Absci Corporation (ABSI) on Q3 2021 Results - Earnings Call Transcript
Operator: Good day and thank you for standing by. Welcome to the AbSci Corp. Third Quarter 2021 earnings conference call. At this time all participants are in a listen-only mode. After the speakers presentation there will be a question-and-answer session. . Please be advised that today’s conference is being recorded. I would now like to hand the conference over to your host today Alexander Conn , Investor Relations. Please go ahead. Unidentified Company Representative: Thank you. Earlier today Absci released financial results for the quarter ended September 30th 2021. If you have not received this news release or if you'd like to be added to the company's distribution list, please send an email to investor.absi.com. Joining me today from Absci are Sean McClain, founder and CEO; Greg Schiffman, CFO; Matthew Weinstock, CTO; Kate Corcoran, VP communications; and Jim Patricelli our new VP investor relations. Before we begin, I'd like to remind you to manage or make statements during this call that are forward-looking statements within the meetings of Federal Securities Laws. These statements about material risks and uncertainties that could cause actual results or events to materially different from those anticipated. You should not place undue reliance on forward-looking statements. Additional information regarding these risks and uncertainties appears in the section entitled “Forward-looking” statements in the press release Absi issued today. For a more complete list the description, please see the risk factors section of the company's most recent filings and Forms 10-Q, S-1, and other reports on file with the Securities and Exchange Commission. Except as required by law, Absi disclaims any intention or obligation to update or revise any financial projections or forward-looking statements whether because of new information, future events, or otherwise. This conference call contains time-sensitive information and is accurate only as of the live broadcast. November 9th 2021. With that I would like to turn the call over to Sean. Sean McClain: Thanks, Alex. Good morning and thank you for joining our third quarter 2021 earnings call, our first as a public company. Our team of Unlimiters has built technology to enable better, faster, smarter biologic drug discovery and cell line development. And we are excited to share our latest financial’s and operational updates with you today. Indeed, our outlook has never been more encouraging. 2021 has continued to be a momentous transformative year for Absci, exemplified by tremendous growth and punctuated by strategic acquisitions and partnerships, important additions to the team in key roles and our debut as a public company. All on top of the scientific innovation we do each and every day. At Absci we are translating ideas into drugs, channeling R&D investment and drug discovery and bionic protein technologies, and developing our innovative drug discovery and bio manufacturing platform as we continue to drive toward our goal to predict the absolute best protein-based therapies for patients a truly unprecedented speeds. This is where the industry is headed and we're excited to share our progress with you all today. Through our integrated drug creation platform, we expect to get better drugs to patients at unprecedented speeds by merging AI and biology. One of the many exciting aspects of our technology is that we have the unique ability to generate billions of data points on protein functionality and manufacturer ability in a single experiment. And we are feeding this data into AI deep-learning models to allow us to predict better drug candidates for patients with unparalleled speeds. At Absci, we have developed a differentiated business model that focuses on partnerships, wherein we develop the drug candidate and associated cell line, out license that to our partners, and benefit from program fees, milestones, and royalties. This is the core of where the value of our platform lies, in the NPV per program or the lifetime value of each program that we work on. At the end of the quarter, we had nine active programs with seven partners that have downstream economic potential. Subsequent to quarter end, we signed an exciting deal with EQRx which I'll speak to in more detail later on. Along with our growing capabilities and enterprise, we recently built and moved into a state-of-the-art campus nearly 80,000 square feet of lab and office space, a truly inspiring place to work. Last week we hosted Washington Governor, Jay Inslee, for a formal ribbon-cutting ceremony, and it was humbling to reflect on the journey over the last 10 years, starting from a basement to the beautiful one of the kind facility. For Absci, the move to this new facility strengthens our capabilities and bolsters our organizational transformation into an innovative and collaborative discovery space. This year alone, we have also announced two transformative acquisitions, kicking off the year with our addition of Denovium in January followed by Totient in June. With the integration of these two technologies and teams, we have significantly expanded our capabilities advancing on the front end of target identification from disease tissue through our acquisition of Totient while incorporating deep-learning AI across our entire platform to drive our in silico drug discovery and CLD through our acquisition of Denovium. Our collective skill set with Denovium and Totient enhancing the core outside platform represents the perfect synergy of ground breaking synthetic biology and cutting edge deep-learning AI to create in silico predictive protein drug design and cell line development capabilities, with the potential to change the paradigm of biopharmaceutical, discovery, and development. Incorporating AI deep learning will allow us to explore all possible protein sequences in silico to identify drug candidates with optimal