- 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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