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For more than 30 years, Cabling Installation & Maintenance has provided useful, practical information to professionals responsible for the specification, design, installation and management of structured cabling systems serving enterprise, data center and other environments. These professionals are challenged to stay informed of constantly evolving standards, system-design and installation approaches, product and system capabilities, technologies, as well as applications that rely on high-performance structured cabling systems. Our editors synthesize these complex issues into multiple information products. This portfolio of information products provides concrete detail that improves the efficiency of day-to-day operations, and equips cabling professionals with the perspective that enables strategic planning for networks’ optimum long-term performance.

Throughout our annual magazine, weekly email newsletters and 24/7/365 website, Cabling Installation & Maintenance digs into the essential topics our audience focuses on.

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Predictive Oncology Enters Biomarker Discovery Market After Successful Retrospective Ovarian Cancer Study Yields Compelling Results

Expands AI/ML driven offering to include novel oncology biomarker discovery to predict patient outcomes and drug response in oncology

Biomarker discovery market estimated by third party research to be $51.5 billion in 2024

PITTSBURGH, July 25, 2024 (GLOBE NEWSWIRE) -- Predictive Oncology Inc. (NASDAQ: POAI), a leader in AI-driven drug discovery and biologics, today announced that it is expanding its AI/ML driven drug discovery platform to pursue discovery of novel biomarkers that can be used to predict patient outcomes and drug response in oncology.

Predictive Oncology’s biomarker discovery initiative stems, in part, from results obtained in the retrospective ovarian cancer study with UPMC Magee-Womens Hospital, which were presented at the 2024 American Society of Clinical Oncology (ASCO) Annual Meeting. In that study, Predictive Oncology successfully developed muti-omic machine learning models that identified key features that could more accurately predict both short-term (two-year) and long-term (five-year) survival outcomes among ovarian cancer patients as compared to clinical data alone. Through this process, Predictive Oncology obtained and analyzed data that supports novel ovarian cancer biomarker discovery and development that will be further explored both independently and in partnership with biopharma companies.

“We have already demonstrated the capabilities of our active machine learning platform to selectively utilize our diverse patient samples preserved in our biobank to predict responses to drugs with a very high degree of accuracy,” said Arlette H. Uihlein, MD, SVP, Translational Medicine and Drug Discovery and Medical Director at Predictive Oncology. “We are now taking this one step further by applying state-of-the-art deep learning approaches for biomarker discovery related to both patient overall survival (OS) and drug response, which can be done with existing resources. Our platform enables us to apply deep learning to the correct patient cohorts and accelerate the initial stages of biomarker discovery.”

“We believe the identification of novel cancer biomarkers represents the next significant opportunity for the application of our platform, which leverages the substantial value inherent in the diversified patient samples and data that we possess, as well as additional potential revenue streams for our company. Our technology has broad applicability, including the development of a clinical decision support tool to screen for clinical trial enrollment, and to inform subsequent drug discovery and development,” stated Raymond Vennare, Chief Executive Officer of Predictive Oncology. “These capabilities extend well beyond ovarian cancer and can be used in the discovery of biomarkers for other cancer types as well, and we look forward to further validating these capabilities through development collaborations with leading biopharmaceutical partners and healthcare networks.”

The total biomarker discovery market is estimated by third party research to be $51.5 billion in 2024.1

Predictive Oncology also announced today the release of a new white paper that discusses its biomarker discovery capabilities in greater detail. The white paper can be accessed at:  https://predictive-oncology.com/blog/BiomarkerDiscovery.

About Predictive Oncology
Predictive Oncology is on the cutting edge of the rapidly growing use of artificial intelligence and machine learning to expedite early biomarker and 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 lab and GMP facilities. 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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1 Mordor Intelligence: https://www.mordorintelligence.com/industry-reports/biomarkers-market


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