We apply machine learning to translate the complex signaling of the immune system into simple, actionable diagnostic insights. MeMed’s machine learning-based diagnostics address key clinical and medical challenges in infectious diseases and inflammatory disorders.
Bacterial and viral infections are often clinically indistinguishable and can lead to inappropriate patient management and antibiotic misuse.1
MeMed BV® is the first FDA-cleared host-immune response assay for accurately distinguishing between bacterial and viral infections in just 15 minutes.
MeMed Key® is a cutting edge, compact immunoassay platform that makes it possible to conduct highly sensitive, quick, multiplexed protein measurements that previously could only be done on large, expensive central lab equipment.
Together, MeMed Key and MeMed BV help physicians make better decisions in the management of patients with acute infections.
External Double-Blind Prospective Validation
Our unique emphasis on quality and breadth of clinical evidence sets MeMed apart. MeMed BV performance has been validated in multi-national, double-blind clinical studies and real world settings enrolling over 20,000 subjects in Europe, Israel and the United States.1-7 These studies have consistently demonstrated compelling performance results in different clinical settings, age groups, and patients with different clinical syndromes.
Additional Clinical Dilemmas
By leveraging our expertise in host-response profiling and machine-learning algorithms, we are creating a portfolio of tests that address tough clinical dilemmas like infection severity and others.
- Oved K, Cohen A, Boico O, Navon R, Friedman T, Etshtein L, et al. A novel host-proteome signature for distinguishing between acute bacterial and viral infections. PloS One. 2015 Mar 18;10(3):e0120012.
- MeMed data on file. Based on secondary endpoint analysis in Apollo Clinical Study (NCT04690569).
- van Houten CB, de Groot JA, Klein A, Srugo I, Chistyakov I, de Waal W, et al. A host-protein based assay to differentiate between bacterial and viral infections in preschool children (OPPORTUNITY): A double-blind, multicentre, validation study. Lancet Infect Dis. 2017 Apr 1;17(4):431-40.
- Srugo I, Klein A, Stein M, Golan-Shany O, Kerem N, Chistyakov I, et al. Validation of a novel assay to distinguish bacterial and viral infections. Pediatrics. 2017 Oct 1;140(4).
- Papan C, Argentiero A, Porwoll M, Hakim U, Farinelli E, Testa I, et al. A host signature based on TRAIL, IP-10, and CRP for reducing antibiotic overuse in children by differentiating bacterial from viral infections: A prospective, multicentre cohort study. Clin Microbiol Infect. 2022 May 1;28(5):723-30.
- Halabi S, Shiber S, Paz M, Gottlieb TM, Barash E, Navon R, et al. Host test based on TRAIL, IP-10 and CRP for differentiating bacterial and viral respiratory tract infections in adults: Diagnostic accuracy study. Clin Microbiol Infect. 2023 Jun 1.
- Eden E, Srugo I, Gottlieb T, Navon R, Boico O, Cohen A, et al. Diagnostic accuracy of a TRAIL, IP-10 and CRP combination for discriminating bacterial and viral etiologies at the Emergency Department. J Infect. 2016 Aug 1;73(2):177-80.