 pathway activity, such as fibrinogen and lipoprotein (a) and safety in PK and antidrug antibodies. There are 3 main goals from this trial: number one, to evaluate quarterly subcutaneous dosing of pacibekitug, which is supported by our PK/PD modeling based on prior clinical trial data; number two, to select a dose to take forward into future trials; and number three, to support Phase III readiness in 2025, enabling us to initiate a range of cardiovascular outcome trials if the Phase II results are positive. We remain on track to share top line data from TRANQUILITY in the first half of 2025. And with that, we'd like to open the floor to your questions. Operator?

[Operator Instructions] Our first questions come from the line of Yasmeen Rahimi with Piper Sandler.

It would be wonderful if you could put into perspective. I guess first question is, how does IL-6 specifically drive MACE reductions during events versus other mechanisms? I think we're learning more and more day by day how inflammation is linked to a MACE benefit and event benefit in cardiovascular patients. But could you compare the mechanism of IL-6 versus other approaches and how that stacks up being at the top of the funnel as a key approach? Maybe that's question number one.

Yasmeen, thanks for the question. Emil, do you want to take that one?

Sure. And thanks for the question. So I think there are maybe 2 major questions in there. The first is hypothesized mechanisms of the potential atheroprotective effect of IL-6 inhibition. In there, what we can turn to is there are a number of potential mechanisms based on experimental studies, which have highlighted the role of IL-6. In particular, IL-6 appears to drive inflammation locally in the blood vessel wall to promote the different stages of atherosclerosis, including the de novo development of plaque, the progression of plaque and then finally, the plaque rupture, which causes the catastrophic event of a heart attack. So IL-6 has been implicated in those different steps -- in addition, IL-6 acts on the liver and there may promote a more atherothrombotic state, so promoting blood clot forming factors as well as increasing levels of the atherogenic lipoprotein, lipoprotein(a). So there are a number of potential atheroprotective mechanisms that have been highlighted really over the past 2 decades, but more evidence coming to light over the past few years. I'll touch on the second part of the question, which is really thinking about this pathway relative to other pathways and how it might fit in the treatment paradigm. Here, I think we're excited about the convergence of evidence that Sandeep had mentioned. So epidemiologic evidence, inferences from clinical trials and human genetic data. And so perhaps I'll touch on each of these and maybe and Dipender can comment as well. But so as far as the epidemiological evidence, as far as I shared the women's health study, what we're excited about is the predictive power of CRP appeared to even outperform LDL cholesterol as well as lipoprotein(a). And Dr. Ridker has shown that in secondary prevention settings as well in 3 large studies published over the past 2 years. And then from a clinical trial standpoint, the inferences from CANTOS are important as well in that trial in patients with a history of myocardial infarction with the anti-IL-1 beta inhibitor, canakinumab, patients who achieved robust lowering of IL-6 levels had a 35% reduction in the risk of MACE as well as significant reductions in cardiovascular death. And importantly, in that study, patients were already quite well controlled. baseline LDL cholesterol in that study was around 80. And canakinumab appeared to achieve the results without affecting these other risk factors like LDL cholesterol or blood pressure. So the magnitude of the reduction observed in the clinical trial as well as the epidemiological evidence really does suggest a potential of large magnitude reductions with IL-6 inhibition as far as the risk of atherosclerotic cardiovascular events. And with that, maybe I'll turn it to Dr. Gill.

Thanks so much, Dr. DeGoma. I think there's a couple of aspects that genetics can add to with providing insight on the mechanism. The first is that if we study the genetic variation mimicking interleukin-6 inhibition, it relates to various subtypes of atherosclerotic cardiovascular disease. So as Dr. DeGoma says, it relates to atherosclerotic coronary artery disease, peripheral artery disease, large artery stroke, carotid plaque. So that combination really does suggest there is something specifically going on with interleukin-6 and atherosclerosis there. That I think the evidence points to that being a factor driving the inflammation that we see in the plaque wall and its progression. And I think that is likely what the genetics is pointing to as the mechanism really driving it there. But the real thing to highlight is that consistency over -- across different atherosclerotic mechanisms with interleukin 6 really being implicated not only epidemiologically, but using the genetics as a causal driver of that pathology, I think, supports inflammation and its role in atherosclerotic cardiovascular disease.