therapeutic properties and manufacture ability. Combining that design power with proprietary data from our integrated drug-creation platform, Absci can create a new gold standard for drug discovery and cell line development for next generation biologics, while at the same time allowing for creation of novel biology previously unattainable. As for Totient, their innovative work identifying disease relevant molecules has exciting therapeutic potential. We believe that the combination of the Totient technology, with Absci's platform and the inclusion of Denovium's AI, provides us the framework and the data to enable in silico target drug design, and ultimately achieve our goal of making the best medicines available to patients. Earlier this year, we announced this exciting biologics development collaboration with Xyphos, an Astellas Company, and a strategic investment by Merck Global Health Innovation Fund. New partnerships are a key component to our future success, while we execute on programs with our existing partners. Even with the continuing COVID environment and recent headquarters move, we relentlessly push forward executing against our plan. In Q1 of this year, we signed and initiated two cell line development programs with a undisclosed new partner. Then last month, we announced a multi program partnership with EQRx to discover and develop next generation protein-based drugs. This partnership leverages Absci's drug creation technology for discovery and development activities along with EQRx clinical development expertise, and commercial capabilities to advance next generation protein-based therapies at more affordable cost to patients. This collaboration with EQRx expands the reach of our AI-powered target discovery, drug design, and development technology. Together, we look forward to discovering differentiated next generation biologics, driving efficiencies, and accelerating timelines so that our future medicines can have the biggest impact possible to patients in need. As we sit here today, things are moving forward on schedule with work plan for the first target already in progress, and we intend to initiate this program around year-end. We also had success this year in advancing two important partnerships. In Q2, we entered into a global technology development and license agreement with PhaseBio to advance an active program for creation of a customized cell line that is expected to enable high-yield commercial production of that clinical candidate. This exciting agreement represents our near-term opportunity for potential royalty revenue. In addition, we signed a global technology development and license agreement with Alpha Cancer Technologies, extending our existing technology development partnership and entitling Absci to contingent milestone payments and royalties on net sales of products comprising recombinant human Alpha fetoprotein manufactured using the producing cell line developed by Absci. Living up to our successful IPO in July, we had several key talents join our team and our momentum has continued into the fall. In July, we announced two executive hires joining our team; Nikhil Goel and Dr. Sarah Korman. These appointments came at a time of significant growth for Absci, as we scale our technology, development programs, and partnerships and integrate the Denovium and Totient acquisitions. We have also success in growing our talented and innovative team today, comprising nearly 220 Unlimiters, up from 74 when the year began. We have been successfully recruiting top talent to the Vancouver area in part because of the promise of our platform and our vision to revolutionize the industry. Our vision is to get better drugs to patients more quickly than ever before, resonates with prospective candidates who are eager to contribute to this important mission and legacy. Of course, all these ambitious activities, building, developing, hiring, and executing takes funding. We have successfully completed several financing this year raising over 435 million including both a key crossover round in March and subsequent July IPO. And we have no intention of stopping there. It took 10 years for Absci to lay the foundation which will allow us to achieve our vision for the next 10 years. We now have access to capital, technology platform, and talented team in place to execute our vision. Late last year, we began building out our discovery pipeline, and shortly thereafter, executed on two key acquisitions. And then a couple of short quarters, it translated into an exciting new discovery deal and boosted our pipeline of future opportunities. This is further demonstration, that with the right team, innovation can ramp quickly. Let me reiterate. We are very encouraged by our progress and excited by the feedback we're receiving in the marketplace. In terms of our adoption rate, our ability to monetize acquisitions and our focus on internal R&D efforts. We are hitting our stride as we host our first earnings call, and we look forward to many more to come. I'll now turn it over to Matthew to tell you more about some of our recent technical accomplishments. Matthew? Matthew Weinstock: Thanks, Sean. And hi, everyone. I'm going to highlight four main areas of R&D investment in Absci and the accomplishments those investments have led to, along with how it's driving business opportunities. Those main areas include: one, our drug discovery capabilities; two, bionic proteins; three, the Denovium acquisition and AI investments; and four, the Totient acquisition and the scope of computational antibody and target discovery activities and assets. Regarding our drug discovery capabilities, in 2021, we succeeded in building out our discovery team on plan to augment the necessary skill sets from early discovery up to IND-enabling studies, tailoring our proprietary screening technologies to enable drug discovery activities, bringing online additional capabilities necessary to support drug