ANDOVER, Mass.– MeMed, a global leader in host-response diagnostics, has announced the completion of development for MeMed BV Flex™, the first fingerstick-based host-response test capable of accurately distinguishing between bacterial and viral infections in just 15 minutes. The test requires only a few drops of capillary blood and is designed for use in decentralized, CLIA-waived settings such as urgent care clinics and physician offices.
The new test runs on an enhanced version of MeMed’s existing platform and combines the simultaneous measurement of multiple host proteins with machine learning to deliver rapid, lab-comparable results. Verified through a prospective analytical study, MeMed BV Flex showed strong concordance between capillary and venous blood samples, demonstrating high accuracy across all protein targets and the overall BV score.
“Accurately and simultaneously measuring multiple proteins from just a few drops of blood, in a rapid and easy-to-use format, has been a long-standing challenge,” said Eran Eden, Ph.D., co-founder and CEO of MeMed. “By pairing this breakthrough with machine learning, we’ve enhanced our platform to help extend host-response testing to broader decentralized use.”
The company has initiated a multi-center pivotal trial to confirm the test’s clinical accuracy and support regulatory submissions, following early discussions with the U.S. Food and Drug Administration.
Dr. Adam Singer, Vice Chairman for Research at Stony Brook University’s Department of Emergency Medicine, noted the potential impact on clinical care: “Running MeMed BV Flex from a simple finger stick will make advanced host-response testing more widely accessible, not just for pediatric patients, but also in decentralized settings. It means fewer venipunctures for children, faster answers for seniors, and smarter antibiotic use across the board.”
The launch of MeMed BV Flex marks a major step in the company’s broader effort to expand access to rapid diagnostic tools and develop additional assays for sepsis, immune status, and disease severity.
