Predictive Oncology Reports Promising Results in AI-Driven Drug Repurposing for Cancer Treatment

Predictive Oncology Reports Positive Results Utilizing Artificial Intelligence for Drug Repurposing - Predictive Oncology (NASDAQ:POAI)

Company successfully identified several abandoned or discontinued drugs for further testing and development in ovarian and other cancer types Creates significant business development opportunities with meaningful long-term commercial potential with large pharmaceutical companies PITTSBURGH, Feb. 18, 2025 (GLOBE NEWSWIRE) -- Predictive Oncology Inc. POAI, a leader in AI-driven drug discovery and biologics, today provided an update highlighting new successes with its drug repurposing initiative. Using publicly available datasets on drugs that have either been abandoned or discontinued by large pharmaceutical companies, Predictive Oncology has developed a registry of promising candidates that can potentially be repurposed for additional or alternative indications. By utilizing its proprietary artificial intelligence and machine learning platform and leveraging its vast biobank of primary tumor samples and decades of drug response data, Predictive identified select drug candidates with promising mechanisms of action for further clinical testing with an initial focus on ovarian, colon and breast cancer and subsequently identified candidates with potential efficacy in treating colon and ovarian cancer. "Early results show that by running our platform for just eight weeks, we were able to identify compounds for use in one or more tumor types," said Dr. Arlette Uihlein, Senior Vice President of Translational Medicine and Drug Discovery and Medical Director at Predictive Oncology. "By precisely measuring only 92 combinations of laboratory experiments on patient tumor samples, the predictive model was capable of making an additional 964 confident predictions, covering a total of 79% of all possible experiments." "Our active learning AI platform enabled us to efficiently and confidently predict an additional 10x the number of measured experiments, eliminating at least 18 months of wet lab testing and identifying two drugs as having very promising results for use in one or more tumor types. Both of these drugs outperformed a known standard of care drug used to treat colon cancer," Dr. Uihlein concluded. Specific examples of currently abandoned or discontinued drugs that Predictive evaluated for potential efficacy include: Drug A: Akt InhibitorDrug B: selective Aurora A InhibitorDrug C: selective PI3Kα InhibitorDrug D: HDAC1/3 InhibitorDrug E: VEGFR2/KDR InhibitorDrug F: PARP1/2 Inhibitor Leveraging the company's foundational proof of concept study, Predictive is also using its AI platform to identify a set of FDA-approved drugs for other cancers that show promising activity in ovarian cancer, the results of which will soon be made public. "Encouraged by the outcome of the Magee Study and ASCO presentation, which predicted short and long-term survival of ovarian cancer patents, we made a conscious decision to proactively investigate potential candidates for drug repurposing or reuse specifically for ovarian cancer," said Raymond Vennare, Chief Executive Officer of Predictive Oncology. "We continue to demonstrate that our high throughput screening approach using the live cell patient tumors in our biobank, coupled with our AI models, is able to identify drugs worthy of further consideration. The significance of these initial drug repurposing findings may lead to some very productive discussions with a range of potential drug development partners." Utilizing its artificial intelligence platform, the company believes that the ability to repurpose approved or abandoned drugs for additional indications represents a meaningful opportunity to deliver value by developing new therapies faster and cheaper than through traditional early drug discovery. A recent market report has projected that the market for repurposed drugs will grow to $51.8 billion by 2033, from $32.1 billion in 2023. (4.5% CAGR). About Predictive Oncology Predictive Oncology is on the cutting edge of the rapidly growing use of artificial intelligence and machine learning to expedite early drug discovery and enable drug development for the benefit of cancer patients worldwide. The company's scientifically validated AI platform, PEDAL, is able to predict with 92% accuracy if a tumor sample will respond to a certain drug compound, allowing for a more informed selection of drug/tumor type combinations for subsequent in-vitro testing. Together with the company's vast biobank of more than 150,000 assay-capable heterogenous human tumor samples, Predictive Oncology offers its academic and industry partners one of the industry's broadest AI-based drug discovery solutions, further complimented by its wholly owned CLIA laboratory facility. Predictive Oncology is headquartered in Pittsburgh, PA. Investor Relations Contact: Tim McCarthy LifeSci Advisors, LLC tim@lifesciadvisors.com Forward-Looking Statements: Certain matters discussed in this release 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 press release regarding our strategy, future operations, future financial position, future revenue and financial performance, projected costs, prospects, changes in management, 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 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. 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What's Going On With Predictive Oncology Shares Tuesday? - Predictive Oncology (NASDAQ:POAI)

Predictive Oncology, Inc. POAI stock is trading higher on Tuesday after the company reported results from utilizing artificial intelligence (AI) for drug repurposing. The Details: Predictive uses AI and machine learning in combination with its biobank of primary tumor samples and drug response data to select drug candidates for potential further clinical testing. The company is initially focusing its efforts on identifying drug candidates for treating ovarian, colon and breast cancer. The company said it decided to proactively explore drug repurposing candidates for ovarian cancer based on the survival predictions from the Magee Study and American Society of Clinical Oncology presentation. "Our active learning AI platform enabled us to efficiently and confidently predict an additional 10x the number of measured experiments, eliminating at least 18 months of wet lab testing and identifying two drugs as having very promising results for use in one or more tumor types. Both of these drugs outperformed a known standard of care drug used to treat colon cancer," said Dr. Arlette Uihlein, Senior Vice President of Translational Medicine and Drug Discovery and Medical Director at Predictive. A recent market report predicts the repurposed drug market will grow from $32.1 billion in 2023 to $51.8 billion by 2033, reflecting a 4.5% compound annual growth rate. See Also: Titanium Metal Company IperionX Secures New DoD Contract; Stock Jumps POAI Price Action: At the time of publication, Predictive shares are trading 10.5% higher at $1.79, according to data from Benzinga Pro. Image: This illustration was generated using artificial intelligence via Midjourney. POAIPredictive Oncology Inc$1.8011.1%WatchlistOverviewMarket News and Data brought to you by Benzinga APIs