- POAI
subsidiary sequencing ovarian cancers as part of CancerQuest 2020 project,
building largest ovarian multi-omic database in the world
- Company’s
work designed to speed development of new drugs, provide therapeutic
choices
- Helomics
recently signed collaborative agreement with UPMC-Magee to establish data-
and artificial-intelligence-driven approach to treating ovarian cancer
The power of artificial intelligence (AI) to assist in the
detection of ovarian cancer much earlier than previously possible is being
recognized worldwide. A company in the United Kingdom is touting the ability of
AI to eliminate late detection of ovarian cancer, thanks to advancements in
health-care technology (http://ibn.fm/AOmHt).
The contribution AI is making in the detection of ovarian cancer has been a
longtime, consistent focus for Predictive
Oncology Inc. (NASDAQ: POAI) as well.
Predictive Oncology recently began sequencing ovarian
cancers as part of its CancerQuest 2020 project and is building the largest
ovarian multi-omic database in the world, designed to speed the development of
new drugs and provide better therapeutic choices. Predictive Oncology’s
subsidiary, Helomics, is vital to the CancerQuest2020 work POAI is doing in the
ovarian cancer space.
Helomics currently has approximately 150,000 cases on its
molecular information platform, 38,000 of which are specific to ovarian cancer.
This invaluable scientific asset positions POAI as a leader in providing the
critical molecular information needed for more effective patient treatments and
new drug discovery.
As part of its CancerQuest 2020 project, Predictive
Oncology, through Helomics, recently signed a collaborative agreement with
UPMC-Magee to establish a data- and artificial-intelligence-driven approach to
treating ovarian cancer. Based on the agreement, the partnership is designed to
validate the significant value of using AI-powered decision-making for
identifying specific treatments on specific genotypes to predict clinical
outcomes for ovarian cancer patients.
Helomics has also begun sequencing retrospective ovarian
cancer cases from the UPMC-Magee collaboration (http://ibn.fm/I4Lnb). As part of the sequencing process,
Helomics is analyzing the mutations in the tumor (genome) and the expression of
genes (transcriptome) in order to build a comprehensive multi-omic picture of
the tumor. That information can then be brought together with Helomics’ data
set of drug-response profiles to build an AI-driven predictive model of ovarian
cancer.
“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,” Helomics CTO Dr. Mark Collins stated in a news release.
In addition to its ovarian-cancer data, Helomics has another
120,000 tumors with drug-response data across 137 cancer types that include
lung, breast, pancreatic, colon and head and neck. Moving forward, the company
intends to sequence all the tumors and build out predictive models in these
additional disease categories. Once this work is complete, Helomics will have
the largest pan-cancer, multi-omic database with drug responses in the market.
For more information, visit the company’s website at www.Predictive-Oncology.com
NOTE TO INVESTORS: The latest news and updates
relating to POAI are available in the company’s newsroom at http://ibn.fm/POAI
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