Vista, CA, Nov. 25, 2024 (GLOBE NEWSWIRE) -- Mindera Health, a precision medicine company developing personalized tools to optimize patient outcomes, today announced that additional patent protection has been issued in Japan for the core technology behind the dermal biomarker patch.
Japanese patent number JP7572774 was issued October 16, 2024 and describes devices that can extract dermal biomarkers in situ. The inventors discovered that a covalently modified patch can efficiently capture and extract meaningful quantities of biomarkers from the skin. This patent adds to existing patent protection for the dermal biomarker patch technology in the United States, Europe, Australia, China, Hong Kong, and Korea. This brings the total number of issued or allowed patents related to the Company's dermal biomarker patch technology to 11.
“We are pleased to have been issued additional patent coverage in Japan for the Dermal Biomarker Patch,” said Tobin Dickerson, Mindera Health’s chief scientific officer and co-founder. “This technology underpins tests such as Mind.Px™, a test designed to optimize psoriasis biologic treatment decisions and reduce trial and error treatment paradigms. As we expand the platform into other indications, we aim to more broadly bring precision medicine to dermatology.”
About Mindera Health™
Mindera Health is a private San Diego-area company developing and commercializing next-generation medical technology to enable a new era of skin analytics at the molecular level. Using a proprietary dermal biomarker patch, next-generation sequencing, and machine learning, Mindera Health technology generates clinically validated data to reduce healthcare system costs and improve patient outcomes. Mindera Health is a CLIA and CAP certified laboratory and has received ISO 13485:2016 certification. Find out more at www.minderahealth.com.
About Mind.Px™
Mind.Px is a predictive test that uses a dermal biomarker patch that allows for rapid and painless extraction of mRNA from skin, followed by transcriptomic analysis and machine learning-derived classifiers to provide actionable results for clinicians with >91 percent positive predictive value[i]. By matching the patient to the right drug class before treatment begins, a recent study used a budget impact model to predict the potential costs savings associated with Mind.Px and returned annually.[ii]
i. Bagel J, Wang Y, Montgomery P 111, et al. A machine learning-based test for predicting response to psoriasis biologics. SKIN The Journal of Cutaneous Medicine. 2021;5(6):621-638. doi:10.25251/skin.5.6.5
ii. Wu J, Montgomery P, Long B, et al. An economic evaluation of the budget impact of precision medicine testing for the treatment of psoriasis. SKIN The Journal of Cutaneous Medicine. 2021;5(4):372-387. doi:10.25251/skin.5.4.6
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