Maybe one last question. Could you maybe talk -- could we talk about a little bit the common practice among cardiologists for measuring CRP levels and seeing it as a risk marker or other inflammatory measures that are in common practice. I think we all know we get our lipid measures frequently, but I just kind of thinking about the inflammatory panel, how much of that is already implemented in the real world right now? And I'll jump back into the queue.

Great. Emil, do you want to take that?

Yes. Yes. No, happy to comment. So I would say that hs-CRP right now, as far as its real-world clinical use, uptake has been relatively limited, but we do seem to be reaching an inflection point based on an accumulation of data and the widespread availability of hs-CRP testing. So real world as of now is rather limited, but we can see that based on the accumulation of data as well as incorporation into additional guidelines as has happened in the European Society of Cardiology, incorporating into guidelines for patients with suspected coronary disease that we would anticipate increased use of this marker to review, it is a standardized test, widely available at commercial labs and inexpensive. And so we anticipate that as cardiologists continue to attempt to treat in a precision way and patients with high risk remain at high risk for atherosclerotic cardiovascular events, that this test will be incorporated into practice similar to checking LDL cholesterol, as you mentioned, or blood pressure. So really a biomarker guided approach to assessing risk and then determining future therapies.

Our next questions come from the line of Roger Song with Jefferies.

Great. And then a couple of questions from us. The first one is very gratifying to see the translation from the genetic to clinical evidence for polymyalgia rheumatica. So just curious, how are you going to draw the comparison between the PMR versus the ASCVD? Any similarity, dissimilarity between those 2 disease? And how should we feel about the translation to the ASCVD from the PMR?

I think the first point to make is that IL-6 is unlikely to be involved in only one pathological process in the body. It's a highly pleiotropic cytokine. It has a number of pivotal effects. We've seen from the genetics that it's potentially implicated in a number of diseases. It's approved. So interleukin-6 inhibition is approved for treatment of various diseases, including polymyalgia, rheumatoid arthritis and other inflammatory disease subtypes. What the genetic supports is that its inhibition is likely to be efficacious for atherosclerotic cardiovascular disease for reducing severity of severe COVID-19 outcomes and for polymyalgia as well as the positive control outcomes for which it's already approved. That doesn't mean to say that the mechanism by which it's exerting these effects across these heterogeneous diseases has to be exactly the same. So what interleukin-6 is doing in atherosclerosis doesn't have to relate directly in terms of mechanism to what it might be doing in rheumatoid arthritis or polymyalgia. I think the commonality there is that the IL-6-related inflammation is a common causal risk factor for these various outcomes. The specific mechanism by which that is leading to pathology, I think, varies across these diseases. So the genetic evidence isn't telling us that polymyalgia itself is a pathological process in atherosclerosis. What it's saying is that IL-6 is a common causal risk factor for both of these potentially related to its pleiotropic effects across biology.

Our next questions come from the line of Thomas Smith with Leerink Partners.

Maybe just a couple for Dr. Gill and for Tourmaline. I guess maybe building on some of the earlier questions. Can you just talk about how much evidence there is for hs-CRP reductions? And I guess, like what levels of CRP reductions you think could confer some level of cardioprotective benefit? And then I guess, any other -- we're obviously going to get the important Novo outcomes data potentially next year. But I guess any other data sets being generated that should be on our radar as we look to track inflammation as this important marker of cardiovascular risk?

Thanks, for the question. Dr. Gill, do you want to start and maybe Emil can chime in afterwards.