discovery efforts, such as library design, high throughput biophysical characterization, and cell-based assays in generating sufficient proof of concept data to result in the closing of a substantial multiple program partnership with EQRx. Next, I'd like to highlight what we call Bionic Proteins. Natural proteins are composed of different combinations of 20 naturally occurring amino acids. Through our Bionic Protein technology, we are able to unlock new chemistries, not afforded to us by nature, through the incorporation of non-natural amino acids. These specialized amino acids, not found in nature, provide a unique chemical handle to cite specifically modify these proteins with additional chemical functionalities. Applications of an opportunity for this technology include attachment of chemotherapeutic molecules or payloads to antibodies to generate extremely targeted next generation cancer treatments that are more efficacious and have less side effects than current chemotherapies, and improving the circulating half life or PK/PD properties of existing drugs through site specific regulation. This year we developed our proprietary Bionic SoluPro system to enable consistent incorporation of non-natural amino acids. Demonstrated success incorporating non-natural amino acid residues into therapeutically relevant molecules at high titer that is greater than a gram per liter and with high quality. We are currently discussing deals with multiple partners ranging from small biotech to multi program partnerships with big pharma to utilize this technology for development of next generation therapeutics. Next up is the Denovium acquisition and AI investments. AI capabilities were brought on in early 2021 through the acquisition of Denovium, an AI company focused on applying deep learning to genomics and protein discovery and design. Since the acquisition, we have built a robust informatics and AI platform that includes teams with world class expertise. Much of the focus this year has been on establishing the necessary infrastructure to support our AI initiatives to enable us to effectively scale over the coming years. This includes building pipelines to properly organize and structure our data to enable automated ingestion by our algorithms, and setting up our own internal GPO cluster equipped with the latest in NVIDIA GPUs. We had some early wins in demonstrating the value of AI on cell line development programs, where an AI predicted novel chaperone protein doubled the titers and improved the molecular quality on one of our partnered programs resulting in a significant program milestone. On-going initiatives continue to develop the technology to design robust manufacturing cell lines, as well as applying the technology to drug discovery efforts. One example I am particularly excited about is the application of these technologies to enable in silico affinity maturation of antibodies and antibody fragments, which will allow us to predict drug candidates that will have optimal properties from a drug-develop ability perspective and to do so very quickly. We look forward to sharing more detail about this in the coming months. I want to conclude by spending a few minutes discussing our computational antibody and target discovery activities. With the Totient acquisition, we acquired a robust antibody and drug discovery platform that is now allowing us to computationally reconstruct antibodies and other disease-specific proteins from both RNA sequencing data collected from disease tissue. This is important because it addresses a major challenge in the biologics discovery world. A limited number of validated, high-value, disease modifying targets for drug development. For example, just 10 targets, including the likes of PD-1, CD20, TNF, HER2, VEGF, IL6, EGFR, and CD19 account for roughly half of FDA new drug approvals. Building on Totient's ability to identify fully human disease modifying antibodies from patients with differentiated immune responses, we are building what we expect to be the world's largest database of human derived antibodies to novel and known tissue specific antigens to supercharge drug discovery efforts. To date, Totient has reconstructed more than 5,000 antibodies from over 65,000 patients. These patients’ samples cover more than 46 cancer types, autoimmune disorders, and infectious diseases, including COVID-19. And as the orphaned a collection of promising antibodies by identifying and validating their target antigens. The result is a comprehensive integrated drug creation platform offering potential partners the opportunity to work with us to address novel disease targets and access new fully human monoclonal antibody sequences, either as therapeutics in their own rights or as starting points for the design of next generation biologics in other scalpels. Our proprietary computational approach allows us to infer antibody sequences from tissue RNA, and we use those sequences to identify target antigens. We expect this to be quite a compelling value proposition and competitive differentiator for Absci in the marketplace. Unlike other approaches in the target discovery space, our methods do not require the processing of fresh tumor tissues or isolation of single immune cells. Instead, we can work with RNA sequencing data generated from banked tissue samples, including older formalin-fixed paraffin-embedded archival specimens that have been collected by academic consortia, clinical trials, and commercial bio banks. Thus, we have the opportunity to direct our technology toward high volume and highly curated source tissues selected for desired disease and therapeutic response profiles, giving us more shots on goal compared to those looking at single-cell sequencing or fresh tumor samples. We reconstruct human antibodies from both RNA sequencing data from disease tissue allowing us to retrospectively pick patients with distinct immune responses and assemble the most prevalent monoclonal