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spk02: Good morning and welcome to the Wave Live Sciences fourth quarter and full year 2020 financial results conference call. At this time, all participants are in a listen-only mode. As a reminder, this call is being recorded and webcast. I'll now turn the call over to Kate Rauch, Head of Investor Relations at Wave Live Sciences. Please go ahead.
spk03: Thank you, operator. Good morning, and thank you for joining us today to discuss our recent business progress and review wave fourth quarter and full year 2020 operating results. On the call with me today are Dr. Paul Bono, our president and CEO, Dr. Mike Panzera, our chief medical officer, head of therapeutics discovery and development, and Kyle Moran, our CFO. Dr. Ken Rhodes, our senior vice president, therapeutics discovery, and Dr. Chandra Varghese, our chief technology officer, We'll also be available for questions following the prepared remarks portion of the call. This morning, we issued a news release detailing our fourth quarter and full year results. Please note that this news release and the slide presentation that accompanies this webcast are available in the investor section of our website, www.wavelifesciences.com. Before we begin, I would like to remind you that discussions during this conference call will include forward-looking statements. These statements are subject to a number of risks and uncertainties that could cause our actual results to differ materially from those described in these forward-looking statements. The factors that could cause actual results to differ are discussed in the press release issued today and in our SEC filings, including our annual report on Form 10-K for the year ended December 31, 2020. We undertake no obligation to update or revise any forward-looking statement for any reason. I'd now like to turn the call over to Paul Bono, President and CEO of Wave Life Sciences. Paul?
spk08: Thanks, Kate. Good morning to everyone on the call, and thank you for joining us. During the call today, I will provide opening remarks, after which Mike Panzera will give an update on our new clinical trials kicking off this year, and Kyle will briefly discuss our financial results. After our prepared remarks, Ken Rhodes and Chandra Varghese will be available for Q&A. 2020 was a productive year for WAVES, resulting from focused and deliberate execution that was driven by our commitment to developing transformative medicines for our patients. As we start 2021, I would like to reflect on the progress we made, which has positioned us to have five programs in the clinic this year. In our neurology pipeline, we progressed our precision HD programs amidst the backdrop of a global pandemic, and we are on track for a data readout at the end of the month. We are delivering on our guidance to advance three new programs into the clinic this year, our SNP3 program in HD, our C9-ORF72 program in ALS and FTD, and our exon 53 program in Duchenne, all of which incorporates our new PN chemistry. We also achieved several milestones for the CNS programs we're advancing with Takeda, including the first demonstration of substantial and widespread target engagement in NHPs. We continue to expand our PRISM platform into new modalities and made significant progress last year on advancing our novel ADAR-mediated RNA editing modality, culminating with the announcement of our first ADAR editing program for Alpha-1 antitrypsin deficiency. Highlighting the progress of both our pipeline and platform, we published five papers within the past 12 months, and we expect to continue to publish more. From a capital position, we raised over $150 million in 2020, ensuring WAVE is well-resourced to advance our pipeline and deliver proof-of-concept results to support growth in 2021 and beyond. Turning to 2021, we anticipate a very busy year of updates on our programs, starting with the upcoming readout of our Precision HD programs in Huntington's disease. These programs consist of core Phase 1b-2a studies and open-label extension studies for both WVE 120-101 and WVE 120-102, targeting SNP 1 and 2, respectively. On slide six, we provide an overview of the data we expect to report from the Precision HD programs at the end of this month. These include biomarker and safety data from all cohorts of precision HD2 core trial, including the 32 milligram cohort, along with all complete cohorts up to and including the 16 milligram cohort from the precision HD1 core trial. We will also share data from the patients who have received multiple doses of 8 or 16 milligrams from the WVE-120-101 or WVE-120-102 in the open-label extension trials. We anticipate sharing data on multiple biomarkers, including mutant Huntington, neurofilament light chain, and wild-type Huntington. This will clearly be a robust data set, which we expect will enable us to make a decision regarding potential Phase III development for either candidate. Before turning to our next pipeline program, I will touch on our novel PN chemistry backbone modification, which augments the first-generation chemistry used in the programs just discussed. As we first highlighted during our research webcast last year, these PN backbone chemistry modifications are an advancement from our PRISM platform and have generally been shown to increase potency, exposure, and durability in preclinical studies across silencing, splicing, and ADAR editing applications. Essentially, our PN chemistry has the potential to lead to compounds with favorable profiles independent of sequence, tissue type, and modality. Importantly, we've already submitted multiple clinical trial applications for candidates using PN Chemistry and anticipate initiating three trials this year. Turning to slide eight, our three upcoming clinical programs targeting SNP3, C9R72, and Exon 53 reflect several advances resulting from the evolution of our platform and our experiences over the past eight years. Enabled by stereo pure design, each candidate has been optimized with PN Chemistry, We've also prioritized the use of in vivo models during preclinical development, and each of these programs has incorporated learnings in translational pharmacology and clinical trial