It's a great question. I think it's really important to really clarify this point. What the genetics tells us is that variation in interleukin-6 receptor, which we can proxy as a mimic for inhibiting interleukin-6 signaling relates to lower risk of atherosclerotic cardiovascular disease. What the genetics also tells us is that, that same signaling mechanism is a driver for CRP. That doesn't mean to say that CRP is on the common causal pathway. It means that both CRP and atherosclerotic cardiovascular disease have a common mechanism in interleukin-6. Interleukin-6 signaling drives CRP and it also drives atherosclerosis. That's what the genetics is telling us. Now translating the genetics to the clinical magnitude of risk reduction, whether that's measured through CRP reduction or clinical outcomes, that's a different question. And it's something that I tried to allude to in my talk where the genetics can tell us, is a target efficacious and in which direction? But that doesn't necessarily tell us the magnitude of effect, right? For the magnitude of effect, we need other information like what are the pharmacological properties of the asset we're pursuing? What is the patient characteristics that we're using the intervention in? What is the duration of follow-up? What is the outcome? What is the intensity of treatment? So I would really urge caution from anyone trying to use the genetics to predict magnitude of effect. I don't think the genetics can reliably inform on that. The genetics can tell us is the target efficacious and in which direction are there. What are the biomarkers? What are the adverse effects? Where do we see greatest benefit. But in terms of magnitude of effect, I think we really need to think about optimizing the trial design to get an insight of that. And for that, I suggest we got a clinical data and clinical trial data rather than using the genetics to predict magnitude of effect.

Thanks, Dr. Gill. And I'll just add here, just to comment on the approach and the use of hs-CRP and potential sort of targets for threshold level or threshold levels of hs-CRP. I think a different -- across the different lines of clinical evidence, it does look like lower is better when it comes to hs-CRP. And that said, it's likely that an initial target might be 2 milligrams per liter, which has been studied across different populations and clinical trials to identify patients at residual inflammatory risk. But the evidence that lower is better is quite sort of similar to LDL cholesterol in that if you look across the epidemiological studies, the human genetic evidence as well as clinical trials, it does seem like achieving a lower CRP is associated with improved outcomes. Now that threshold of 2 milligrams per liter has been established now as far as clinical guidelines, and that's based on a wealth of evidence across clinical trials and epidemiological evidence. But it could very well be that lower is better, but an initial target might be 2 milligrams per liter, again, just based on studies that have been done to date. I'll just highlight here, the initial LDL-cholesterol goal was 130 milligrams per liter many years ago. And subsequently, as more trials emerged, the goals were lowered subsequently. But as an initial threshold, 2 milligrams per liter will likely emerge as a target, and that's how some of these trial data have been presented to date.

Our next questions come from the line of Yatin Suneja with Guggenheim.

This is Eddie on for Yatin. Can you use any of this genetic variability to exclude patients from any of the outcome subgroups? And what characteristics of patients with inflammation might not be candidates for IL-6 inhibition? And then can you speak a bit more on how targeting the ligand versus the receptor may impact the clinical trial success and what differences there might be in the pharmacology between pacibekitug and the [ NovoLase ] that's currently in several large Phase III CD outcome trials?

Yes, it's a great question. And actually, I think the genetics can be particularly powerful in this regard. So we have this genetic variant, this genetic instrument for interleukin 6 signaling. And we can leverage that across different cardiovascular outcomes, some of which may superficially seem to be related, but actually in practice in terms of pathophysiology or mechanism could be quite distinct. So for example, we could undertake work and we have undertaken work where we say, how does the genetic instrument for interleukin 6 signaling relate to different subtypes of cardiovascular disease; heart failure, peripheral arterial disease, abdominal-aortic aneurysm versus thoracic aneurysm, intracranial aneurysm, et cetera, et cetera. And actually, that can really help us prioritize what should be included in a composite outcome. So if we're saying interleukin-6 is important, what are the outcomes we really should be aggregating for that. And actually, the genetics is an ideal tool for that, right? So where is the genetic evidence that supports that the target is going to be efficacious, that is what we should be including. I think it's safe to say the genetic evidence is incredibly strong for atherosclerotic cardiovascular disease. I think it's pretty clear from the published literature, it's also incredibly strong for abdominal-aortic aneurysm. So I think that relates to a lot of it. The second part of your question, I think, is incredibly important, right? So how does targeting the receptor compared to the ligand? And in this part, I think we've got to have some humility to what nature has offered us. So nature has given us genetic variation at the interleukin-6 receptor. So the insights we draw so far relate to signaling related to that receptor. There has been some work trying to look at whether there is genetic variation at the interleukin-6 ligand, so the gene coding for interleukin 6 itself. There isn't anything convincing there. So about 1/3 of genes don't have genetic variation that allow us to study the effects of their pharmacological perturbation. And I think interleukin-6 falls into that category. So it's not that we can say interleukin-6 won't work or will work. What we can say is we don't know because we don't have genetic variation related to interleukin-6 as a ligand in the same way that we do for the receptor. I think that's the important distinction. So there's an absence of genetic evidence for interleukin-6 as a ligand. There is strong genetic evidence for interleukin-6 receptor, and that's what we're basing our conclusions on. I hope that answers the question.

