ImmunoPrecise Antibodies Ltd.

good morning and thank you for standing by welcome to immuno precise antibodies first quarter fiscal 2023 earnings conference call also on the call with us today are jennifer bach chief executive executive officer brad mcconn chief financial officer ilsa rodink chief scientific officer and barry duplantis vice president of client relations before we get started remember some statements we make today may be considered forward looking statements for the purpose of applicable United States and Canadian securities laws. IPA cautions that these forward looking statements are subject to risks and uncertainties that could cause actual results to differ materially from those indicated in the forward looking statements. Additional information about these risks and uncertainties is included in our SEC filings. IPA undertakes no obligation to update these forward looking statements except as required by law. On today's conference call, non-GAAP financial measures may be used to help investors understand IPAs business performance. We refer current and potential investors to our forward-looking information section of its management's discussion and analysis issued today at www.cdar.com and on EDGAR at www.sec.gov. Following our prepared remarks, We'll answer analysts' and investors' submitted questions. So with that, I'll now turn the call over to Dr. Bass.

Great. Thank you, Julianne. Good morning, everyone, and thank you for joining us today. We are pleased to offer Q1 updates on the heels of our year-end results. And as we enter this fiscal year with aggressive strategic aims, many of which we'll share with you today. We remain highly confident in our ability to grow revenue through new and existing clients, novel high-value revenue streams, and importantly, the commercialization of disruptive AI-driven in-silico technologies offered through our newest subsidiary, BioStrand. Additionally, four of our potential best-in-class and first-in-class therapies from our internal pipeline are now positioned for active licensing with the aim of commercialization this fiscal year. Lastly, we simultaneously prepare the regulatory submission of IPAs for anti-SARS-CoV-2 antibody therapeutics, which have sailed through preclinical IND-enabling studies and remain the only first-generation therapy to retain efficacy against all tested variants of concern, including the most recently screened BA.2.75. with more details on that program to come on this call from Dr. Rodink. IPA employees and their directors are particularly excited about the opportunities emerging from our most recent acquisition, Biostrand. It's been exactly five months today since the closing of this transaction, and both teams have been working tirelessly at delineating what the initial outcomes of these two companies coming together could be. If what has come to fruition up to this point is indicative of the future, IPA is about to engage in a disruptive and game-changing path forward. BioStram proposes a truly transversal and universal solution based on technologies that apply to every studied species, any sequencing format for data generation, and any application domain. As many of you know, many years ago, BioStrand made a pivotal discovery by identifying underlying universal fingerprints at the core of the biosphere's amino acid and nucleotide space. Those fingerprints, termed HIFs, after the inventor's name, Derek Van Hifta, unlock meaning and insight through multiple omic dimensions analyzed concurrently. Impossible with other technologies, the task of computing in parallel is now achieved by this remarkable and elegantly coded and indexed platform that renders near instantaneous results. We believe this will revolutionize the antibody drug discovery and development market as it results in knowledge and insights that dramatically speed up parallel hypothesis generation, target identification, antibody discovery, antibody engineering, and drug ability profiling. Months, if not years, may be saved with razor sharp precision in the results generated. Therapeutic discovery is no longer just the purview of biologists. It's now interdisciplinary and heavily influenced by the fields of computational modeling and data science. Actionable data is the first prerequisite for making progress in the world of personalized medicine. of which the global market size is expected to reach 5.7 trillion U.S. dollars by 2030, and to expand at a CAGR of 11.6% from 2020 to 2030. The industry is being driven primarily by increasing prevalence of malignancies and genetic illnesses. Additionally, a massive influx of expenditures in R&D and healthcare IT is supporting industry expansion of these patient-tailored therapies. In order to create specialized treatment plans, fine-grained knowledge on disease mechanisms and stages is needed in combination with the identification and analysis of patient-specific biomarkers. Especially in cancer and unusual genetic illnesses, better outcomes are expected with more precise and personalized approaches to treatment. Now, that said, the sheer volume of available data and their multilayered