design from our first-generation programs. Mike will speak further to these learnings and provide an update on our planned clinical trials later on this call. Slide 9 provides an overview of our neurology-focused pipeline, which includes silencing, splicing, and editing programs. All of our current discovery and preclinical stage programs utilize this PN backbone chemistry modification. Among our discovery and preclinical CNS programs that we're advancing with our partner Takeda, we continue to produce compelling in vivo data and progress multiple discovery programs towards portfolio entry and candidate nomination. In 2020, we also made significant progress on our ADAR editing modality, which we believe has many advantages in the editing space and positions us at the forefront of RNA editing. Our approach to RNA editing employs short, fully chemically modified oligonucleotides to recruit endogenous RNA editing enzymes called ADAR. Our ADAR editing compounds are optimized using our proprietary stereochemistry and PN backbone chemistry modifications, which enables us to avoid delivery vehicles such as AAV vectors or nanoparticles and allows us to leverage established manufacturing processes. ADAR editing opens the door to a number of therapeutic applications, including restoring or modifying protein function and upregulation of protein expression, which greatly expands the landscape of disease variants that we can potentially address. In 2020, we generated exciting proof-of-concept data in non-human primates that resulted in successful and durable RNA editing of up to 50% in vivo. We are excited about the potential to apply ADAR editing in neurology, and last year we demonstrated successful RNA editing in vitro in neurons and in vivo in the CNS of mice. This year, we anticipate sharing additional non-human primate ADAR editing data, and we are actively evaluating potential neurology programs to address with this modality. Our first ADAR editing program addresses alpha-1 antitrypsin deficiency, or AATD, by correcting a single-point mutation on the mRNA coded by the Z allele of the serpent A1 gene This mutation leads to misfolding and aggregation of alpha-1 antitrypsin protein, or AAT, in hepatocytes and a lack of functional protein in the lungs where it would protect lung tissues from neutrophil elastase. Patients with AATD typically exhibit progressive lung damage, liver damage, or both, leading to frequent hospitalizations of potentially terminal lung or liver disease. Unlike a silencing approach, We believe that our novel ADAR editing modality has the potential to address both the lung and liver manifestations of AETD. By editing at the RNA level, we avoid the risk of off-target genome editing and are able to titrate our dose, thereby avoiding potential challenges with overexpressing an aggregation-prone protein. In the fourth quarter of 2020, we successfully demonstrated editing of the SERPEN A1Z allele transcript to wild-type in vitro in hepatocytes from a transgenic model with upwards of 60% correction of the Z allele transcripts. This level of editing resulted in a threefold increase in AAT protein. Since our last update, we have further validated these secreted proteins to be functional wild-type AAT proteins. These in vitro results are what gives us excitement to generate preclinical in vivo data. We continue to optimize our proprietary in vivo model, which contains both humanized serpent A1 and humanized ADAR, and we are on track to share additional data in the first half of 2021. I'd now like to turn the call over to Mike Panzera for an update on our Huntington's franchise and our three clinical trials planned for this year. Mike?
spk01: Thanks, Paul. We ended 2020 with momentum across development programs as we continued to progress our precision HD trials towards the upcoming data readout. As Paul described earlier, we anticipate sharing a robust data set for our SNP1 and SNP2 programs by the end of the month. Looking to 2021, we successfully submitted clinical trial applications during December to initiate clinical development for WVE003, our third allele-selective candidate in Huntington's disease, and WVE-004, our variant selective silencing candidate in ALS and FTD. In addition, submission of a third CTA for WVE-N531, our candidate for DMD patients with mutations amenable to exon 53 skipping is imminent. All of these compounds incorporate our novel PM backbone chemistry, which has led to favorable profiles in the numerous in vivo studies supporting these programs. We owe the significant progress we've made to our team and our partners in the research and patient communities who continuously adapted to the ongoing challenges presented by the global pandemic to achieve these objectives. I'll discuss each of these programs in more detail today, starting with our Huntington's franchise. We have purposely built a portfolio of allele-selective HD candidates designed to lower mutant Huntington while preserving wild-type Huntington. During the time we have spent developing and advancing these three programs, the evidence supporting the importance of wild-type Huntington has only continued to grow. Wild-type Huntington is essential for proper function of the central nervous system as part of the regeneration transcriptome, especially in the setting of physiological stress, as well as having systemic effects. Wild-type Huntington carries out essential functions in both developing and adult brains. It protects neurons, against various types of stress prevalent in cells with high metabolic activity, including excitotoxic, oxidative, and protein misfolding stress. Wild-type Huntington also plays a key role in trafficking synaptic proteins and synaptic vesicles. This trafficking function has been shown to affect synaptic plasticity, which is important for learning and memory, as well as for supplying the essential growth factor BDNF to striatal neurons to ensure their survival. Additionally, wild-type Huntington is critical for the formation and function of cilia, which control the flow of CSF and help maintain homeostasis in the CNS. We like to use the example of a tug-of-war to illustrate the battle ongoing between the positive biological effects of