Appreciate it. Great. And then maybe I'll touch on the question regarding differentiation relative to the NOVO. I mean, first of all, I say that we think this is an exciting area. There's a lot of potential here to go after risk factor that just has not been well addressed to date, but there's increasing recognition of the importance of it. Now in terms of how we compare the NOVO program, we think there's 3 ways we see to differentiate. First of all, there are properties inherent to our antibody that we think make it attractive. In as far as, we have a long half-life that's already been demonstrated to have a long dosing interval, which we can push out even further. Now in a setting like CV, where we're talking about prevention of disease, adherence can be a challenge and a drug that can be given with less patient administration burden, we think has very obvious and clear advantages as we've seen with other drug classes within CV that less frequent appears to be more preferred. Second, we think there's ways we can differentiate on trial designs relative to what NOVO has done for their studies in an area like CV in many ways, being second is better. There are learnings that may come out of the NOVO program that we can use and come up with more informed trial designs as we've already been working through with our SAB. And then finally, I'll mention that there's just a lot of white space here. I think Dr. Gill nicely framed just how many different indications there are within CV where IL-6 has found -- has very clear genetic validation, which offers us a number of white spaces, new indications, new areas to think about that we're really excited to pursue.

Our next questions come from the line of Josh Schimmer with Cantor Fitzgerald.

First, a couple for Dr. Gill. You highlighted some evidence suggesting that the role, I guess, of the IL-6 polymorphism was most manifest in patients with higher CRP. Just want to understand that a little bit better because I would have thought that polymorphisms that cause IL-6 levels to be low patients just kind of consistently have low CRP levels. Why do you think you were finding high CRP in them, if I understood correctly?

Josh, thanks for the question. And a big fan of your podcast biotech hangout. So to hear your question. So the actual analysis you described, we stratified the U.K. biobank population based on their CRP levels. And we found that in those that have the highest baseline CRP levels, and this was excluding people with extreme CRP, whether there's an acute infection or acute inflammation. So across the distribution of CRP, we're representing residual inflammation. Those that had the highest baseline levels of CRP, we showed that the genetic variation mimicking interleukin-6 receptor signaling inhibition have the highest association with CVD risk. At an absolute level, that meant in those individuals, we saw the greatest absolute risk reduction. When you put it on a relative scale, so you scale by CBD risk reduction divided by CRP reduction, you found that actually it was pretty similar relative risk reduction across the population. How we interpret that is that those that have the highest levels of CRP will see the lowest CRP reduction with inhibition and therefore, the lowest CBD risk reduction as well. If you put that on a relative scale for the CBD risk reduction relative to the CRP reduction, it's pretty uniform.

Is the point for those patients that they might have had the IL-6 polymorphisms that lowered IL-6 levels, but not substantial enough to drive very low CRPs?

I understand. So another really important point to clarify is the genetic variation for interleukin-6 signaling is tiny. So this is explaining less than a few percent of the variation in interleukin-6 signaling. It's not enough to cause massive disruptions in CRP across the population strata. And in any case, we corrected that. So before stratifying the population, we corrected for genetic predisposition. So this is CRP corrected for genetic predisposition and then the stratification was done on that. So it's not that the genotype is influencing the CRP that we're stratifying on. It was genotype independent CRP stratification.

Got it. And you cited a number of settings where the genetics really correlated with the target. How often do the genetics get it right? Do you find many circumstances where the genetics point you to a conclusion that actually hasn't been replicated in, I guess, in the clinic or real world?