nature, such as omics data or textual data and clinical data, have historically restricted data integration. In addition, these data are all stored in silos and in different formats, which further complicates valuable integration. As a result, readability has been quasi-law. and efforts are deployed in computer power instead of understanding what data actually is relevant to discovery of safe and effective therapies and personalized medicine. Lens AI from BioStrand data management successfully solves this problem and provides a hyperscalable solution, integrating multiple data layers at once. Lens AI proprietary technology turns unstructured big data into structured big data and allows for instantaneously actionable and computed data. All data is secure and an easy-to-use access system is in build-out. This will be the foundation for a highly sophisticated data management solution to help partners maximize large internal data links, which may have been accumulating for decades without being taken full advantage of. The depth and richness of these libraries remains to be explored and analyzed in a feedback loop process in order to continuously enrich our partners' programs and turn data storage, which is a sunk cost for them, into an asset. The unique offering of Lens AI Analysis Platform is to rapidly bridge the gap between sequence analysis, 3D protein structure information, and the knowledge hidden in the different text documents. all using proprietary HIFT fingerprints. We are pleased to announce that building further on the cornerstone of Lend AI technology, similar to our original HIFT fingerprints, we have now generated structural HIFT fingerprints, which are fully built, also indexed into the software, and are now operational. This opens up a whole gateway to even more complex and integrated analysis for what we believe will revolutionize the fields of antibody humanization, epitope prediction, biosimilar antibody generation, and epitope-peritope binding predictions. As may be becoming clear within the context of what we are sharing, one of the several powerful cornerstones of IPA is now connecting and integrating data, data science, and bioscience. We believe this will enable us to tackle, in the near future, discovery challenges not previously possible through in silico means. These disruptive capabilities are then supported by our exceptionally broad downstream antibody development capabilities to provide high quality products with exceptional speed in the process of taking a therapy from concept to clinic. We are very pleased to announce on this call that as of today, we've made tremendous progress on multiple in silico fronts. First, we have implemented powerful structural prediction capabilities. After a full implementation of DeepMind's AlphaFold on our servers, we indexed our recently completed structural HIF and then applied structural search capabilities to our workflow. This now enables us to navigate seamlessly the structural world of biology and to generate more specific structural predictions and insights, all based on our proprietary HIFT syntax and structural HIFT indexes. Recalling that in biology, structure equates to function, and that function is at the heart of every biological activity. This effectively means that we are able to search related functions coded in HIFT. Second, we have expanded our database extensively with antibody libraries, structural libraries, scientific literature, and the integration of TALIM's proprietary data lake derived from multi-species genome reference sequencing, structural crystallography, and functional metadata, all to improve and enrich analytical capabilities for both IPA and TALIM. Third and lastly, we've also evolved Lens AI into a self-adaptive feedback loop platform, where HIPs are continuously enriched with structural and functional metadata, accelerating time for discovery and supporting our world-class function-first B-cell platforms. Building on these recent advances, we've spent the past quarter generating multiple exciting case studies within Silico Validation, which are pending wet lab validations, with final results aimed at release this quarter. Based on these initial in-silico findings, we have garnered interest from partners on multiple high-value programs using our newest in-silico technology. This confirms that the industry is shifting toward in-silico development more than ever, and that the appetite for emerging and disruptive technologies is high. As high-value targets are increasingly complex, together with an ever-growing interest in discovering new targets, the industry needs new tools to alleviate the difficulty level to achieve success. Lens AI is unequivocally positioning itself as a powerful and unparalleled, fully integrated in silico and wet lab engine. While we won't be sharing any of our in silico validated case studies under in vitro review until later this quarter, we are happy to share one of our case studies that we produced since past April. This one with the aim of analyzing a blockbuster monoclonal antibody that had been sponsored by a top 10 pharma that was deemed a commercial