Predictive Oncology Inc. (NASDAQ:POAI) Q1 2024 Earnings Call Transcript

Predictive Oncology Inc. (NASDAQ:POAI) Q1 2024 Earnings Call Transcript May 15, 2024

Operator: Ladies and gentlemen, good morning, and thank you for standing by. Welcome to the Predictive Oncology Q1 2024 Earnings Conference Call. At this time, all participants are in a listen-only mode. After the speakers’ presentation, there will be an opportunity to ask your questions. Please be advised that today’s conference is being recorded. And I would now like to hand the conference over to your speaker, Mr. Glenn Garmont, Investor Relations. Mr. Garmont, please go ahead.

Glenn Garmont: Welcome, and thank you, everyone, for dialing in to the Predictive Oncology First Quarter 2024 Financial Results Call. First, you’ll hear from our Chief Executive Officer and Chairman of the Board, Raymond Vennare. Then our Chief Financial Officer, Josh Blacher, will review our financials. 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 the 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 future performance may differ materially 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 Vennare, Chief Executive Officer. Raymond?

Raymond Vennare: Thank you, Glenn, and good morning, everyone. Thank you for joining us today. I would like to begin this morning with an update on a truly groundbreaking study that we recently completed with UPMC Magee-Womens Hospital in Pittsburgh. This was a retrospective multiyear study to determine if we could leverage our artificial intelligence capabilities to build multi-omic machine learning models that would be better than clinical data alone in predicting both short- and long-term survival outcomes among ovarian cancer patients. Ovarian cancer represents a significant unmet need in oncology with epithelial ovarian cancer being the deadliest of all gynecologic malignancies. While these cancers are sensitive to frontline chemotherapy in approximately 75% of the cases, these women will ultimately experience disease relapse in an equal percentage, which is incurable.

Outside of primary chemotherapy, there is no universal treatment decision path to determine the agent, sequence and timing of the standard of care for chemotherapy agents. The Magee study was designed to identify key features that drive overall survival endpoints. It included data from 235 ovarian cancer patients from 2010 through 2016, a broad array of inputs, including patient data, whole exome sequencing, whole transcriptome sequencing, drug response profile and digital pathology profiles were used to train the 160 models that we included in the study. We are very pleased to report that we were able to deliver strong predictive models with high levels of accuracy and our machine learning capabilities demonstrated the ability to identify prognostic subgroups within an ovarian cancer patient population.

Q&A Session

Further validating the significance of these study results, we announced a few weeks ago that an abstract detailing the study has been accepted for presentation at the very prestigious American Society of Clinical Oncology Annual Meeting, better known as ASCO, which is being held May 31 through June 4 in Chicago. The presentation, which will be delivered by Dr. Brian Orr, gynecologic oncologist at the Hollings Cancer Center, Assistant Professor at the Medical University of South Carolina and lead investigator of the study is scheduled for Monday, June 3rd at 9 a.m. Central Time. As we stated last quarter, the potential implications for the Magee and other clinical decision-makers are significant as these models can be used as an important decision support tool to better tailor therapies to individual patients and positively affect overall survival.

The implications for Predictive Oncology extend beyond that, however, we believe there are many opportunities to utilize this information for purposes other than clinical utility. The possibility does exist to leverage these data to develop digital pathology applications and new predictive models for other cancer types. And other such application would be to drive the design of more efficient and effective clinical trials. Also, with the ability to identify novel biomarkers that are correlated with survival, we can leverage this information to become more directly involved in drug discovery itself in addition to acting as a partner to others to expedite drug discovery. This has formed in my vision, as you know, for the company. The successful results of this ovarian cancer study not only clinically validate our ability to successfully predict outcomes, they serve as a sort of proof-of-concept that supports further work towards that goal.