This is a really important point to clarify. So the human genetics when performed robustly and you've got to integrate the methodology, the data, you've got to do everything very rigorously. And I've got to say, and even a lot of the published literature, it isn't done rigorously, and there are a lot of modeling assumptions that can be overlooked or misleading. But when done rigorously, you have really robust genetic evidence that a particular target is having a causal effect, usually, that's pretty substantial, and it's pretty robust. Where that doesn't translate clinically is in the detail of the actual -- the clinical translation. So that relates to what is the drug doing? Is the drug hitting the target? Is it hitting other things? Is it mimicking? Is it hitting the target in the same way that the genetic variants mimic perturbation? Have we got the right population subgroup? Have we got a sufficient duration of follow-up? Do we have the intensity of therapy? Have we got the right outcomes? Have we phenotyped them appropriately? Is there heterogeneity we're missing out on? A classic example is CTP, right? CTP, really strong genetic evidence, like the genetic evidence is incredibly strong, like it is for PCSK9, like it is for HMGCL, like it is for interleukin-6 receptor. A number of those trials didn't reach their primary endpoint. That may not necessarily be because the target isn't good. The target can be good, and there still could be other reasons the trial doesn't work. And that could include all the things we spoke about, the pharmacology of the asset, whether it's really having the affinity we want, the patient population selection, all of those things. What I can say to interleukin-6 receptor that genetics is incredibly supportive for atherosclerotic disease risk reduction. Whether the trial is successful or not is going to depend on other things outside of whether the target is good. Similarly, you can have some targets for which there is not robust genetic evidence, right? And SGLT2 inhibitors is a classic example, right? Blockbuster drug, multiple indications, incredibly efficacious, in some ways, a real game changer. There is a rare family that have glycosuria and a mutation in that gene, but there is nothing near the sample size for us to undertake the Mendelian randomization analysis to infer causal effects. So I'd say about 1/3 of targets, we simply don't have the genetic variation to study drug target perturbation. I'd say for 2/3, we do. and where the genetics do predict efficacy, and we don't see that clinically and the genetics is robust and appropriately performed, then we've got to start looking at whether we've performed the clinical translation properly. Have we hit the right pharmacology? Have we hit the right population, have we designed the trial right? That's where I see the translation sometimes can go wrong.

Got it. Very interesting. Maybe a question for the Tourmaline team now. I guess it sounds like NOVO is going to have their first proof-of-concept data, Phase III data for the IL-6 mechanism in 2026. You'll be in a position to potentially start a Phase III trial before we get that the data readout from NOVO. So how are you thinking about the timing and staging and whether you would embark on a Phase III program prior to those results or not?

Josh, thanks. I'll take that question and if Emil has anything to add, please do. Right. So our time line is we'll have data from TRANQUILITY first half 2025. Again, that is a CR endpoint, and we will outline our goals for that trial. Our -- one of our objectives is that we'd be Phase III ready coming out of that study in line with other questions, including from NOVO. And so our plan is to -- once we have data, we will go to the agency to talk through our data from Phase II as well as what our plans are for Phase III at that point. Given that this could be a relatively large trial, it will be an outcome study, it's kind of thing where probably would be a few quarters before we start that study after we have data in hand. Now we are planning for success here, given the strength of evidence has been outlined today and including other lines as well. And so we are working through with our SAB a number of Phase III outcomes trial designs that we could pursue. We'll be in a position close to when we have TRANQUILITY data, We will talk through what that study will look like and how we might think about operationalizing it.

Our next questions come from the line of Srikripa Devarakonda with Truist Securities.

I have one question for Dr. Gill, maybe 2. Dr. Gill, when we talk about the human genetic studies as validation, how important do you think it is to have a diverse population from an ethnic diversity perspective where you've seen the causal relationship. I think you briefly mentioned something on the call. Have you seen cases where the ethnic background confounds the causal relationship? And maybe your thoughts on targeting the IL-6 pathway in that context.

Great question. So the first thing I think it's really important to make clear is that genetic diversity is very important for unraveling mechanisms. There are some genetic variants that are present at a far greater frequency in some genetic ancestry population group as compared to others. And actually capturing that diversity is really important for inferring causal effects. We need as much variation as we can get to really understand what different genes are doing, what proteins are doing and how we might harness that information mechanistically or therapeutically. So diversity is important. A second point related to that is, is there evidence that genetic diversity can be translated to means that some targets are more relevant to some population groups than others. And I think, particularly for interleukin-6 receptor, there is no evidence to support that. We have one published study where we looked at interleukin-6 receptor variation, genetic variation in an East Asian population. And we found similar evidence of efficacy for atherosclerotic cardiovascular disease that we do find in European ancestry populations. So at least in the example of interleukin-6 receptor, I don't think there's any genetic evidence to support that there's variation across genetic ancestry subgroups. Now whether that translates to other targets or not is less clear. And I don't think there's actually anybody in the world that really knows the answer to that. Can we use genetic variation or Mendelian randomization heterogeneity across population subgroups to infer varying efficacy of different targets in those different populations. I don't think the answer to that is fully known. And actually, a lot of people have been exploring that not only for heterogeneity across different ancestry groups, but across sexes; so males and females; is there evidence to support some targets will work better in one population group versus another. Based on the genetics, I don't think the answer is fully known. But at least in the example of interleukin-6 receptor, what we do know is that the genetic linked to atherosclerotic cardiovascular disease does seem to be fairly consistent irrespective of which population subgroup you focus the analysis on.