success, but for which adverse events emerged and were occasionally fatal. Our objective was to determine why the antibody under review had elicited undesirable adverse events in patients, as well as to determine if our lens AI could have predicted these complications, possibly even preventing fatality. For anonymity, as we are preparing to share the final result with the sponsoring pharmaceutical company, we'll simply call the antibody of interest antibody X. So as an example of one of our earlier case studies, antibody X is a commercial stage anti-cytokine antibody used in the treatment of a wide variety of inflammatory conditions such as rheumatoid arthritis, Crohn's disease, and ankylosing spondylitis. By using HIF-transcribed omics sequence data and a binding prediction algorithm, we identified what we believe to be a common binding site between antibody X and the fungus Aspergillus. We then applied our bottom-up NLP approach for scientific literature analysis to extract multiple biomedical reports, which pointed to a link between antibody X treatments and allergic bronchopulmonary aspergillosis, an exaggerated response of the immune system to the fungus aspergillus. Our Lens AI software indicated the following. Antibody X was capable of binding to aspergillus, and was causing severe allergic reactions in some patients who had been treated with the antibody. This novel interaction could have been predicted using Biostrand's holistic multi-species approach, which would have helped prevent the adverse events by allowing the sponsor to preclude patients with previous aspergillus infection from both the clinical trials and also from post-trial treatments. This case study represents only a small portion of the clinically relevant breakthroughs that we believe Lens AI is capable of solving. The in silico case studies currently undergoing wet lab validation are focused on demonstrating the ability of HIF fingerprints to rapidly revolutionize the fields of antibody humanization, transgenic animal usage, biosimilar discovery and development, in silico identification of antibody functions, and much more. As a result, we believe our Lens AI software combined with our broad wet lab capabilities will ultimately disrupt multiple industries in a relatively near future. With that, I'll go ahead and turn things over to Dr. Barry Duplantis, Vice President of Client Relations.

Thank you, Jennifer. We will now start with the performance review of our CRO business. When comparing this quarter to the same period last year, the company's project revenue has been quite consistent. However, we have noted several highlights that indicate growth as we look to the future. Firstly, discovery-based sales orders, which are signed commitments of future work, are up at our Canadian site by 67.5% and 18% globally. While this is a very promising metric, we do like to remind those listening that based on program timelines, IPA will be recognizing this revenue as over a period of 0 to 10 months. Secondly, the number of multi-phase discovery project starts, including our B-cell select, phased display, and hybridoma platforms, are up 125% at our Canadian site and 100% globally. The primary driver for both sales orders and project starts can be attributed to an increased demand for IPA's Rabbit B-cell platform. IPA began a sales and marketing push in the beginning of Q4 last year, targeting the therapeutic companion market. Therapeutic companion antibodies are critical and necessary reagents required to bring a therapeutic drug to market. The combination of IPA's function-first B-cell select workflow and the untapped potential of the rabbit's immune system produces highly selective, high-density antibodies that provide our clients with a best-in-class solution to complete a critical piece of the therapeutic equation. Thirdly, IPA has just completed the onboarding of another major pharmaceutical company, meaning that IPA now has had a contract service-based relationship with 80% of the globe's top 20 pharmaceutical companies. Finally, IPA has begun to see an increased impact from hedge fund-backed virtual biotherapeutic companies that lack or are very limited in wet lab facilities and capabilities and are often headed by researchers that have had previous experience with IPA's team and services while serving in past position at other IPA client companies. An example of this impact is represented by the fact that in this past quarter, two of IPA's top five revenue generating clients operate with less than 10 employees. This contrasts with zero of our top five clients from Q1 a year ago. While IPA is always developing and expanding relationships with major pharmaceutical companies, we expect to see and will actively pursue an increase in partnerships with small, fully virtual companies. These companies can be more agile, they have substantially lower operating costs, often have significant budgets, and seek to leverage the expertise and platforms of CROs to succeed and meet their objectives within the constraints of the current global financial environment. With that final update, I'm going to turn things over to Ilsa.