Predictive Oncology Inc (NASDAQ: POAI) Collecting Data to Predict Better Ovarian Cancer Outcomes

Predictive Oncology (NASDAQ: POAI), a company focused on applying AI (Artificial Intelligence) for medicine and drug discovery, reported initial artificial intelligence-driven ovarian cancer results. In addition, its subsidiary Helomics is also working on data from the 100,000 Genomes Project, which is likely to predict survival rates of the patients post their treatment for ovarian cancer.

Working on predicting survival rates for ovarian cancer patients

Predictive Oncology indicated that its subsidiary Helomics is working on data collected from the 100,000 Genomes Project in Genomics England’s NGRL (National Genomic Research Library). As a result, the company has developed a new artificial intelligence model, enabling the specialist to predict the survival rates post-treatment for ovarian cancer patients. Further, the models can improve the treatment paths and drive new therapies for ovarian cancer. The outcome of the work is likely to get published in the late summer.

The subsidiary uses a machine learning approach to remove the genomic features from almost 500 ovarian cancer participants. In addition, the company stated, the model learns the patterns in the genetic mutations of patient’s tumors. Post which, Predictive Oncology work on predicting the survival rates is likely to increase to around 70% accuracy post the treatment. In addition, the company is working to refine its artificial intelligence models with a focus on improving overall predictions.

Oncology moving ahead

As per the company, the development of the model is a crucial achievement and a big step forward in oncology. As per the industry, there are currently no biomarkers for prognosis, making the treatment process difficult for individual patients. As a result, experts are forced to choose the drugs and treatment, which has not changed in the last several years, despite the industry’s extensive research. In addition, the company said that the artificial intelligence models also provide doctors and scientists better insights into which genes are involved in response to treatment, allowing for the development of new precision medicines.

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