wild-type Huntington protein and the toxic effects of mutant Huntington in the CNS of those living with HD. Given that HD patients start out with approximately 50% less wild-type protein than a healthy individual, we think this is a reasonable way to illustrate how patients gradually lose ground to disease progression, particularly if there is further depletion of the wild-type protein reservoir. As such, we believe wild-type preservation may be an important driver of efficacy when considering how much mutant Huntington lowering may be required to achieve clinical benefit. Our approach to achieving allele selectivity is to target specific single nucleotide polymorphisms, or SNPs, found on the mutant Huntington allele. Some people with HD can harbor multiple SNPs, in which case a given patient may be eligible for any one of the three SNP targeting treatments. Approximately 50% of the HD population carries SNP1 or SNP2 with an overall estimate of up to 70% carrying SNP1, SNP2, or both when the groups are combined. People with SNP3 represent approximately 40% of the HD population, and it is estimated that up to 80% carry at least one of these three SNPs. Allele selective therapies have the potential to benefit a substantial portion of patients living with HD. Today, we are focused on the symptomatic manifest population, though we believe that with an allele-selective therapy, we may be able to address patients in the pre-manifest setting before the onset of clinical disease. In the US, there are approximately 30,000 people with manifest Huntington's disease and approximately 200,000 people at risk of developing HD based on their family genetics. In order to advance our portfolio of allele-selective candidates, we have needed to innovate on the tools available to accurately and rapidly identify the patients with SNPs that we wanted to target. We achieved this through novel long-read sequencing technologies such that now SNP identification is fairly routine and highly specific. In 2020, these accomplishments were the subject of multiple publications and, in partnership with a surgeon, we are expanding our ability to rapidly identify patients to include in our studies and potentially to support commercialization. Our existing precision HD programs and planned 003 trial will evaluate CSF biomarkers to confirm target engagement, neuroprotection, and wild-type sparing. Building on the existing mutant and total Huntington assays, we have implemented a novel method to assess wild-type Huntington by depleting mutant Huntington from patient CSF samples to allow for direct wild-type measurement. As shown on slide 18, we collect CSF and deplete mutant Huntington using antibody conjugated magnetic beads. This allows us to directly measure the protein that remains, leading to quantitation of wild-type Huntington. As the importance of wild-type Huntington is increasingly acknowledged, we expect this ability to measure wild-type protein to be a meaningful contribution to the HD community and look forward to expanding its use. Now turning to WVE003, our third allele-selective candidate for HD, and our first HD candidate to incorporate PM backbone chemistry modifications. This SNP3 program builds upon the wealth of learnings and experience we have gained from our first-generation HD programs. For instance, 003 is the first of our HD compounds evaluated in an in vivo model system to better understand PK-PD relationships, and these results have informed the starting dose in our clinical trial. We are also leveraging our collaboration with Assuragen and experience at the sites from the Precision HD trials to drive new efficiencies with our clinical trials. The Phase 1b-2a clinical trial is planned to enroll up to 40 patients with a confirmed HD diagnosis who are in the early stages of the disease and carry SNP3 in association with their CAG expansion. The trial will incorporate an adaptive design with both single and multiple ascending dose portions. Throughout the course of the study, an Independent Data Safety Monitoring Board, or DSMB, will guide the level of dose escalation and dosing intervals to make data-driven decisions regarding dose and to potentially accelerate time to proof of concept. Safety and tolerability of 003 will be evaluated along with similar biomarkers as our precision HD program, including mutant Huntington, neurofilament light chain, and wild-type Huntington to assess for allele selectivity. Clinical trial site activation is ongoing, We anticipate dosing a first patient this year. Turning to our C9R72 program for the treatment of myotrophic lateral sclerosis, or ALS, and frontotemporal dementia, or FTD. Our clinical candidate, WVE004, is designed to target hexanucleotide repeat expansions in the C9R72 transcript that lead to reduced expression of healthy protein, accumulation of repeat-containing toxic RNA foci, and the abnormal expression of neurotoxic dipeptide repeat proteins, or DPRs. Mutations in C9R72 gene are the common underlying determinants driving these diverse and devastating phenotypes. Our variant selective targeting strategy was recently described in Nature Communications. In this paper, we describe our work to identify and validate the targeting site to achieve variant selective knockdown of expansion-containing C9R72 transcripts. The publication highlights the foundational work that led to the development of the clinical candidate. A key reason we remain excited about the potential of 004 is clearly demonstrated on slide 22, showing Preclinical data recently presented at the 31st International Symposium on ALS and Motor Neuron Disease. In this transgenic mouse model, two ICV injections of 004 administered seven days apart resulted in rapid and durable knockdown of over 90% of the DPR polyglycine proline, or polyGP, in the spinal cord and at least 80% knockdown in the cortex with a durable effect out to at least six months. Further, normal C9R72 protein remains unchanged at that time point. Measurement of polyGP in the CSF is a key endpoint in our clinical studies, so we are looking forward to assessing the impact of treatment in humans given these promising preclinical results. Like our SNP3 trial, the planned Phase B Phase 1B-2A clinical