With these compelling results in hand, we are accelerating our drug rescue, drug repurposing and drug combination initiatives and more fully leveraging our artificial intelligence, machine learning and wet lab capabilities to evaluate the drug response of hundreds of diverse patient tumors against hundreds of drugs in a fraction of the time and at a fraction of the loss of valuable samples. Turning now to another recent development. Last month, we announced the collaboration with Fujifilm to co-market our EndoPrep sample treatment technology, together with Fujifilm’s PYROSTAR bacterial endotoxin detection reagent to reduce protein interference and bacterial endotoxin testing of biopharmaceutical products. For those interested in learning more, the first joint webinar will be held on Wednesday, May 29, at 10:00 a.m. Eastern Time.

Endotoxins also known as lipopolysaccharides LPS are components of the outer cell membrane of gram-negative bacteria and are released when intact bacteria are disrupted. Sub-nanogram levels of endotoxins can trigger immune responses such as inflammation and fever in patients, even leading to systemic shock and death. Endotoxins are highly resistant to sterilization processes and accurate detection and removal of endotoxins in biopharmaceuticals are required before entering animal trials or human clinical trials. PYROSTAR is widely considered to be the best detection system for measuring endotoxin levels in biologic products. When paired with EndoPrep, they can accurately detect residual endotoxins in the presence of interfering glucans and reduced interference of most biologic products with detection assay.

In a proof-of-concept study, we achieved reproducible and accurate measurements of endotoxin in the presence of specific interfering proteins in biologics. The study results indicate that three or four tested biologics went from not failing in the 50% to 200% detection of challenge endotoxin to falling in the 50% to 200% detection range as required by the FDA for clinical testing. In addition to demonstrating the versatility of our biologics technology, this collaboration will allow Predictive Oncology to make a significant positive impact on drug safety. We are very pleased to have the opportunity to work with Fujifilm on this project as they are a clear industry leader in the development of endotoxin solutions for injectable pharmaceuticals and biological products.

We also announced recently that we are making meaningful progress with FluGen in the development of a first-of-its-kind intranasal flu vaccine. This project is part of a $6.2 million Phase 2b grant awarded by the United States Department of Defense. Pursuant to this agreement, we are utilizing our formulations expertise to help FluGen develop its M2SR vaccine that is soluble and stable in a refrigerated state, which is a vital part in the drug development process. Most importantly, this would also address the need for a longer vaccine shelf life to support global distribution, including remote locations. Unlike the standard of care flu vaccines, M2SR stimulates mucosal, humeral and cellular immunity. In an unprecedented challenge trial, M2SR demonstrated protection against infection and illness across seven years of virus DRiPs, and M2SR induces a durable antibody response with potential to cover an entire flu season beyond.

M2SR also has shown activity as a vaccine vector for other respiratory vaccines in infectious diseases, including a COVID-19 flu combination. With our proprietary HSC technology and artificial intelligence platform that efficiently analyzes more than 4,000 different drug formulation combinations using FDA-approved excipients, we are able to find the optimal formulation tailored to the final product’s application in only three to six months using as little as 20 micrograms of protein. Our novel design of experiments is a critical component currently being utilized for the development of FluGen’s flu vaccine. This is exactly the kind of innovation that we strive to be part of, and we look forward to the continued development of this groundbreaking advancement in the vaccine field.

Moreover, as I mentioned in our last update, we have recently announced the development of our latest stem cell technology breakthrough, a novel protein expression method for G protein-coupled receptors, GPCRs, and other membrane protein classes. This capability supports drug discovery for a variety of diseases, including aggressive cancers. Turning now to other collaborations we have discussed in the past. Let me give you a brief update on Cvergenx as well as the most recent submission to the center for the advancement of science and space. You may recall that last February, we announced the collaboration with Cvergenx to develop the first ever genomics-based approach to precision radiation therapy and drug discovery using artificial intelligence.

