Categories: News

Predictive Oncology Launches Website Highlighting AI-Powered Cancer Research Advancements

Predictive Oncology is leveraging AI to streamline drug discovery and development, improve outcomes in clinical testing and forge a new frontier of cancer research

MINNEAPOLIS, Oct. 19, 2021 (GLOBE NEWSWIRE) — Predictive Oncology, an oncology and cancer research company using big data and machine learning to improve pharmaceutical development and predictive treatment outcomes, launched a website today that emphasizes its role in advancing its mission.

The website features information about Predictive Oncology and its subsidiaries, Helomics, Soluble Biotech and TumorGenesis which are all integral to the overarching goal of eliminating cancer by predicting treatment outcomes and aiding in the development and optimization of cancer drugs.

“The website redesign is really intended to showcase the great work that all these teams have been doing, and emphasize what they’re all contributing to the same grand mission under the Predictive Oncology banner,” said J. Melville Engle, CEO and Chairman of the Board of Predictive Oncology. “Putting an end to cancer is a team effort. We need the analytical capabilities of Helomics and TumorGenesis to help expedite the development of new cancer treatments and we need the expertise of Soluble Biotech to optimize those treatments. Each is mission-critical to our end goal of equipping healthcare providers with what they need to take the fight to cancer and win.”

Here’s a closer look at each of Predictive Oncology’s subsidiaries and how they’re contributing to advancing cancer research and saving lives:

  • Helomics: Helomics maintains a database that includes information on 137 types of tumors and more than 15 years of treatment outcome data spanning more than 150,000 clinical cases. Helomics relies on proprietary artificial intelligence software, known as the Computational Research Engine (CoRE™), to analyze this rich set of data and personalize cancer therapies for patients. It can also help drive the development of new targeted therapies in collaborations with pharmaceutical companies, finding effective treatments more quickly and helping them get to clinical trials.
  • Soluble Biotech: Soluble Biotech is a provider of soluble and stable formulations for proteins including vaccines, antibodies, large and small proteins, and protein complexes. Soluble Biotech can help decrease the cost, time, and demand on resources conventionally needed to optimize formulations, cutting the average time down from one year to just three months.
  • TumorGenesis: TumorGenesis enables researchers to better study cancer cells found in tumors of the blood and all organ systems. TumorGenesis achieves this by growing cancer cells in the lab while retaining the unique DNA/RNA and proteomic signatures that would exist inside a patient’s body. In this way, TumorGenesis offers a granular view of the tumor — and the information needed to effectively treat the patient’s cancer. Currently, TumorGenesis is focused on studying ovarian cancer tumors, covering 25 ovarian cancer cell lines representing 90% of ovarian cancers.

“Eliminating cancer may seem like a lofty goal, and indeed such a complex disease isn’t going to be cured overnight,” said Engle. “But, with modern technology and the power of artificial intelligence, we have at our disposal some of the most potent tools to solve the challenges facing us in cancer research. Now that we can contextualize and cross-reference hundreds of thousands of case studies against detailed information about each and every tumor we have received, we can ensure our treatments are tailor-made to be most effective for each and every patient.”

About Predictive Oncology

Predictive Oncology Inc. (NASDAQ: POAI) is a knowledge-driven company focused on applying artificial intelligence (AI) to develop personalized cancer therapies, which can lead to more effective treatments and improved patient outcomes. Using artificial intelligence, Predictive Oncology utilizes a database of 150,000+ cancer tumors, categorized by patient type, against drug compounds to determine optimal therapies to be used to ultimately eliminate cancer.

As the drug discovery community realizes, a genomics-based approach to cancer research and drug development is insufficient to achieve the promise of personalized therapeutics. Predictive Oncology instead takes a multiomic approach, which considers the vast multitude of factors that make each cancer unique. Rather than operating based on the equivalent of a birds’ eye view, Predictive Oncology makes possible a more personalized and effective approach to cancer research and treatment.

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, 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.

Investor Relations Contact:

Landon Capital
Keith Pinder
(404) 995-6671
kpinder@landoncapital.net
Media Contact:
media@predictive-oncology.com

Staff

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