trial for 004 will be adaptive with both single and multiple ascending dose portions. The clinical trial will enroll up to 50 patients with a documented C9R72 expansion and a confirmed ALS, FTD, or mixed phenotype. A DSMB will guide the level of dose escalation and subsequent dosing interval, enabling the potential for rapid proof of concept. Safety and tolerability of 004 will be assessed along with key biomarkers of target engagement in neurodegeneration, including polyGP and neurofilament light chain. Key exploratory clinical outcome measures to be assessed include the ALS-FRS-R and CDR-FTLD. Clinical trial site activation is ongoing, and we anticipate dosing a first patient this year. Finally, I would like to discuss WVE-N531, our exon skipping candidate we plan to evaluate for patients with Duchenne muscular dystrophy amenable to exon 53 skipping, and the first splicing candidate in our pipeline to use PN backbone chemistry modifications. The N531 program is guided by work in DMD with Suvidersen, which used our first generation PSPO chemistry. Biopsies from our open-label study clearly show that suvidersen reached muscle tissue but did not achieve target engagement, apparently due to poor intracellular access in dystrophic muscle. Our decision to advance N531 was driven by the compelling preclinical data for the candidate, as well as that of surrogate compounds incorporating PM backbone chemistry modifications. This evidence includes dose-dependent increases in dystrophin production of up to 71% in vitro in patient-derived myoblasts with N531, higher concentrations and broader distribution in non-human primates with N531 as compared to first-generation chemistry, supporting the potential for biweekly dosing. And lastly, rescue of double knockout or DKO mice from a rapidly fatal phenotype with a PN-containing exon skipping compound, as shown on slide 25. As a reminder, the DKL mouse model has a mutation in exon 23 leading to a lack of dystrophin, as well as a second mutation leading to a lack of eutrophin production, resulting in severe and rapidly fatal phenotype. A recently completed study shown here, we compared the effects of a PSPO-containing molecule dosed at 150 mg per kg weekly to a PN-containing compound dosed at the same level and at 75 mg per kg every other week, as well as a PBS control group. On this slide, there are survival curves for these treatment groups. Other than placement of the three PN backbone linkages, these molecules have the same sequence and chemistry. Despite that, there is a dramatic increase in survival in those animals treated with the PM-containing compounds as compared with other treatment groups, including at 75 mg every other week, a dose 75% less than that of the other groups. Both cohorts of mice treated with the PM-containing compounds survived to the time of study termination at 40 weeks as compared to a median survival of approximately 12 weeks for the cohort dose with the PSPO-containing molecule and a median survival of only 7 weeks in the PBS group. Not shown in the figure was a separate matched control group of MDX mice, which lived to study termination. We are on track to submit a CTA for N531 in the first quarter of this year. In fact, the submission is imminent. The planned clinical trial will be open label and enroll up to 15 patients with DMD amenable to exon 53 skipping. Patients will receive a biweekly dose of N531 and dosing will be driven based upon PK data and safety observations. The trial will be powered to detect a change in dystrophin production and will assess intracellular drug distribution in muscle as well as initial patient safety. If successful, there is the potential to apply PN chemistry to other exon-targeting compounds, and discovery work is ongoing. I will now turn the call over to Kyle Moran, our Chief Financial Officer, to report our financial results. Kyle?
spk09: Thanks, Mike. Wave reported a net loss of $28.8 million for the fourth quarter of 2020, compared to $56.8 million in the same period in 2019. For the full year, ended December 31, 2020, the company reported a net loss of $149.9 million. as compared to $193.6 million for the year ended December 31, 2019. Research and development expenses were $30 million in the fourth quarter of 2020 as compared to $49.1 million in the same period in 2019. Research and development expenses were $130.9 million for the full year of 2020 as compared to $175.4 million in 2019. The decrease in research and development expenses in the fourth quarter and full year was primarily due to decreases in external expenses related to WAVE's decision to discontinue its Suvidersen program in December 2019, as well as decreases in compensation-related expenses and other external expenses driven by WAVE's February 2020 cost reduction plan, partially offset by increases in external expenses related to clinical and preclinical activities related to its HD programs and its C9ORF72 program for ALS and FTD. General and administrative expenses were $9.7 million in the fourth quarter of 2020, as compared to $13.8 million in the same period in 2019. General and administrative expenses were $42.5 million for the full year of 2020, as compared to $48.9 million in 2019. The decrease in general and administrative expenses in the fourth quarter and full year was primarily driven by the cost reduction plan announced last February. WAVE ended the fourth quarter of 2020 with approximately $184.5 million in cash and cash equivalents as compared to approximately $147 million as of the end of December 2019. The increase in cash and cash equivalents year over year primarily reflects the $93.7 million in net proceeds from its September 2020 public offering and $59.9 million in net proceeds from its aftermarket equity program. We continue to expect that existing cash and cash equivalents, together with committed cash from our existing collaboration, will enable WAVE to fund its operating and capital expenditure requirements into the second quarter of 2023. As a reminder, we do not include potential milestone payments and other uncommitted payments related to our Takeda collaboration in our cash runway. I will now turn the call back over to Paul for closing remarks. Paul?