Great. That was really helpful. And if I can ask one more about a different mechanism of action. Recently, the GLP-1s have shown data indicating cardiovascular benefit. In the context of literature suggesting an anti-inflammatory role for GLPs, can you opine on how these 2 might, if at all, interact? Do you think that -- if you think many years into the future, could it be sequence? Could it be a combination? Or is it a completely different population that you would target with GLP and IL-6?

Thanks, for the question. Emil, do you want to take that?

Sure. I'll take that. That's a great question as the therapeutic landscape evolves, how do we envision where an IL-6 inhibitor might make sense. This, of course, has to be borne out in the context of the clinical trial results. But -- so it's reasonable to think that, in particular, in patients who have quite high residual inflammatory risk identified by quite high levels of hs-CRP that a targeted IL-6 inhibitor may make more sense in the context of very high baseline CRP levels. But again, this would need to be borne out in the context of the clinical trials themselves. But the reason I say that is because as far as IL-6 inhibition and CRP reduction, it does appear to date that lower appears to be better. And we have seen in the context of IL-6 inhibition, quite robust reductions and inhibition of that pathway. Again, there haven't been any head-to-head studies, but reductions, for example, in the SELECT trial of semaglutide showed reductions of CRP of around 35% to 40% compared to placebo, reductions of CRP and suppression of the IL-6 pathway has been in excess of 80% as far as CRP reduction. So perhaps that might translate into robust risk reduction. So they might be used in combination in patients with very high CRP or depending on the results, selection of one therapy versus the other based on CRP, for example.

Our next questions come from the line of Yi Chen with H.C. Wainwright.

My first question is, maybe you touched upon it before. Is there any other mechanism of action that can target hs-CRP other than IL-6? And do you believe IL-6 inhibition can have synergy with drugs of other mechanisms of action?

Thanks for the question. Emil, do you want to take this one? And maybe Dr. Gill can weigh in afterwards.

Yes. So as far as lowering CRP, I think here, it could very well be the case that mechanism matters. And so there are other therapies that lower CRP, including statins that lower LDL cholesterol and also lower C-reactive protein. But in the context of even high-intensity statin therapy, residual elevated CRP does exist as has been shown in a number of studies, and these are the individuals in particular that may be -- may benefit from targeted IL-6 inhibition patients who have elevated CRP at baseline. And so in particular, in the setting of IL-6 inhibition, lower CRP does appear to be better. So while there are existing therapies that lower CRP like statin therapy, there aren't targeted therapies. And so that's one of the reasons why there's excitement about targeted anti-inflammatory therapies like IL-6 inhibitors.

Got it. The second question is, what is the best target patient population for IL-6 inhibition? Is it treatment experienced or treatment naive? And I noticed in your enrollment criteria, there's a range of hs-CRP. So the top end is below 15 milligram per liter. So why there is a need to have a top end limit of hs-CRP for this trial?

