Executive Summary / Key Takeaways

• Predictive Oncology is strategically focused on leveraging its unique combination of artificial intelligence (AI), a vast proprietary biobank of over 150,000 tumor samples, and a CLIA-certified wet lab to accelerate and de-risk early-stage oncology drug discovery.
• Recent financial results for the core continuing operations show significant revenue growth in Q1 2025 ($110,310 vs. $4,858 in Q1 2024) driven by increased service delivery, alongside substantial reductions in operating expenses as the company streamlines its focus.
• The company has undergone significant restructuring, including the divestiture of non-core assets like the STREAMWAY business ($625,000 sale proceeds in Q1 2025) and consolidation of operations, expected to yield approximately $2.5 million in annual cash operating expense savings from Q4 2024.
• Despite promising technological validation (e.g., 92% prediction accuracy, UMich collaboration showing 73% predictions from 7% wet lab experiments) and strategic progress, the company faces significant liquidity challenges, recurring losses ($182.87M accumulated deficit as of March 31, 2025), and substantial doubt about its ability to continue as a going concern without significant additional funding.
• Key risks include the need for substantial capital, potential NASDAQ delisting due to stockholders equity non-compliance, and ongoing litigation following the terminated merger discussions with Renovaro (RENO).

Predictive Oncology's AI and Biobank Engine: Unlocking Value in Cancer Drug Discovery

Predictive Oncology Inc. (NASDAQ: POAI) is positioning itself at the intersection of artificial intelligence and oncology, aiming to revolutionize the notoriously challenging process of cancer drug discovery and development. At its core, the company is a knowledge-driven entity dedicated to applying AI and machine learning to identify optimal cancer therapies, ultimately striving for more effective treatments and improved patient outcomes. This mission is underpinned by a unique combination of assets: a proprietary biobank housing over 150,000 tumor samples, decades of longitudinal patient-specific drug response data, a CLIA-certified wet lab, and a growing repository of digitized pathology slides. These components form the foundation of the company's AI platform, known as PEDAL.

The drug discovery landscape, particularly in oncology, is fraught with high costs and high failure rates. Historically, a vast majority of drug candidates entering clinical trials never receive commercial approval, largely due to the complex and heterogeneous nature of tumors and patient responses. Predictive Oncology's strategic response to this challenge is to introduce patient and tumor heterogeneity into the earliest phases of drug development. By leveraging its extensive biobank and historical data, the PEDAL platform generates predictions on how tumors will respond to specific drug compounds. The company asserts that its scientifically validated platform can predict tumor response with 92% accuracy, supporting these in silico predictions with validated in vitro experiments in its wet lab. This capability is designed to provide drug developers with critical insights, enabling them to prioritize the most promising candidates and potentially save millions of dollars and years of development time by avoiding compounds predicted to fail.

The company's technological differentiation extends beyond its core PEDAL platform. Predictive Oncology has developed a novel organ-specific 3D cell culture technology designed to mimic the physiological environment of human tissue more closely than traditional 2D assays. This technology aims to preserve critical interactions between a tumor and its surroundings, leading to more robust predictions of clinical outcomes and optimizing candidate selection. Furthermore, the company's Biologics group developed a novel method for the expression and purification of G protein-coupled receptors (GPCRs) and other membrane proteins, important targets in drug discovery. This technology has led to collaborations and the filing of intellectual property, with potential for out-licensing. The company also possesses High Throughput Self-Interaction Chromatography (HSC) technology and an AI platform capable of analyzing over 4,000 different drug formulation combinations, enabling rapid identification of optimal solubility and stability conditions, as demonstrated in its collaboration with FluGen on a novel flu vaccine. This process can potentially find optimal formulations in 3-6 months using minimal protein material.

Predictive Oncology operates within a competitive landscape that includes larger, more established players as well as other AI-focused startups. Direct competitors like Tempus (TEMP), Foundation Medicine (part of Roche) (RHHBY), and Guardant Health (GH) offer AI-enabled data analytics, genomic profiling, and liquid biopsy services. While these competitors possess advantages in scale, market share (Tempus estimated 10-15% in AI analytics, Foundation Medicine 20-25% in genomic profiling, Guardant Health 15-20% in liquid biopsy), and financial health (Tempus and Guardant Health show higher revenue growth rates, Foundation Medicine benefits from Roche's robust margins), Predictive Oncology differentiates itself through its unique integrated asset base. The combination of a vast, diverse biobank of live tumor samples, extensive historical drug response data, and wet lab validation capabilities provides a level of real-world heterogeneity and empirical support that management believes is difficult for competitors to replicate. The company's 3D models are claimed to offer 20-30% greater accuracy in mimicking human tissue responses, a quantifiable advantage in predictive power, although potentially at higher operational costs per unit compared to more data-centric approaches. While POAI's financial metrics like gross margin (36.88% TTM) and operating margin (-736.26% TTM) currently lag behind competitors (Tempus est. 55% gross margin, Foundation Medicine est. 75% gross margin, Guardant Health est. 65% gross margin), its focus on niche innovation and cost management could improve these over time.