spk08: Thanks, Kyle. WAVE is entering 2021 with depth and diversity throughout our pipeline and platform, and we look forward to several upcoming milestones. At the end of the quarter, we anticipate sharing data from our precision HD study, and as Mike mentioned, our CTA submission for our Exon 53 candidates is imminent. Including this Exon 53 program, we are on track to initiate dosing in three new clinical trials this year. And importantly, we are well capitalized to advance all of these programs through clinical data. Lastly, we continue to generate exciting data for our 8R editing modality and anticipate sharing preclinical data for our in vivo model and Alpha-1 antitrypsin program. With that, we'll open up the call to questions.
spk02: At this time, I would like to remind everyone, in order to ask a question, please press star one on your telephone keypad. Again, that is star one on your telephone keypad. Your first question comes from the line of Salim Seed from Mizuho. Your line is open.
spk06: Great. Good morning. Thanks so much for the questions, guys, and the color. So, Paul, obviously, an important data set coming up at the end of the month. I was just wondering if you can just articulate for us how you're thinking about – this is a very Wall Street-y question. I apologize. The bogey here, what's a win scenario, especially on the 32 milligram data? How are you thinking about the various scenarios that we can get? And then two, more of a higher-level question here. Maybe I'll just answer the first question first, and I'll follow up with the second one. Thank you.
spk08: No, thank you. And I wouldn't call it a Wall Street question. I think this is a question that's on the mind of our patients and clinicians as well. And it is an important question for us as a company as we think about the possibility to progress to phase three. I'll start, and then I'll hand the question over to Mike. But I think what we've continued to look at is a profile that does two things, and I think, as Mike alluded to in his section, the wild-type assay being an important one. I think, one, we want to see, if we see a reduction of 20 to 30%, which is in line with where our peers are in a pen silencing approach, and are able to see, in addition, wild-type sparing we do believe that that's a successful profile to advance not just in the Phase III studies, but also to think about the pre-manifest population more broadly. So as we think about a profile that could be superior to existing programs, we think that that's a profile that supports moving forward. Mike, do you have anything you want to add to that?
spk01: Only that, I mean, I think that this, as you said, it's a question that is something we've been considering with our partners and clinicians and other people in the field. And, you know, I think the allele selectivity aspect of it, we hear time and time again that even thresholds lower than that could be meaningful if we're shown to be allele selectivity. But as Paul said, that's where we believe we need to be, and it would be a big success.
spk06: Any comment on NFL expectations or how we should be thinking about NFL expectations?
spk08: I think what we'd like to see, I mean, I think like everything else, we need to generate the data and analyze it. But I think if we can analyze the data and see a flat, a decrease in NFL, that would be different than other profiles that have been seen. But I think we have to generate the data and analyze it on two fronts. And I think that's the same on the NOCDA. I think we're going to look at, and that's why this data set is robust in the sense that we'll be looking at not just the potency, as you pointed out, of the 32 milligrams, but we're also going to be able to look at an open-label extension data across two studies at the up to 16 milligrams and see what happens over time. So I think we'll get a good assessment in both of those studies at NFL levels at the time we have data to share.
spk06: Got it. And then just a quick follow-up, if I can. Strategy-wise, which one are you more excited about, the HD data coming up at the end of March or the PN chemistry pipeline that follows subsequent to that?
spk08: I think we're excited about both, right? I mean, I think it's an opportunity. We had an interim look at a partial data set in December of 19, which was just, you know, a snapshot and all patients hadn't received all doses. So I think for us, and that was just SNP2, we hadn't looked at SNP1. So I think, you know, like this has been a study that we're anticipating and looking forward to reviewing the full data from these studies and excited about progressing SNP3 and what that brings with PN chemistry, not just in SNP3, but also with C9 and then splicing with DMD. I do think it's important to note that, you know, we could have applied our PN chemistry to a pen silencing approach and said, you know, let's just move forward in a way based on following where others have been. And I think that data, as Mike alluded to in great detail, and, you know, I think it's important, around wild-type sparing, led us to apply the PN chemistry to an additional allele-specific compound in CYP3. I think we're looking forward to this data. I think we're looking forward to the upcoming data around the three new programs. And I think the key for us is a commitment to Huntington's disease.
