- 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…
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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