The objective of this collaboration is to leverage and maximize the combined power of Predictive Oncology’s expertise in artificial intelligence and Cvergenx’s proficiency in biomarker development to identify novel radioprotector and radiosensitizer drugs. Over the past year, we have made significant progress, having now evaluated trained or developed models to predict changes in radio sensitivity for more than 3,000 different drug exposures as well as using well-established gene expression databases. These findings form the basis of an NIH SBIR Phase 1 grant to screen vast libraries of compounds to accelerate the potential development of drugs, drug combinations or repurpose drugs, sensitize or protect human subjects from the effects of radiation.

The significance of identifying of these radiosensitizers and radioprotectors extends well beyond drug repurposing, however. Using these models, for example, we would be able to proactively screen workers in the nuclear energy industry and military and in the clinical setting, optimize the planning and treatment of patients receiving radiotherapy. So our work with Cvergenx has potentially broad utility across a number of important applications. And in the process, we have been able to expand those data sets, which may be leveraged in several important ways with respect to commercialization. First, to screen individuals for radiation sensitivity or resistance to optimize the clinical effect of radiotherapy. Second, to screen for interactions between sensitive or resistant patient tumor samples and therapeutic compounds.

And third, to identify combined or developed novel or repurpose radioprotective or radiosensitizing drugs. These are not isolated developments, with synergistic activities that have created new and more interesting opportunities, which has led to collaborations with Merck & Company, OCMS and Redwire Space. And now I would like to turn this call over to Josh Blacher, our Chief Financial Officer. Josh?

Josh Blacher: Thank you, Raymond. We concluded the first quarter of 2024 with $5.2 million in cash and cash equivalents compared to $8.7 million as of December 31, 2023, and $4.0 million in stockholders’ equity compared to $8.3 million as of December 31, 2023. In April, we established a new at-the-market ATM financing vehicle, which will allow us to sell common shares from time to time. Our current dollar value to pass through the ATM is over $3.5 million. Our net loss per share for the first quarter of 2024 was $1.04 per basic and diluted share as compared to $0.86 per basic and diluted share for the first quarter of 2023. The company recorded revenues of $420,000 for the first quarter of 2024 compared to $240,000 for the comparable period in 2023.

Revenues for the quarter ended March 31, 2024 and March 31, 2023, were primarily derived from the company’s Eagan operating segment, which contributed revenues of $404,000 and $216,000 for the quarters ended March 31, 2024, and 2023, respectively. General and administrative expenses primarily consist of management salaries, professional fees, consulting fees, administrative fees and general office expenses. G&A expenses increased by $291,000 to $2.6 million in the three months ended March 31, 2024, compared to $2.3 million in the comparable period in 2023. The increase was primarily due to increased professional fees, including audit and consultant fees, as well as increased business factors, offset by decreased employee compensation as well as decreased depreciation due to fully depreciated assets.

Operating expenses primarily consist of expenses related to product development and prototyping and testing. Operations expenses increased by $224,000 to $1.1 million in the three months ended March 31, 2024, compared to $879,000 in the comparable period in 2023. The increase was primarily due to increased employee compensation associated with our research and development efforts. Sales and the marketing expenses consist of expenses required to market and sell our products, including staff-related expenses for individuals performing at work. Sales and marketing expenses increased by $369,000 to $740,000 in the three months ended March 31, 2024, compared to $370,000 in the comparable period in 2023. The increase was primarily related to severance related to a former executive.

Net cash used in operating activities was $3.4 million for the first quarter of 2024, roughly flat with cash used of $3.4 million for the comparable period in 2023. The company incurred net losses of $4.2 million and $3.4 million for the quarters ended March 31, 2024 and March 31, 2023, respectively. As of March 31, 2024, the company had an accumulated deficit of $172 million as compared to $168 million as of December 31, 2023. That concludes the financial overview. We will now open the call for questions. Operator?

Operator:

Raymond Vennare: Thank you very much, everyone. I just wanted to again say that we are very pleased with our progress, with the new developments that we’ve been able to initiate over the last few months. We appreciate your ongoing support, and we look forward to our next update in the next quarter. Thank you very much.

Operator: Thank you. The conference of Predictive Oncology has now concluded. Thank you for your participation. You may now disconnect your lines.