The RAID method

Veterinary Decision Support System (RAID)

RAID is Veterinary Decision Support System (RAID), does not require culturing and thus can detect bacterial infection within maximum 2 hours at affordable cost. Uniquely, it uses phospholipids as “bacterial fingerprints”, which are detected by regular Mass Spectroscopic (MS) measurement. The key innovation is the intelligent algorithm that can separate the complicated mixed MS signals and identify these “bacterial fingerprints”.

Phospholipids are a class of lipids that are a major component of all cell membranes. They can form lipid bilayers because of their amphiphilic characteristic. The structure of the phospholipid molecule generally consists of two hydrophobic fatty acid “tails” and a hydrophilic “head”, joined together by a glycerol molecule. The phosphate groups can be modified with simple organic molecules such as choline. Our intelligent method identifies these molecules as fingerprints. When teaching the algorithm, the fatty acids and their ratio identical for a given bacterium species, are determined. These fatty acids are paired with the polar head (ethanolamine or glycerol) and their sum should also be found in the spectrum. If all the three signals are found: fatty acids, ethanolamine or glycerol and their sum, the phosphatidyile structure is determined. Since the types of phosphatidyile compounds are identifying the bacteria, this method will determine the bacterium identification

RAID detects bacteria species without lengthy culturing procedure, even in complex mixed samples. Our RAID method reduces the bacteria identification from 24-72 hours to maximum 2 hours, in most of the cases to about 20 minutes. Our innovation contains three main steps.

Our proprietary methodology is based on the identification of phospholipids found on the outer surface of the bacterium cell (at high concentration) and use them as “bacterial fingerprints”. These fingerprints have very complex, but unique mass spectroscopic sign different for each bacteria species. The key innovation of our development is the intelligent algorithm that can separate the complicated mixed MS signal and the software based on this algorithm.