spk06: Great. Thanks, Paul. Thanks, Mike. Appreciate the call.
spk08: Thanks, Mike.
spk02: Your next question comes from the line of June Lee from Trust Securities. Your line is open.
spk10: Hi. Thanks for taking our questions. If the results of the upcoming high incidence updates are below your threshold of 20 to 30%, but there's some signal that you still want to proceed with the SNP1 and 2 programs, would you go up in the dose or switch to PM backbone altogether? And related to that, what proportion of SNP1 and 2 patients also have SNP3 that could be treated with your SNP3 program? And up to what dose are you planning to test for the SNP3 program? Thank you.
spk08: So I'll take part of the question, then hand to Mike. And I think the question I'll take is the reason we chose SNP3 at the beginning was because in and of itself, given the overlaps where there's SNP1, 2, and other SNPs, SNP3 covers 40% of the Huntington's disease population. It gives us an incremental 10% on and above SNP1 and 2, but it is a substantial portion of Huntington's disease by itself. Mike, do you want to take the question as it relates to dose escalation?
spk01: Yeah. So, I mean, I think that if we saw some very promising target engagement in a safety profile and allele specificity that all lines up, you know, we would consider going up higher and starting that planning for phase three at the same time. Because, you know, if we have some robust engagement and a good profile and allele specificity, And, you know, we know we can go higher based on our existing preclinical data in terms of the range we can go. There's no reason we wouldn't do that, but we would do that as we were beginning the planning for that next phase of development. And, you know, and I think you asked one last question about in terms of the dose in SNP3. Yes. We are going to base that starting dose on our preclinical data, and as we said, that will then be from there guided in a very data-driven way by our independent data safety monitoring board.
spk10: But your preclinical data implies that you use a lot higher dose for SNP3 than you did for SNP1 and 2. Is that correct? If so, does that mean that you're also going to test a lot higher dose than what you did for SNPs 1 and 2?
spk08: I think the key on it, yeah, so what's interesting, remember, about SNP 1 and 2 is we didn't have a preclinical model that guided dosing. So a lot of the dose exposure work was done, right, in potency in vitro and then exposure in vivo. The data that's going to guide the starting dose, which is why we believe we could start a relevant dose in SNP3, and as Mike said, be able to accelerate that study in terms of exploring doses beyond that, is because we have in vivo PKPD modeling on target engagement with SNP3. So we have to look at those programs differently around where we can guide our starting dose. and ultimately where we get to. They're different drugs, and I think SNP3 leveraging our PN chemistry, we have a lot more data, in vivo data, as we alluded to earlier, to guide those dosing decisions. Mike, is there anything you want to add to that?
spk01: No, only one thing you alluded to is that the beauty and the power of this platform is each one of these compounds are different from one another, and that they have their profiles and they're rationally designed individually. So there is, by definition, just like with any compounds, you're going to have different numeric doses to achieve what you're looking for. So that would be the only thing I'd say is that, you know, the beauty is having a single compound that we can then optimize in preclinical, each individual preclinical study.
spk08: And I think for step one and two, I mean, and I think the previous question addressed this, I think that's why we were excited about this data set. In the absence of preclinical PKBD modeling, we'll have answers around human data at various doses, you know, higher doses to long doses in terms of accumulation. And so I think, again, this being a robust data set, it's really going to tell us where we are.
spk10: Great. Thank you.
spk02: Your next question comes from the line of Mani Forohar from SVV Lyric. Your line is open. You may ask your question.
spk07: Hey, thanks for taking the question. I guess the first question is around this upcoming 100 disease readout. Should we expect that the assays being used in this readout should be, you know, moderately different in any subtle ways from what was used in the last time we saw data from this study in late 2019? And you mentioned something about, you know, the pull-down assay with magnetic beads and subtle changes to the assay. How should we think about those changes as we interpret these datasets? And secondarily, when you think about it, actually, we'll start with that before I have the next question.
spk08: Just so we can make sure we get that one to completion, I'll start and then Mike will pick up. But I think the most important piece is the mutant Huntington assay and the neurofilament assay are the same assay we used in the previous readout. Those are Those are assays that have been used by others, and so, you know, no change in the interpretation of how those assays are run. What's new is really, you know, the work, and the team's done an amazing job this year of really working through how to develop an assay to assess wild-type. And so, Mike, do you want to take the second piece? Because that is a different assay than the total assay.
spk01: Yeah, I mean, I think the work that's been done has to take these assays and the available reagents that have already been used in the field and already what we used in the initial assessment and modify them in a way that allows us to directly measure wild type protein so the antibodies being used in this pull down approach are the same antibodies that would be used in that measurement in the mutant huntington assay except that they're now applied to beads and we use that approach to pull out the mutant, so we can directly measure wild type on a total assay that has also already been developed. So in terms of interpretability, I mean, with mutant, it's going to be the same, and the wild type now is a new approach that we'll be presenting in the context of the mutant. But it's using available reagents. It's using techniques that have been deployed before.
