Predictive Oncology Inc. (NASDAQ: POAI) Subsidiary Helomics

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Predictive Oncology Inc. (NASDAQ: POAI) Subsidiary Helomics Continues Progress Toward AI-Driven Predictive Model of Ovarian Cancer

- POAI’s Helomics division progresses toward critical milestone in CancerQuest2020 initiative
- Predictive models immensely valuable to pharmaceutical industry, improving drug evaluation without incurring high laboratory costs
- POAI is bringing precision medicine to the treatment of cancer for patients of today and tomorrow

Predictive Oncology Inc. (NASDAQ: POAI), a knowledge-driven company focused on applying artificial intelligence (AI) to personalized medicine and drug discovery, today announced continued progress by its Helomics subsidiary toward the goal of developing an AI-driven predictive model of ovarian cancer. This achievement will be a key milestone for the company’s CancerQuest2020 initiative (http://nnw.fm/W2TJb).

CancerQuest2020 is focused on building an AI-driven model of ovarian cancer that will predict drug response and outcome leveraging Helomics’ huge knowledge base of tumor profiles. Predictive models embody the knowledge from these profiles to create a “computational expert” or a “virtual patient” that can be queried. Predictive models such as these are of high value to pharmaceutical companies as they can be used to quickly select patients for clinical trials and assess potential new drugs or biomarkers computationally (“in silico”) before initiating expensive laboratory experiments. In short, Helomics’ predictive models will save time and money in the search for new targeted therapies.

Using the power of AI, the model draws on data generated from over 150,000 tumor cases obtained from over 15 years of clinical testing on living patient tumors, bringing together valuable multi-omic data, i.e. drug response, genomic (mutations), transcriptomic (gene expression) and tissue-omic (tumor pathology) profiles to predict drug response and outcome.

“Despite some headwinds imposed by the current COVID-19 pandemic, the Helomics team has been working diligently to meet both our clinical testing priorities for ovarian cancer patients and their oncologists, as well as maintaining progress on data generation for CCQ2020,” Helomics President Gerald Vardzel stated in a news release (http://nnw.fm/J8eDI). “Also, we received our formal letter of compliance today for our CLIA (Clinical Laboratory Improvement Amendments) recertification survey conducted on March 10, 2020. Results of this survey showed all requirements were met and that we were in full compliance with applicable regulations,” added Helomics medical director and vice president of operations and pathology services Dr. Arlette Uihlein.

“In a true team effort across the company we have made solid progress on our CCQ2020 milestones this quarter; we ramped up our sequencing effort as part of our UPMC-Magee collaboration; initiated further digitization of our histopathology slide collection; renewed our collaboration with Genomics England 100,000 genomes project and completed development of our AI model build framework so we can train millions of potential models at scale using cloud resources,” indicated Helomics CTO Dr. Mark Collins.

POAI is bringing precision medicine, or tailored medical treatment using the individual characteristics of each patient, to the treatment of cancer. Through the company’s Helomics division, the company leverages its unique, clinically validated patient derived (PDx) smart tumor profiling platform to provide oncologists with a road map to help individualize therapy. In addition, the company is leveraging artificial intelligence and its proprietary database of over 150,000 cancer tumors to build AI-driven models of tumor drug response to improve outcomes for the patients of today and tomorrow.

For more information, visit the company’s website at www.Predictive-Oncology.com

Please see full disclaimers on the NetworkNewsWire website applicable to all content provided by NNW, wherever published or re-published: http://NNW.fm/Disclaimer

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