- Cancer screenings, treatments declined during COVID-19 pandemic, highlighting need for personalized therapies to improve outcomes
- Comprehensive genomic, transcriptomic sequencing of patient samples complete, patient outcome data obtained from UPMC-Magee
- Project is template for future partnerships with other healthcare institutions to expand POAI’s AI-driven clinical models to other cancers
The consequences of COVID-19 sent shock waves throughout the healthcare sector in more ways than just the direct impact of coronavirus infections. A recent study (https://ibn.fm/6LLiW) showed that cancer screenings and treatments declined during the pandemic, with the authors cautioning that the fallout could be dramatic. The study’s results certainly highlight the need for more individualized treatment regimens that improve patient outcomes, minimize patient visits and help patients with advanced disease at the time of treatment. This is the area of specialty of Predictive Oncology (NASDAQ: POAI), a knowledge-driven medicine company that focuses on applying data and artificial intelligence (“AI”) to cancer personalized medicine and drug discovery. Through its Helomics division, the Minneapolis-based company has just made a significant stride in its efforts to build AI-driven models of ovarian cancer by completing key data generation milestones in a retrospective study in collaboration with UPMC-Magee Women Hospital, an affiliate of the University of Pittsburgh Schools of the Health Sciences (https://ibn.fm/KSr2G).
While the science and technology are complex, the overarching concept isn’t: Test drugs on individual tumors in a lab setting to better inform doctors’ decisions in the real world. Effectively, Helomics performs chemotherapy on a patient’s tumor before the patient gets the drug to provide the oncologist with information on what may or may not work before the oncologist ultimately prescribes a treatment plan.
During more than 15 years of clinical testing, Helomics has amassed a proprietary knowledge base, coined TumorSpace(TM), of more than 150,000 tumor drug response profiles. Simply, Helomics grows patient tumors and tests how they respond to drugs, constantly analyzing and collating data as it builds multi-omic predictive models of tumor drug response and outcome. “Multi-omic”—biotech speak for integrating data collected from different omic levels (meaning things like genomes, proteome, etc.) to understand interactions and influence on disease pathogenesis—involves using cutting-edge machine learning technology to combine a drug response profile with a genomic profile to deliver a more meaningful and effective impact than genomics alone could.
Helomics currently provides treatment option recommendations to personalize therapy based on tumor profiles as it continues development of its AI-driven models. Once the AI models are complete and validated, it will move exclusively to the AI-driven computer models.
As it happens, looking back is often the best way to move forward. That was the purpose of the study with UPMC-Magee Women Hospital. Comprehensive genomic and transcriptomic sequencing of patient samples is now complete, and patient outcome data has been obtained from UPMC-Magee. These data will now be used to drive POAI’s AI models of ovarian cancer and their internal ovarian cancer drug re-purposing project.
“The successful generation of high-quality genomic and transcriptomic data from archived materials at Helomics, together with the gathering of historical outcome data from our collaborator UPMC-Magee, demonstrates that we can leverage Helomics’ unique asset and deliver significant value,” said Predictive Oncology CEO Dr. Carl Schwartz. “Furthermore, this project is a template we can use to partner with other healthcare institutions and expand our AI-driven clinical models to other cancers.”
According to the American Cancer Society, about 21,410 women will receive a new diagnosis of ovarian cancer this year and approximately 13,770 women will die from the disease.
POAI is bringing precision medicine, or tailored medical treatment using the individual characteristics of each patient, to the treatment of cancer. Through its Helomics division, the company leverages its unique, clinically validated patient derived (“PDx”) smart tumor profiling platform to provide oncologists with a roadmap to help individualize therapy. In addition, the company is leveraging artificial intelligence and its proprietary database of over 150,000 cancer cases 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.
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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