Technologies

Biomarker for Multiple Sclerosis

  • Category: Diagnostics
  • Investment Status: Pre-Seed
  • Medical Field: Neurology
  • Medical Center: Faculty of Medicine, Technion and HaCarmel Medical Center and Chemical Eng, Technion
  • Inventors: Prof Ariel Miller and Prof Hossam Haick

Background: Currently, the diagnosis of MS is based on invasive and/or expensive laboratory techniques. Furthermore, specific MS tests are prescript by a neurologist only after at least two MS episodes separated by at least one month, and if the location of the lesions is in at least two distinct sites of the central nervous system. Therefore, there is an urgent need for a quick, reliable and easy-to-use diagnostic tool, in both outpatient and specialized clinics.

Technology: The invention describes a new, low-cost, easy-to-use and non-invasive (early) metabolomic diagnostic method for MS, which is based on breath testing with a sensor array. This method can be applied in non-specialist settings to diagnosing MS and classifying the current stage of disease (steady state or relapse phase). Possible future applications include screening of the general population and identification of MS at an early stage, identification of the current stage of disease, and assisting the clinical specialists in informed decision making regarding its optimized treatment.

Breath testing links specific volatile biomarkers or biomarker patterns in exhaled breath to medical conditions. MS related changes may occur due to abnormal lesions in brain and/or spinal cord, as well as due to oligoclonal bands of immunoglobulin G and increased levels of lactate in cerebrospinal fluid. They would be reflected, trough exchange via the lung, in a measurable variation of the biomarker levels in the breath. In contrast to Magnetic Resonance Imaging and/or handling cerebrospinal fluid samples, breath testing would be non-invasive, save and comfortable to the patient, and the health hazard through sample handling would be negligible.

Array of broadly cross-reactive sensors combined with a method for statistical data analysis, are ideally suited for the identification of patterns of volatile biomarkers of disease. In this configuration, each sensor reacts to all the chemical compounds in the breath. The integration of molecularly functionalized Au nanoparticles and single wall carbon nanotubes covered by a thick layer of polycyclic aromatic hydrocarbons derivatives into the sensing elements increases the sensitivity of the sensors, improves response and recovery times of the device, and achieves sensitivity to the MS biomarkers.