Computerized Detection of JWH Synthetic Cannabinoids Class Membership Based on Machine Learning Algorithms and Molecular Descriptors

An Artificial Neural Networks (ANN) model identifying JWH Synthetic Cannabinoids, that we have developed based on a combination of topological, 3D-MoRSE (Molecule Representation of Structure based on Electron diffraction) and ADMET (Absorption, Distribution, Metabolism, Excretion and Toxicity) molecular descriptors, is described and analyzed. The validation results indicate that this computerized system has a very high potential for efficiently predicting the class membership of JWH and discriminating them from a large variety of (non-JWH) substances of forensic interest.