antibodies expressed in the tissues of interest and presumed to be contributing to the immune response. Another key differentiator of our platform is that we sampled disease affected tissues directly, rather than looking at peripheral blood, allowing us to look for active plasma cells rather than memory B cells, which are often unrelated to the on-going pathology. Our novel approach improves the likelihood that the antibodies we discover will be therapeutically relevant. Predating the acquisition, Totient had synthesized, expressed, and purified several hundred antibodies, and subjected a subset of those to further characterizations and de-orphaning to identify the target antigens. Confirmed targets recognized by our in silico paired antibodies includes seven well-known cancer specific antigens, including NY-ESO-1, MAGEA3, GAGE-2A, and DLL3, as well as immuno modulatory molecules expressed in the tumor micro environment, including ASXL1, TGF beta 1, and C4 BTB, in addition to many novel potential drug target antigens. The identification of well-known drug targets with this methodology serves as a proof-of-concept for the potential of this approach using computationally derived antibody sequences to determine relevant antigens for future drug discovery applications. As additional validation of the platform and evidence of the efficiency of our computational human antibody discovery technology, we were able to reconstruct more than 400 distinct fully human antibody sequences for further testing during the COVID-19 pandemic using RNA sequencing data from patients infected with the SARS-CoV-2 virus. We identified over 15 antibodies that bound to the SARS-CoV-2 spike protein with high affinity, a number of which show potential to neutralize infection. This is a potentially powerful approach to enable rapid response to emerging infectious diseases through efficient identification of antibodies that could be useful for diagnostic and/or therapeutic interventions. We expect to continue to evaluate patient tissue samples and extract new antibody sequences that we will subsequently de-orphan. We made source specimens of interest to a particular partner or worked directly with RNA sequencing data supplied by a partner. Since the acquisition of Totient, we have begun to express nearly 14,000 antibodies for de-orphaning activities, each of which could represent a viable candidate for therapeutic development. One particular class of antibodies that we are extremely interested in are those reconstructed from oncology patients that are responding to immune checkpoint inhibitors. These therapies, such as Merck's KEYTRUDA or BMS’ Opdivo are transforming how certain cancers are treated but suffer from the fact that only a minority of patients respond to the treatment. Mounting evidence has shown that patients who generate a robust intra-tumoral B cell response in combination with immune checkpoint inhibitors treatment leads to an improved clinical outcome. Our technology allows us to reconstruct the antibodies from these responding populations and identify antibodies that could be combined with previously developed checkpoint inhibitors to increase the response rate. To date, we've reconstructed over 110 antibodies from these patient populations and are looking forward to exploring their ability to improve response rates, either as an internal program or in collaboration with the right partner. While to date, we have tune our pipeline for reconstruction of antibody sequences. The methodology is extensible to assembly of other proteins expressed differentially in disease tissues, particularly immune system components that conform to conserved architectures. We expect to reconstruct human T cell receptor sequences for example in New York taking a similar approach as we develop for antibodies. Beyond the direct utility of novel antigens that we identify as potential drug targets and if human antibodies that we discover as drug candidates, we believe that the expertise we accumulate as we build our collection of antibody antigen pairs has the potential for much more profound impact. Protein-protein interactions are highly complex and multi parametric. Deep learning neural networks are ideally suited to tackling the sort of complexity. Through the de-orphaning process, we expect to generate large datasets that describes sequence determinants of functional interactions between proteins. Training our Denovium engine models on these data may enable us to hone our predictions of relevant drug sequence variants to design for a given target, or even allow us to identify novel targets in silico from computationally assembled antibody sequences. Eventually, we're driving toward a future in which our AI models enable us to identify novel disease-specific targets and design optimize lead drugs and cell lines to manufacture them all at a click of a button. We intend to generate the right data, train comprehensive models, and realize this industry transforming potential of in silico protein-based drug creation. Our goal is to get the best possible medicines to patients more quickly than ever before. In summary, each of these four areas of R&D investment that I've just described are drug discovery capabilities, bionic proteins, the Denovium acquisition and AI investments, and the Totient acquisition and scope of computational antibody and target discovery activities and assets. It's foundational to our existing achievements and integral to our future business opportunities. Looking ahead, each of these investment areas, individually and in concert, represents future opportunities for Absi to capture, optimize and benefit from. We are particularly excited to update you all on our progress as we continue our successful integration of the innovative Totient assets into our expanding platform. With that, I'll turn it over to Greg to cover the key financials. Greg? Greg Schiffman: Thanks, Matthew. Before we discuss