Predictive Oncology Announces Planned European Launch of its ChemoFx® Treatment Selection Marker and Tumor Profiling Assay

Initial plans target European clinical trials while providing standard testing to clinicians for individual patients

There are an estimated 250,000 gynecologic cancers diagnosed annually across Europe

PITTSBURGH, Jan. 16, 2025 (GLOBE NEWSWIRE) -- Predictive Oncology Inc. (NASDAQ: POAI), a leader in AI-driven drug discovery, today announced plans to launch its validated flagship live cell ChemoFx® drug response assay in Europe and expanded availability in the United States. The ChemoFx® treatment selection marker and tumor profiling assay will initially focus on ovarian and other gynecological cancers and may include testing of other major tumor types of interest over time.

The ChemoFx® drug response assay is a treatment selection marker for chemotherapies that quantifies an individual cancer patients’ in vitro tumor response to various chemotherapeutic agents.

“The drug response results are critical to Predictive Oncology’s live tumor cell platform that uses AI to create predictive models of drug response to streamline and de-risk the drug discovery process,” said Dr. Arlette Uihlein, Senior Vice President of Translational Medicine and Medical Director. “Data sets extracted from these models can be applied to clinical trial design as well as biomarker discovery and companion diagnostic development efforts.”

According to the American Cancer Society, nearly 115,000 new gynecological cancer cases are diagnosed in the United States each year with more than 34,000 deaths attributed to these cancers. In Europe, an estimated 250,000 gynecologic cancer cases are diagnosed each year, the most frequent of which are endometrial, cervical and ovarian.

“Of the approximately 150,000 live cell tumor samples that Predictive has in its biobank, nearly half of those specimens are gynecological cancers, and half of those are ovarian,” said Raymond Vennare, Chief Executive officer of Predictive Oncology. “Our artificial intelligence and machine learning platform was validated against 175 FDA-approved drugs and 130 primary samples from ovarian tumors, and the use of those same data sets to build multi-omic models to predict short and long-term survival in ovarian cancer patients speaks for itself.”

By testing multiple chemotherapies on a patients’ cancer cells before treatment selection, the drug response assay helps determine which chemotherapies are more likely to be effective on the tumor and which are less likely to provide benefit to the patient.

Mr. Vennare added, “While much can be said about the significance of our biobank for drug discovery, ChemoFx® not only represents an equally crucial asset for the personalized treatment and care of cancer patients, the development of AI-driven clinical decision support tools in oncology. Both opportunities come with the potential to generate significant short-term revenue and long-term gains. When first developed and introduced to the market, ChemoFx® generated gross revenues in excess of $25 million annually.”

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 proprietary AI/ML platform has been scientifically validated 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. 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 facilities. Predictive Oncology is headquartered in Pittsburgh, PA. 

Contacts:

For Predictive Oncology (investors):

Tim McCarthy  

LifeSci Advisors, LLC  

Forward-Looking Statements: 

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