Assess a Diagnostic Tool to Distinguish Between Bacterial and Viral Infection

Overview

In the past 70 years antibiotics have served as the first line of defense against infectious diseases. However, antibiotics are only effective against bacterial infections and are not the solution for infections caused by viruses such as common colds or flu. Despite their contribution to healthcare, antibiotics are currently recognized as the most misused drugs in the world with global overuse estimated at 40%-70%, mostly due to the ineffectiveness of current diagnostic solutions to distinguish between bacterial and viral infections. Antibiotics misuse often causes preventable adverse events that impact patient care and lead to the emergence of antibiotic-resistant bacteria, one of the major threats to global health today. To address these challenges, MeMed has been developing the ImmunoDx™, a novel technology that relies on the best available detection system for differentiating between viruses and bacteria - the body's own immune system. The ImmunoDx™ technology employs a simple blood test that provides the physician, within two-hours, the information he needs to decide whether to treat the patient with antibiotics or not. This technology has been tested on over 1000 patients of different ages and diseases and was found to be highly accurate and safe. The current study is a non-interventional study and the participants do not receive any investigational drug nor any experimental examination or procedure. Therefore, the collected data in this study will not affect the diagnosis, prognosis, or treatment of the participants. Participation includes the collection of a teaspoon of blood and collection of a specimen using a nasal swab. These procedures are common in the clinical practice and are widely performed and possess no significant risk. By participating in the study, the subjects impact the development of the ImmunoDx™ technology, which is expected to enable a future faster and more accurate diagnosis of infectious diseases as well as more appropriate prescription of antibiotics. This will open the way to improve treatment decisions in millions of patients around the world.

This is a prospective clinical validation study of a novel in-vitro diagnostic (IVD) assay that will enroll 830 pediatric patients. The study will be conducted in two stages: In stage A 50 patients will be enrolled with the aim of verifying proper protocol execution including proper collection of patient samples, accurate data retrieval and precise etiology determination. In stage B 780 patients will be enrolled with the aim of blinded validation of the host-response based diagnostics using a fresh independent cohort of patients. Patients enrolling into the study will be managed according to the current standard of care (GCP) and per standard institutional procedures. Participation in this study requires the collection of an additional blood sample and a nasal swab sampling. The investigated assay requires the measurement of three host-related, blood-based, protein biomarkers that are being integrated using a logistic regression formula into a single score. Based on this score, each patient is classified into one of three categories: (i) bacterial immune response (i.e., pure bacterial infections and mixed bacterial and viral co-infection), (ii) viral immune response, and (iii) marginal immune response (inconclusive or non-infectious). It is estimated that 10-20% of the infected patients will have a marginal immune response. A composite reference standard will be used in order to determine the diagnosis of each patient. Specifically, all the clinical, radiological, microbiological and laboratory data of each patient, will be recorded in a dedicated eCRF. Based on this data, the diagnosis of each patient will be determined by a panel of three independent pediatricians. Each pediatrician will be blinded to the diagnosis of his peers and to the assay results. In the current study, unanimous agreement between the experts ("consensus agreement") will be considered as the true diagnosis for the purpose of computing the assay performance.