the financial results for the quarter, I want to provide an overview of our financial model and key metrics. As Sean and Matthew have discussed, we are an enabling technology for our partners. We structure our programs to share in the success of our partners. This includes program fees, milestones, and royalties. The greater value we are bringing to our partners, the higher the payoff. As Sean has indicated, we have expanded our product offerings this year beyond our traditional cell line development into drug discovery. This expands our product offering to more comprehensive discovery deals facilitated by the company's strategic efforts this year, which are expected to have far greater economic impact to Absci in the intermediate and long run. We target risk adjusted program value between $10 million and $20 million. This includes discounting all potential milestone and royalty payments after applying for probability for success of each development milestone, and the probability of the drug candidate eventually being approved. We are using industry benchmarks to arrive at the probability of achieving these milestone payments, as well as royalty revenues. Cell line development deals are on the lower end and discovery deal on the upper end of the range. for program work represents an insignificant portion of overall deal value. To date, all of our revenues have been based solely on program work. We expect that to change as candidates begin to move to the clinic business. This has us so excited about the future here at Absci. The work we are performing today has the potential to generate revenues over the next 25 years. Milestone and royalty revenues virtually represent all profit. Thus, our focus is on active and on-going programs and growing that pool. Those include all programs where we are either working on the drug candidate, our partner is pursuing the drug candidate in a preclinical or clinical process where the candidate hasn't been approved by the FDA. As programs mature, we expect to provide insight into where they are in the development lifecycle. We guided to closing five new programs in 2021. The value of these five programs is between $50 million to $100 million today, risk adjusted for both time and probability of success, even though we will only book revenue this year approaching $5 million. You can see now why we focus attention today the program NPV versus current revenue. Revenue for the quarter was up approximately 68% to $1.5 million for the three months ended September 30th 2021, compared to $900,000 for the three months ended September 30th 2020. This is slightly below our internal forecast which was based on our programs predominantly being cell line development programs. We are currently projecting that three of the five yield this year will be discovery deals, creating far greater value future economic potential. Encouragingly, our partners have expressed strong interest in our new and expanded capabilities. However, given the size and scope of the deal, they take longer to execute the traditional cell line programs. This has created revenue recognition timing differences relative to our original projections. However, these discovery programs will generate far more value or greater milestones and royalties. So while we are slightly lower in revenue than our original projections, we are generating greater long term and sustainable value. Research and development expenses were $10.7 million for the third quarter of 2021, as compared to $2.7 million for the corresponding prior year period. This increase is associated with the increased headcount which will continue through the fourth quarter. We have and expect to continue to make significant investments in platform capability expansion. We will provide more detailed guidance in early 2022. However, we currently expect nominal growth in employees targeted for specific skill sets next year, and we expect to have ample resources to execute a significant increase in the number of programs with resources being traded off from some of the current platform development efforts and data generation experiments for our AI models. Selling, general and administrative expenses were $9.7 million for the third quarter 2021, as compared to $1.3 million for the corresponding prior period. G&A expenses include $3.3 million of personnel costs, 600,000 of recruiting-related costs. Public company related insurance and auditing costs are approximately $1 million, and non-cash stock compensation related expenses were approximately $3 million this quarter. Net loss was $23.6 million for the third quarter of 2021, as compared to $3.7 million for the corresponding prior year period, which includes a non-cash charge of $3.6 million related to the re-evaluation of convertible notes and preferred stock warrants. Cash and cash-equivalents were $279.3 million as of September 30th 2021. On July 22nd 2021 Absi completed its initial public offering raising approximately $210 million of net proceeds after deducting underwriting discounts and commissions and estimated operating expenses. Cash usage for the quarter for operating activities was $21.7 million. This included prepaid expenses for public company insurance of approximately $6 million. In addition, the Company acquired approximately $5.6 million in property plant and equipment assets, comprised of additional lab equipment and new facility costs. With that, we would be happy to take your questions. Let me now turn it over to the operator. Operator: Thank you. . And our first question comes from the line of Tycho Peterson with JPMorgan. Your line is open. Please go ahead. Tycho Peterson: Thanks. Appreciate all the color. I guess question on Totient, and curious about your kind of interest and willingness to do kind of accurate development, also how you're thinking about the diagnostic opportunity around that. And then on that kind of neutralized COVID spike protein, it seems like a