Predictive Oncology Inc.’s (NASDAQ: POAI) Valuab
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- Predictive Oncology Inc. harnessing the power of artificial intelligence and its rich database of tumor data to help clinicians match cancer patients with most effective drug treatments
- Like Amazon’s customer dataset, POAI’s deep database of historical tumor information positions it for industry success
- Precision medicine is a data problem – demonstrates the huge value of data and those companies that generate it
When shopping on Amazon, it seems like the multinational technology company knows its customers intimately. Every product filtered into a search query response seems carefully curated to match each customer. This ability to leverage big data has pushed Amazon to the peak of success, and it now accounts for approximately 50 percent of all purchases made online (http://nnw.fm/9p3Le).
Amazon’s success is a result of the company’s deep historical dataset of customer purchase profiles and its ability to leverage that with technologies such as AI. Across multiple industries from e-commerce, through finance to health care, there is now a recognition that data and the algorithms that help make sense of data are increasingly valuable and a key competitive differentiator.
From the health care field Predictive Oncology Inc. (NASDAQ: POAI) has been garnering industry attention as a hidden gem in the field of precision medicine for its innovative use of data and algorithms.
Precision Oncology is harnessing the power of artificial intelligence (think algorithms) to revolutionize treatment outcomes for cancer patients. What sets POAI apart from its competitors is the same factor that fueled Amazon’s rise: data. POAI (via its Helomics acquisition) has a huge proprietary database of tumor information, gathered from over 15+ years of clinical testing, which uniquely contains the drug responses of 150,000 individual patient tumors. Like Amazon’s database, which grows with each purchase, this unique tumor database grows daily as new tumors are tested.
While the use of data in cancer diagnostics is becoming more commonplace (think BRCA gene testing for breast cancer), for most patients the genomic data gathered from their tumor is not actionable, because researchers have a poor understanding of what mutations are important for choosing therapy. In the Amazon example, it would be like knowing people purchased dog food and cat litter but failing to predict they should buy cat food. POAI’s unique data on tumor drug response builds AI-driven predictive models that bring together the mutational and drug response profiles of the tumor to offer true actionable insights.
POAI is working with the pharmaceutical, diagnostic, and biotech industries to use its predictive models to both improve the development of new drugs (patients of tomorrow) as well as help clinicians individualize therapy (patients of today).
One disruptive aspect of POAI’s technology is that it helps the clinician to increase the chance of choosing more effective therapy, resulting in potential reduction of side-effects as well as cost savings. Traditionally oncologists prescribe what drugs they think have the best chance at beating a patient’s cancer, and the drug may or may not prove effective. Meanwhile, the patient’s undergoes chemotherapy with often debilitating side effects. If the drug proves to be a poor fit for the patient’s cancer, the chemotherapy experience will have been in vain, and the patient must continue acting as a guinea pig in experimenting with the next likely drug candidate. This is the standard cancer treatment of today. However, by utilizing POAI’s innovative tumor-profiling platform, which literally performs chemotherapy on the patient’s tumor outside the body to determine which drug is most effective, the patient can be spared many of the risks of being a “guinea-pig” as the oncologist attempts different drugs.
As Predictive leverages the data from its huge database of 150,000 of these “chemo outside the body” tests to build new predictive models, the ability to help the clinician choose the most effective drug for a patient cancer will improve. In addition, Predictive’s valuable predictive model will be a boon to the pharmaceutical industry in their race to develop new drugs to fight cancer.
For more information, visit the company’s website at www.Predictive-Oncology.com
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