Empowered Patient Podcast Life-Saving Diagnostics Enhanced by AI Analysis to More Accurately Inform Patients and Providers Eric Mayer New Day Diagnostics
Eric Mayer, CEO of New Day Diagnostics, is tapping into the trend for more user-friendly diagnostics that patients can use to test themselves for making medical decisions. While blood draw facilities and complex testing will always be a component of healthcare, as technology progresses, more at-home testing will become available. To better support patients and providers, New Day is finding less invasive ways to collect biomarker information and using AI and machine learning to refine the interpretation of test results.
Eric explains, "The business model is very straightforward. We design and develop our suite of diagnostic products that cover cancer testing, infectious disease testing, digestive disease, and women's health. We also operate a contract research laboratory and CRO services for other diagnostics developers, whether point-of-care or over-the-counter, who want to bring those products through the FDA. We help with those studies, and we help with the clinical trials. And then, we also deploy diagnostics. We operate a clinical laboratory where we can drive patient results through the tests that we deploy and have a network of distributors and sales channels to get kitted products and kitted diagnostic tests out into the field once they're approved."
"Depending on the type of test or the type of disease we're trying to detect, there are some that are just a yes-no. It's sort of a qualitative result. Either the virus or that bacteria is or is not there. Then, there's another for measuring numerous biomarkers in a blood sample. A liquid biopsy is a great example. At New Day Diagnostics, we incorporate AI and machine learning to combine advanced mathematics and science and distill it down to what we believe is a very easy-to-understand result for that physician and for that patient to understand. That is absolutely right. It doesn't help anybody if its result is just a mishmash of numbers without any clinical usefulness for what that result represents."
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