windows kind of shutdown on monoclonal antibodies given what we saw out of Pfizer and Merck on antiviral data, but I'm curious how you think about that up to any particular as well? Sean McClain: So I guess I'll take the second piece of that question first regarding the COVID-19 opportunity. I agree with you that that probably the opportunities closed for the current variance. I think that we may see that opportunity opened up as the pandemic evolves. That's definitely not a major focus for the platform. The focus at the moment is on oncology and autoimmune disorders. But I do think that that's a key validation of the platform and just how quickly that the team can actually move to identify valid solutions for that. And so I think that's just something worth highlighting in terms of how that how the technology actually works, and also the potential to deploy it in the case of future pandemic situations. And Tycho, I'm sorry but I've already forgotten the first part of your question. Tycho Peterson: How far how far downstream do you take it -- like what your willingness and risk to be kind of at risk development of your own targets and you kind of mentioned diagnostics in your comments as well? I'm curious just broadly how you feel about that opportunity for Totient. Sean McClain: So the diagnostic piece is not one that that we've thought too deeply about at this point. We've just noted that there's definitely an opportunity there for us should we ever want to move in that direction. And then in terms of the development of the assets that are coming out of that pipeline, that's something that we're definitely internally evaluating exactly how far we want to take those things. Obviously there's more value the further along we take them kind of down the validation and toward IND, but there's also more investment involved in that. So it's kind of striking a balance there. We don't we don't see ourselves taking things through the clinic by ourselves at any time in the near future. But just how far you know how close to the clinic do we need to take things before we partners those assets office is something that we're exploring. Matthew Weinstock: And Tycho, in regards to the target validation itself we can either take partners data that they have and work with them on doing a targeted discovery program, or we can take patients samples from hospital collaborations that we have and validate those targets internally and we are planning on executing on both of those strategies. Tycho Peterson: Okay. That's helpful. Sean, are you able to say anything more about it EQRx? I know you mentioned the multiple therapeutic areas, oncology, immunology, and your plan your first target work in here, but can you just talk a little bit about your priorities under that partnership and other downstream economics on this one. Sean McClain: Yes there are downstream economics on this deal. Currently, at this time, we can't talk about the targets themselves, but we can't say that it is a multi-target, multi-program deal that we're very excited about. Tycho Peterson: Okay. And then last one for Greg. Just a question around visibility into project revenue streams. You come up a little bit like in this quarter in the street. If I look at next year the street's got you down about 13.5 million. Anything you're willing to say on numbers for next year given how things are played out these last two quarters. Greg Schiffman: So guidance -- it's preliminary for us to give guidance for next year. We have been impacted this year we indicated early timing related where we have seen the interest from our partners moving from cell line development into discovery, and those deals took longer to close than our original estimates would have been for us cell line development deal. And that's caused some timing differences on revenue. I don't think we're ready to update next year guidance at this point, but we're feeling very good about the program for bringing on board. We'll start executing those programs and the timing issues, the chance that we have will be behind us. Tycho Peterson: Okay. Thank you. Operator: Thank you. Our next question comes from the line of Dan Arias with Stifel. Your line is open. Please go ahead. Dan Arias: Good morning, guys. Thanks for the questions. Sean, I want to just ask a couple on a few of the partnerships. On the Astellas partnership that you've mentioned any insight into the discovery work that you guys are doing with them and the prospects that they might have for advancing to preclinical with you guys. And then relatedly advancing the preclinical program to the clinical program? And then that's -- so that's one. And then the second one we should be on PhaseBio. Obviously, we don't know exactly what drug you're working on with them but if we were to sort of take a stab and assume it was Bentracimab, would that -- I think that would make the timeline something like mid 2022 for a BLA filing. If that were to happen, would that make royalties in 2023 a decent assumption? Sean McClain: Yes I'll start with the PhaseBio question first, Dan. So given that we can't disclose what asset we're working on, we can't opine on that at the current moment. PhaseBio is in a much better position to answer that question of that at this point in time. And regarding Astellas, it is a molecule optimization discovery program and it's not de novo drug discovery. So they had given us a molecule to optimize for them. And in regards to preclinical development and taken it into the clinic, again, we cannot opine that at the current moment, but I will say that the program is progressing well. Dan Arias: Okay. If I could just sort of ask a follow up on PhaseBio. I think the idea by once you get past to BLA, they will go from using another provider to you guys in terms of in terms of producing the active compound. Do you have a sense for the timing that might transpire with respect to that, in other words that quickly after