- POAI plans to have first predictive model of ovarian cancer ready for initial commercialization in Q1 2020
- First batch of 400 ovarian cancer subjects in initiative has been sequenced
- Groundbreaking AI-driven model of ovarian cancer will be capable of predicting tumor drug response, patient outcome
Predictive Oncology Inc. (NASDAQ: POAI), a company focused on applying artificial intelligence to personalized medicine and drug discovery, has updated the commercialization of its pioneering CancerQuest 2020 initiative (http://ibn.fm/gs5Qh). Based on the updated announcement, the company plans on having its first predictive model of ovarian cancer ready for initial commercialization in revenue-generating projects with Pharma in Q1 2020.
POAI’s CancerQuest 2020 initiative has been driven Helomics, a Predictive Oncology subsidiary which has worked closely with collaborators at the University of Pittsburgh Medical Center (UPMC)-Magee Women’s Hospital to optimize and scale the genomic and transcriptomic data that has been gathered. The first batch of the 400 ovarian cancer subjects has been sequenced, and Helomics is confident that the remaining subjects will move forward on schedule.
The sequencing marks the completion of one of five milestones outlined by POAI in its groundbreaking initiative designed to look at both tumor mutations (genome) as well as tumor gene expression (transcriptome) to build a comprehensive multi-omic picture of ovarian tumor (http://ibn.fm/noUgA).
“We are also using deep learning on histopathology images of the tumor tissue (tissue-omics) to add an additional dimension to this multi-omic profile,” explained Helomics CTO Dr. Mark Collins. “We believe the combination of the rich multi-omic profile of the tumor and clinical outcome data will allow us to build an AI-driven model of ovarian cancer capable of predicting the tumor drug response and patient outcome (prognosis).”
POAI anticipates receiving the outcome data on the 400 subjects in this retrospective trial from its collaborators at Magee Women’s Hospital shortly. Helomics intends to use the multi-omic data along with existing drug-response profiles and the outcome data to build its first AI-driven predictive model of ovarian cancer; the company expects the model to be commercialized in Q1 2020.
“We believe that this effort will enhance our understanding of the molecular profiles of women with ovarian cancer by using the power of artificial intelligence to create predictive models of therapeutic success,” said Dr. Robert Edwards, professor and chair of the Department of Obstetrics, Gynecology and Reproductive Sciences in the University of Pittsburgh School of Medicine (http://ibn.fm/I7qrx). “We are excited about the potential for AI-powered, evidence-based decision making to increase our ability to bring about successful outcomes.”
In addition, Helomics intends to sequence 50% of its 38,000-plus ovarian tumors in the upcoming year, creating what may be the world’s first comprehensive, actionable multi-omic data set for ovarian cancer. And Helomics doesn’t plan on stopping there. The company is already evaluating ways to sequence other cancers types in its database to build additional AI-driven predictive models, strengthening the company’s presence in both the clinical and research markets.
Predictive Oncology, which began as a joint venture between Skyline Medical and Helomics, is ideally positioned to harness the power of artificial intelligence and work with the pharmaceutical, diagnostic and biotech industries to develop highly customizable assessment methods for cancer patients.
For more information, visit the company’s website at www.Predictive-Oncology.com
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