spk07: Great. That's really helpful. And in considering Wave 003 or SNP3, whichever you want to call it, in considering time to data, how should we think about the sites in which patients are being enrolled and the rate of enrollment and the impact of screening around SNP3 to determine when we might see that?
spk08: I mean, I'll share with Maya. I think step one is, you know, obviously we'll set the framework once we've dosed and how to think about going forward. I think what we've leveraged, and, you know, we've said this a couple of times, which I think is really important, is we're able to leverage the infrastructure, the clinical trial infrastructure, the SNP phasing and screening infrastructure, the running CASAs. I think there's a lot that we can take from SNP 1 and 2 in terms of infrastructure, architecture, and execution. and be able to apply that rapidly to SNP3. Mike, I don't know if there's any additional insights that you want to add to that.
spk01: No, I think that the sites we've been working with for years now know how to do this, and then it's just a matter of getting those prospective numbers on SNP3 from patients that they have in their practices. So, no, I think once we get the first patients in, we'll be able to really see where we are.
spk08: I think, you know, just to echo and add on to that, I mean, that is the advantage of having run these SNP phasing studies over time is we can identify the SNP3 patients to get, you know, get a start. The clinicians know how to run the studies. And, you know, as we said before, around having the models to predict where we can begin the study, there's a lot of features that we think are in place now for this study to execute a lot more quickly than the first two where we had to start a lot earlier.
spk07: Great. Thanks. That's really helpful.
spk02: Your next question comes from the line of Paul Matias from Stiefel. Your line is open.
spk00: Hi. Thanks so much for taking the question. This is Thor on for Paul. I think you mentioned previously that it was a COVID dosing delay, but can you just give us a little color on why we won't have 32 milligram data in HD1? And then kind of a follow-up to that, is there any reason that this 32 milligram data in HD1 will be meaningfully different than HD2 data at 32 milligrams? Thanks.
spk08: No, great question. And as we said last year on our call where we provided that update, there were two patients that had to be rescheduled for their dosing related to COVID. And because of that, they'll get their last dose in the end of March or March. So given that shift, they're there, they're scheduled, they'll be dosed, and that's, you know, that was unfortunate last year, but that's what we are dealing with in terms of a global pandemic. In addition, to your point of will we see differences, that's why we think this is a robust data set and we'll be able to make an interpretive decision with that because we'll have matched cohorts up to 16 where we can compare that pharmacology between SNP1 and 2, knowing that the SNP, sorry, the SNP1 32 milligram data will be following on that. So You know, it is, you know, as we'll always say, you know, different molecules, you know, there could be differences. But we'll have the data to determine where we are, and we'll have that data in on the other side. But given, you know, past experience and understanding, what we don't want to do is cut a partial data set. We'd rather let the data set be intact and evaluated, and based on the other data we'll have, including the open label extension data sets, you know, through 16 across SNP1 and 2, we believe we'll have the data that's necessary to relate SNP1 and 2 pharmacology.
spk00: Great. Super helpful. Thank you.
spk02: Your next question comes from the line of Luca Ecy from RBC. Your line is open.
spk04: Oh, great. Thanks for taking the question. This is Lisa Walter. I'm for Luca. Just, again, on your HD program, we recently saw some data from the Open Label Extension Trial for Thionis and Roches to Minnersen on the European Clinical Trial Register. The data here was early, but it suggested no cognitive benefit by HD-CAB, nor a benefit in ventricular volume. Just wondering, what was your reaction to that data? How should we think about implications for your program? Thank you.
spk08: No, thank you. And this is a question that, you know, we focused on actually years ago when we began our program. I mean, if we think about the early days of when we decided to go into Huntington's disease with our oligo approach, our view was to take an allele selective approach because we believe the biology supported that. We always said, as both studies were kind of moving forward, that the reason we were taking an allele-selective approach in sparing wild type is that Huntington's is both a toxic gain-of-function and a toxic loss-of-function disease. Both are important, and I think Mike eloquently shared this tug-of-war concept that I think is just so critical, at least to try to imagine this really is a two-pronged disease. Our view was that sparing wild type and wild type or wild type reduction wasn't going to be, quote, a safety signal, but what would probably be the manifestation of treating the toxic loss of function would be that it would become harder to see a clinical benefit with a requisite amount of youth knockdown. And so, therefore, our approach was remove the mutant toxic gain-of-function protein, but preserve the toxic loss of function so that you have the protein there to help. You know, we have to see this study go out. I mean, you know, this thesis, you know, we're running the The allele-specific silencing clinical studies, it's interesting to watch what PAM silencing does. But there's two different biologic approaches that we're taking in the treatment of Huntington's disease. So we have to watch the data emerge and be prepared. But I think this is aligned with some of our thinking around what happens when you deplete wild sites. Mike, I don't know if there's any addition, anything you want to add?