you see the BLA, success with BLA, is there an evaluation period down the road do you think needs to take place? I'm just sort of trying to understand the cadence of the events that would just sort of lead you to evidence of the progress that you guys are making with some of these really good partnerships. Sean McClain: Yes. With progressing to the BLA and then you know implementing after post BLA, amendment again, PhaseBio would be the party to opine on that, and from a regulatory standpoint what needs to be done as well. Dan Arias: Okay. I understand I'm asking questions that are hard to answer so thanks for indulging me on that. Just last one for maybe for Greg on the pipeline and the mix of the early and the late stage negotiations that you have there. I think the plan earlier this year was for the pipeline to be skewed toward discovery projects. Is that still true and when you look at 2022 and to some of the comments that you made before, do you think that you see the mix shift toward discovery more in terms of signed deals next year? Greg Schiffman: I would say yes. I mean, this year three of the five deals that we -- indicated was our goal this year will be a discovery deal. And the last three that we will look to find are all discovery deals. And if we continue to follow that trend I would say it would be heavily biased to discovery deals next year, and I think that's our assumption based on the discussions and feedback we're getting from the partners we're having dialogues with. Sean McClain: I would say the markets very excited about our discovery platform. And just to clarify the discovery programs do include the cell line developments so discovering the molecule as well as the cell line development. And as Greg noted, a majority of the pipeline that we currently have is discovery, and we're very excited about again how the marketplace has been receiving and our discovery platform. Dan Arias: Okay. Thank you guys. Operator: Thank you. And our next question comes from the line of Max Masucci with Cowen and Company. Your line is open. Please go ahead. Max Masucci: Hi, thanks for taking the questions. So the pace of hiring continues a fast clip. They give 146 new hires this year. Whereas the recent hires then focus, is it more toward the four initiatives in R&D or more on the commercial side. Looks like SG&A came in a bit above our expectations in Q3. And then within the commercial organization, do you see more of the near-term low-hanging fruit coming in the form of expanding your presence within existing customer or finding new customers? Greg Schiffman: Sure. Let me have a discussion around the cost and then let Matthew or Sean talk about the second one. The majority of the headcount that we are bringing on board is associated with our lab and operations group. The SG&A was above expectations for the quarter, but a large portion of that was associated with non-stock compensation, which there was a lot of uncertainty exactly what any of that would be when we were thinking about that prior to an IPO, and we had $3 million of the $9 million was associated just with that cost. Many you had about $2 million associated with recruiting and public company costs coming on board. And so the headcount itself and the expenses that we have really have been growing in the lab operations, its skills enabling us to be able to do to some of the discovery work and that's what we're bringing some additional talent on board. We do expect that to continue to grow in Q4 but moderate substantially next year. We will build out an infrastructure that could execute on far more deals than we are executing on today. And at this point in time, I feel really good about what our ability to attract the talent that we brought on board, what it's enabling us to do and have positioned us to go forward. But we would expect to see a lot of the work that we're investing in today, which is building out some of the infrastructure capability moving over into operations. Sean McClain: And I will say that in regards to the AI and data sciences team, we've expanded that team as well and really recruited world class AI talent, which is extremely difficult to find no matter where you're at. And I would say that we've done a very good job of attracting that talent. And the reason because of the data that we have that no one else has access to. The billions of different data points on drug functionality and manufacturer ability, which again has led us to attract this top AI talent along with top biologists and send bio experts in the world. Max Masucci: Great. And then just on the commercial side. Just curious you know where the focus is no more square. Is it more in the same customer expansion or winning new customers? Sean McClain: Yes. So are our existing partnerships are really key for us expanding into the future. So we see growth within our existing partners signing new multi program deals, but then also attracting new partners just like we saw with EQRx about our multi program, multi target sorts of partnerships moving forward. But both are important to us. But the trend that we're seeing is that the fact that we're signing these multi program deals with one partner. Max Masucci: That makes sense. Then if understanding you, you can't go into deep into any specifics, but if you look at the nine total active programs, most being in earlier stages. If you think about the timelines and your technology or what to enable for partners compared to a conventional approach, does late 2023 or 2024 sound like a more reasonable time when we could start to see a more smoothing out of programs that are approaching or triggering pre commercial milestone payments, just another question well into visibility. Greg Schiffman: Yes. I think you know first and that's when I want to highlight that we have no specific information from any partner that shares with us the exact details of their clinical programs and where they're