So there are a few questions there. And so in particular, which patient populations might be most appropriate in the context of a Phase III study to try to enrich for patients who might benefit for IL-6 inhibition. I think that's one of the questions. The second one is around the design of the Phase II. As far as the Phase III and thinking about enrichment criteria and the appropriate patient populations, I think as Dr. Gill mentioned, and there's other evidence to point to it, that high CRP as an entry criteria is likely an important enrichment factor to enrich for patients who are -- have higher risk, but maybe more likely to benefit from IL-6 inhibition as far as patient selection. And there are other patient populations as well who are at high residual risk, whether that's polyvascular disease or multivessel coronary disease and other subgroups that we're continuing to discuss with our newly formed Cardiovascular Scientific Advisory Board. And I'll just comment briefly on the second question, and then I'll turn it over to Dr. Gill to comment a bit more about Phase III and potential enrichment. But from the Phase II study, your question was around the CRP entry criteria. So the rationale for having a ceiling for hs-CRP in the context of the Phase II, was in the context of the Phase II wanted to minimize potential variability of the pharmacodynamic endpoint. So CRP, particularly on the high end at times may be due to acute illnesses. And so in the context of the Phase II biomarker study in order to reliably assess and protect the primary pharmacodynamic endpoint, that was the reason for the decision to include a ceiling CRP in that context. We don't envision that for any future Phase III studies. But for the Phase II study, we thought it was important in order to carefully be able to evaluate these different doses and isolate their effect on CRP levels. With that, I'll turn it to Dr. Gill to comment a bit more on enrichment strategies potentially for Phase III and populations that might be more likely to benefit.

Thanks so much, Dr. DeGoma. The first thing I want to do is let's just bring it back to CRP. And I think there's a very important point to distinguish here. The way I understand it and at least what the genetics is informing me of is that CRP is a biomarker, okay? So there's various things that cause CRP. Obesity increases CRP. Interleukin-6 signaling increases CRP. There's evidence that tumor necrosis factor signaling increases CRP. So there's various things that can impact CRP. Some of those might have an effect on atherosclerotic cardiovascular disease, including interleukin 6 signaling, including obesity and some of them might not. So CRP is a biomarker of various things, including interleukin-6 signaling. Not everything that affects CRP will affect atherosclerotic cardiovascular disease risk and not everything that affects atherosclerotic cardiovascular disease risk will affect CRP. So we have to make that distinction. Now the fact is that CRP is clinically readily accessible, easy to measure, right? So it's a very attractive biomarker for interleukin-6 signaling because one of the things that really does perturb CRP is interleukin 6 signaling. And for that reason, we can use it. The fact is that there's lots of things that can also correlate to CRP and that can be through interleukin-6 signaling or higher interleukin-6 levels and other mechanisms as well. I think what the genetics points to, and this was also apparent where we stratified based on CRP levels is that what is likely driving the increased risk of atherosclerotic cardiovascular disease in these populations is residual inflammation driven by IL-6. And those that have highest residual inflammation driven by IL-6 also have higher CRP. So it works to stratify on CRP. But I think really the causal factor that we're targeting for which CRP is a biomarker is residual inflammation driven by IL-6. So for me, at least, the strategy is to prioritize which patient population has highest residual inflammation, how can we best select and stratify that population to give them an intervention that is most likely to work for that risk factor. And I think that's the objective. So CRP works super well for that. But really, what we're trying to get at is which population has highest residual inflammation that is driven by IL-6, and that is the population that I think will benefit most from this intervention.

Thank you, Dr. Gill. My last question is roughly what percentage of cardiovascular patients does that range of hs-CRP represent the range of 2 milligram to 50 milligram per liter.

So I'll take that. So it depends on the patient population, but generally, a number of studies looking at high-risk patients with established atherosclerotic cardiovascular disease have CRP levels of 2 or greater, approximately 55% or more than half of patients. Again, it varies by specific patient population. If you look at patients who are more acutely post event or certainly heart failure or abdominal-aortic aneurysm, sometimes they have higher percentages. But in most studies looking at a secondary prevention population, a bit over half of the patients have CRP levels of 2 milligrams per liter or more.

Thank you. As there are no further questions, I would now like to hand the floor back over to Dr. Kulkarni for any concluding remarks.

Thank you, operator. As we wrap up today, I want to extend a sincere thank you to all of you for attending, leveraging genetic data to guide clinical development, especially in areas like cardiovascular disease that continues to pose significant global health challenges is an immensely important tool. I'd like to once again thank Dr. Gill for sharing his expertise today and all of you for your interest. I hope you found the insights shared here valuable. The emerging data continues to reinforce our confidence in the therapeutic potential of IL-6 inhibition in cardiovascular disease as we look forward to a catalyst-rich 2025. Operator, you may now end the call.

Thank you. This does conclude today's teleconference. We thank you for your participation. You may disconnect your lines at this time. Enjoy the rest of your day.