The company's strategic journey has involved significant restructuring to sharpen its focus on this core AI-driven oncology business. Following a shift in emphasis around 2017 and key acquisitions, the company implemented a new strategic vision in early 2023. This led to the reclassification of the former Birmingham (Biologics) and Eagan (STREAMWAY) operating segments as discontinued operations. The sale of the Eagan assets (Skyline Medical's STREAMWAY product line) to DeRoyal Industries, completed on March 14, 2025, for $625,000 plus assumed liabilities, was intended to allow the company to concentrate resources on its core AI capabilities. Similarly, the consolidation of the Birmingham operations into Pittsburgh, expected to be fully implemented in Q4 2024, is part of a strategic cost reduction initiative. This initiative is projected to reduce the run rate for cash used in operating activities by approximately $2.5 million annually, representing about 20% of the 2023 cash burn ($13.2 million). Management also anticipates continued savings in areas like cloud computing and marketing expenses.

Recent financial performance reflects this strategic pivot and ongoing operational adjustments. For the three months ended March 31, 2025, revenue from continuing operations saw a substantial increase to $110,310, compared to just $4,858 in the same period of 2024. This growth was primarily attributed to the completion of a tumor-specific 3D model project. Cost of sales also increased due to associated direct labor, but the gross profit margin improved significantly (59.1% in Q1 2025 vs. -361.8% in Q1 2024). Operating expenses for continuing operations decreased, with General and administrative expenses falling to $1.83 million (from $2.33 million), Operations, research and development expenses decreasing to $520,406 (from $630,085), and Sales and marketing expenses dropping sharply to $3,633 (from $608,710). These reductions were driven by lower headcount, decreased professional fees, and reduced marketing spend, partially offset by increased legal fees. The total operating loss from continuing operations improved to $2.29 million in Q1 2025, down from $3.58 million in Q1 2024.

Despite these operational improvements and revenue growth in the core segment, the company's financial position remains precarious. As of March 31, 2025, cash and cash equivalents from continuing operations stood at $3.09 million. While net cash used in operating activities from continuing operations decreased to $985,840 in Q1 2025 (from $2.71 million in Q1 2024), the company continues to burn cash. Cash flow was temporarily bolstered by financing activities, including proceeds from warrant exercises, a Registered Direct Offering ($545,004 gross), and a share issuance to Renovaro ($500,000), although the Renovaro payment was returned in April 2025 following the termination of merger discussions. Cash flow from discontinued operations provided $854,494 in Q1 2025, including the $625,000 from the Eagan asset sale. However, the company's accumulated deficit reached $182.87 million as of March 31, 2025, and it faces significant short-term obligations of $4.61 million and long-term operating lease liabilities of $1.41 million. Management explicitly states that substantial doubt exists about the company's ability to continue as a going concern within one year without raising significant additional capital. Potential financing alternatives, including equity or debt, could result in significant dilution for existing stockholders.

The outlook for Predictive Oncology is heavily dependent on its ability to secure necessary funding and translate its technological capabilities into consistent, high-value contracts and partnerships. Management anticipates more collaborations in the coming quarters. Recent achievements like the successful development of predictive models for previously untested natural compounds from the University of Michigan (showing 73% predictions from only 7% wet lab experiments) and positive results in drug repurposing initiatives highlight the potential of the platform. The expansion of the ChemoFx® assay into Europe and the US also represents a potential revenue stream that complements the core AI business by generating valuable data. However, the company must overcome significant hurdles, including regaining compliance with NASDAQ's minimum stockholders equity requirement to avoid delisting and managing the costs and potential distractions of the lawsuit filed by Renovaro.

Conclusion

Predictive Oncology is undergoing a critical transformation, shedding non-core assets and focusing intently on its differentiated AI-driven oncology drug discovery platform, underpinned by its unique biobank and wet lab capabilities. The recent increase in revenue from continuing operations and significant reductions in operating expenses signal progress in streamlining the business and executing on its strategic vision. Early results from collaborations and internal initiatives demonstrate the potential of the company's technology to accelerate drug discovery, identify biomarkers, and repurpose existing compounds, offering a compelling value proposition in a market desperate for more efficient approaches. However, the company's severe liquidity constraints, history of losses, and the explicit going concern risk represent substantial challenges that overshadow its operational and technological achievements. The ability to secure significant additional funding, successfully navigate competitive pressures, and convert promising collaborations into sustainable revenue streams will be paramount to the company's survival and its potential to deliver long-term value to investors. This remains a high-risk investment proposition tied directly to the successful execution of a focused strategy under significant financial duress.