at. And so really just based upon interactions that we have and what you traditionally see in a clinical program, but I think the timing for that is probably appropriate when we look at where we are in the early stage programs. And we tend to think it's 10-year time period from that start to where you typically see a therapeutic move through to eventual approval. And again, those are just typical timelines. We don't have any specific insights we will get that insight probably at the same time that you do when we start seeing the programs being publicly announced in terms of the clinical programs. And we know that we're being used in that program. Max Masucci: Great. Thanks for taking the questions. Operator: Thank you. And our next question comes from the line of Michael Ryskin with Bank of America. Your line is open. Please go ahead. Michael Ryskin: Great. Thanks. Just a couple of quick ones for me. One on the five programs target for 2020. I just want to be clear. Would EQRx count as one of those or potentially multiple if you're talking about multiple targets -- just want to clarify-- programs versus deals, sort of how you talk to those KPIs. Greg Schiffman: So EQRx is a multiple program and said it would be more than one. I think from that standpoint, that's probably how we would think of it. We're very confident we will be achieving the five this year. I think Sean indicated that in his comments earlier in the call. And at this point, we feel we're well positioned to hit that goal. Michael Ryskin: Okay. Great. And then just another point sort of on future pipeline. Obviously not getting the specifics, but maybe you could talk about potential programs starts next year. How do you think about visibility? Could you just talk us through what the pipeline is there in terms of additional programs with other partners? How long those conversations take and so you get something signed three months, six months? Just walk us through the process and what happens is you build that backlog for next year and the year beyond. Greg Schiffman: Let me just maybe give an intro and then I'll turn it over to Sean. One of them, we've been building that backlog over the past four or five months. We brought it on and have expanded our business development group that's working with the partners bringing on the deal. We've seen now the EQRx deal closed. We've got others that are getting -- we believe very close to signing. And you really have a pipeline that you've started to build up that will continue, and so from that standpoint where we had a little bit of a lag on signing a few deal, it really would that shift going from cell line development to discovery. But you've been building up a partner up a pipeline beyond just the couple that were in the deal that we announced to an EQRx that the others that are about to be signed with is a pipeline going toward next year already been established. And then I'll turn over to Sean. Sean McClain: Yes. We've got a really strong pipeline right now especially on the discovery programs and with the IPO that continued to give us credibility, being able to close and press release EQRx. It just continues to build out our credibility and drive our pipeline within the marketplace. And so going into next year, it's an extremely robust pipeline that we're really excited about. But as you indicated, it does take time to build that and that's what we've been doing is really building that and leading us to have a really strong 2022. Michael Ryskin: Great. Thanks so much. Operator: Thank you. . And I'm showing no further questions, and I'd like to turn the conference back over to Sean for any further remarks. Sean McClain: Thank you. Out outside, we have experienced significant achievement this year creating and integrating new technologies to drive our business opportunities. We have also had success in recruiting and building a world class team of unlimiters, raising the needed capital to allow us to execute on our stated objectives and building out and moving to a terrific new campus. And all of this was accomplished while executing on our partnerships and signing our first major multi program discovery deal. And we are confident in our ability to in this year having hit our goal for the number of new programs we set forth. Before closing, I want to acknowledge and thank our team at Absi for their limitless dedication and extraordinary work this year. And I'm excited for what the future holds. We look forward to continuing to engage in dialogue with you all. And as a reminder we'll be presenting at the Credit Suisse Healthcare Conference later today and the Stifel Healthcare Conference next week. Thank you all for listening, and we look forward to speaking to you all again. Operator: This concludes today’s conference call. Thank you for participating. You may now disconnect. Everyone have a great day.ABSI Ratings Summary
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Absci Corporation Reports 2021 Results, Announces NVIDIA Partnership
Analysts at Berenberg Bank provided their views on Absci Corporation (NASDAQ:ABSI) following the company’s released 2021 results. Given the company is still in the early stages of scaling its portfolio of both discovery and cell line development (CLD) programs, the analysts believe their revenue estimates are conservative in the near term.
2021 and early 2022 saw the adoption of the company’s newly commercialized discovery capabilities and the execution of five new active programs in 2021, as previously guided. On the back of early adoption of the company’s discovery applications and its new NVIDIA collaboration to scale its own AI capabilities, the analysts maintain their $28 price target and Buy rating.
During NVIDIA’s GTC conference yesterday, the company announced its new partnership with NVIDIA, through which it will leverage NVIDIA’s computational power to scale its own AI models for therapeutic protein design and optimization.
