Predictive Oncology Inc.

Good day, and thank you for standing by. Welcome to the Predictive Oncology Q2 2023 Earnings Conference Call. At this time, all participants are in a listen-only mode. After the speaker presentation, there will be an opportunity to ask your questions. Please be advised that today's conference is being recorded. And I now would like to turn the conference over to your speaker, Mr. Glenn Garmont. investor relations. Mr. Garmont, please go ahead.

Welcome and thank you, everyone, for dialing into the Predictive Oncology second quarter 2023 earnings call. First, you'll hear from our chief executive officer and chairman of the board, Raymond Venari. Then our chief financial officer, Bob Myers, will review our financials. Finally, Dr. Pamela Bush, our chief business officer, will join Raymond and Bob to answer any questions that you may have. Certain matters discussed on this call contain forward-looking statements. These forward-looking statements reflect our current expectations and projections about future events and are subject to substantial risks, uncertainties and assumptions about our operations and the investments we make. All statements other than statements of historical facts included in this call regarding our strategy, future operations, future financial position, future revenue and financial performance, projected costs, prospects, plans and objectives of management are forward-looking statements. The words anticipate, believe, estimate, expect, intend, may, plan, would, target and similar expressions are intended to identify forward-looking statements although not all forward-looking statements contain these identifying words. Our actual performance, future performance, may materially differ from that contemplated by the forward-looking statements as a result of a variety of factors, including, among other things, factors discussed under the heading risk factors in our filings with the SEC. Except as expressly required by law, the company disclaims any intent or obligation to update these forward-looking statements. And now I'd like to turn the call over to Raymond Vernari, Chief Executive Officer. Raymond?

Thank you, Glenn, and good afternoon, everyone. During the second quarter of this year, we continued to make significant progress in growing our pipeline with biotech and biopharma companies, as well as research institutions looking to incorporate artificial intelligence and machine learning into their early drug discovery process. The importance of our differentiating petal platform, which includes our vast proprietary biobank of more than 150,000 heterogeneous tumor samples and more than 200,000 pathology slides combined with our CLIA-certified pet lab is beginning to resonate in the market. We are the only AI-powered company capable of predicting clinical success in the very early stages of drug discovery and supporting those predictions with actual in-silico modeling and bench-level experimentation. This is only possible because we are able to introduce the human element of heterogeneity far earlier in the drug discovery process, essentially looking five years into the future of drug development in advance of clinical trials. As I have mentioned before, and for those unfamiliar with our company, the word heterogeneous is a key descriptor for predictive oncology. Even though many patients are diagnosed with the same type of cancer, each of those tumors respond differently to a particular cancer therapy. Each tumor and every response is unique. Understanding drug response in a heterogeneous population is invaluable along the entire continuum of drug discovery through drug development. Our unique combination of assets and capabilities offers drug developers a multifaceted value proposition that includes, first, the mitigation of clinical risk at the most critical stage of drug discovery. Second, by identifying and validating drug targets sooner and thereby avoiding unnecessary trials that are likely to fail later in development. The potential exists not only to significantly reduce the cost of drug discovery, but potentially to expand the drug development pipeline. And third, by accelerating early-stage discovery, replenishing pipeline, and optimizing clinical development, the commercial life of these drugs under patent exclusivity is extended and expanded. the emergence of AI is fundamentally changing how drugs are discovered and subsequently developed. And we are at the forefront of this exciting transformation. It is well known and generally accepted that approximately 95% of drug candidates are never approved. But with predictive oncology's capabilities, our partners essentially have the ability to look into the future of drug response and to confidently anticipate clinical validation with much lower financial risk and therefore a much greater likelihood of commercial success. The global artificial intelligence in drug discovery market was valued at $1.1 billion U.S. in 2022 and is expected to expand at a compound annual growth rate of 29.6% from 2023 to 2030. The growing demand for the discovery and development of novel drug therapies, a fresh approach to drug repurposing, and the need to replenish product pipeline as patents expire are the driving force behind this market growth. Again, with our highly differentiated portfolio of assets and capabilities, we believe that we are incredibly well positioned to occupy a leadership position in this emerging field. This year, for the first time, we had a very notable presence at the 2023 BIO International Convention, which was held in Boston in June. BIO, which stands for Biotechnology Innovation Organization, is among the most widely attended industry conferences in the world dedicated to partnering and business development within the life sciences. During the conference, our chief business officer, Dr. Pamela Bush, was invited to deliver a presentation on the importance of addressing patient heterogeneity in drug discovery, the advantage of introducing active machine learning into that process, which, as I just mentioned, is a key differentiator for us and an important component of the lab experiments that support or refute the predictions that come from PETL. Also, during the conference, we met with more than 30 customer prospects, several of which have led to substantive ongoing discussions. Annual conferences like BIO are critical to raising awareness of predictive oncology and unique value that we can deliver to our customers, and we will certainly be participating in additional industry-related events in the future. For example, since BIO, We are in active negotiations with a key European player in the formulation space to out-license our proprietary rapid formulation technology for use in a proscribed territory, which effectively would expand our reach into Western Europe. Those discussions are ongoing and a term sheet is now being drafted. Again, for the benefit of those who may be new to our story, At the core of our offering is our PETL platform. As we have said before, PETL is comprised of several interrelated components. It is the application of artificial intelligence as a tool that is directed by rigorous scientific experimentation conducted in our own laboratory, which is informed by the most significant resource at our disposal, which is a biobank of more than 150,000 tumor samples, and the drug response data derived from those samples.