spk01: No, nothing to add, Paul. That captures it nicely.
spk02: Your next question comes from the line of Yun Yang from Jefferies. Your line is open.
spk05: Good morning. Thanks for taking our question. This is for Yun. I have a few questions about the HD program. The first one is about the wild-type hunting NSA that you're going to be using. I'm just wondering if that has been validated with external parties. And also, for the OLE data that you're expecting to report, how is do you expect to utilize the data to guide the next step? And I have a follow-on question on the alpha trypsin deficiency program. Thank you.
spk08: Mike, would you like to take the first two Huntington's questions?
spk01: Sure, yeah. So regarding the assay, we have been working with the developers of the original assays that we employed to develop this particular assay. We've been working with to get patient samples that have allowed us to go through the validation process for the assay. And our intention is to work with those external parties to publish the assay and share the results and share it with the community at large so that it can be used. So this has been a, you know, we couldn't have done what we've done with this assay without the collaboration of external parties and we're really pleased where we are and And they're really pleased where we are. In particular, our partners at CHDI who, you know, without their work, we wouldn't have been able to leverage and adapt to take this next step. Regarding the OLE data, I mean, that's a really important data set. I mean, you know, when you think about the precision HD studies, you think about any proof of concept study. you want to get that short-term exposure to try and get a nice, clear, short-term dose response. The OLE gives you that added power, even though it's open label, in the setting of a biomarker like we're doing, it really allows you to see not just a dose response, but the impact of chronic longer-term dosing, which gives you a sense of not just an effect, but the depth of the effect with chronic treatment, as well as safety, of course. But what we've seen from the Roche Iona studies is that the degree of mutant knockdown, the degree of Huntington knockdown, I should say, in a plant-selective way, increased with extended duration. So it's a really important data set that is going to help us in our decision-making as we look at dose selection for future studies. So it's very valuable to be able to have this, and we're grateful that patients have opted to continue in the studies.
spk05: Thank you. And my follow-up question is with AATD. Based on the non-human primacy, what would be a reasonable expectation for the mouse model data?
spk08: Yeah, I think there's two things, and this is why we actually want to run the mouse model data and the work, you know, twofold on the mouse model. One is to make sure that, you know, not only are we looking at the serpent A1 animal model, but we're doing it in the cross with the human ADAR mouse, is that we can expedite the work that we do on optimization so that we're not optimizing a sequence to edit mice, but we're optimizing a sequence that can be clinically translated to patients because it expresses human ADAR at the appropriate levels. I think what's interesting and exciting about using the mouse work is while we see substantial editing efficiency in NHPs and we can edit mice, we can move from just looking at a percent editing of a number, because we know that just like a number of oligosaccharides, it's not a one-for-one ratio of an editing to generating protein, but in the animal model, really be able to start measuring the protein levels. So there's correlation looking at editing percentage, but really starting to establish biomarker thresholds in terms of how much protein you need. You know, we know, as we think about in the clinic, that restoring of levels greater than 11, you know, micromolar AAT proteins ideal. We know that the protein infusions there are leaving patients uncovered for a good amount of time. And so, you know, our belief is by using the model, we can really do several things. We can continue to characterize the protein production, the fact that it's functional, and be able to start establishing dose responses, as we have for a number of our other programs in silencing and splicing. that we can then translate those molecules to the clinic. So, you know, I think we've got, you know, great data around galnet conjugation and exposure in NHPs. We've got exposure in mice using, you know, now getting the human ADAR coupled with the target. So I think if we can see durability and duration, we can see PKPD and generation of protein, you know, those will be the features that we'll be looking for as we set up a transition to the potential of a clinical program here. But we're very excited about ADAR as a space and how we can apply it broadly. And we're excited about the AT program specifically.
spk05: What is the expected dosing frequency for this program?
spk08: I apologize. You broke up a little bit on that.
spk05: Oh, sorry. What is the expected dosing frequency? for age?
spk08: I think that's, yeah, that's what we're going to establish as we, you know, that is the primal, you know, example. We look at duration, too. So, when we think about the dosing frequency, that's going to be driven based on our preclinical models. Obviously, now with GalNec, we have subcutaneous administration that we've looked in both large, animal, and small. So, we know that subcutaneous administration with GalNec is efficient. But we need to do that work in the in vivo models to explore that PK-PD relationship to be able to move forward.
spk05: Okay, great.
spk08: Thank you so much.
spk02: Thank you. And presenters, there are no more phone questions. I'll now turn the call back over to Dr. Paul Bono.
spk08: Thanks, everyone, for joining the call this morning to review our fourth quarter and full year 2020 corporate update. And thank you to our WAVE employees for their hard work and commitment to patients, especially amidst the global pandemic. We look forward to speaking to you again soon. Have a great day.
spk02: This concludes today's conference call.
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