NCJ Number
218655
Date Published
January 2005
Length
3 pages
Annotation
This report, which was developed by the Scientific Working Group for the Analysis of Seized Drugs, recommends minimum standards for the forensic identification of commonly seized drugs.
Abstract
The minimum standards refer to a table that classifies techniques for the analysis of drug samples into three categories, based on their discriminating power. Techniques with the most discriminating power (category A) are listed as infrared spectroscopy, mass spectrometry, nuclear magnetic resonance spectroscopy, and Raman spectroscopy. Techniques with somewhat less discriminating power (category B) are listed as capillary electrophoresis, gas chromatography, ion mobility spectrometry, liquid chromatography, microcrystalline tests, pharmaceutical identifiers, thin layer chromatography, and macroscopic examination and microscopic examination (cannabis only). The third category of techniques (category C), which have less discriminating power than the techniques listed in categories A and B, are color tests, fluorescence spectroscopy, immunoassay, melting point, and ultraviolet spectroscopy. The minimum standards indicate that when a validated category A technique is used in an analytical scheme, then at least one other technique from any of the three categories must be used. When a category A technique is not used, then at least three validated methods must be used. For the use of any method to be considered of value, test results must be considered positive, although negative test results provide useful information for ruling out the presence of a particular drug or drug class. In cases where hyphenated techniques are used, they are considered separate techniques if the results from each technique are used. Cannabis exhibits tend to have characteristics that are visually recognizable. Macroscopic and microscopic examinations of cannabis will be considered uncorrelated techniques from category B when observations include documented details of botanical features. Examples of reviewable data are listed.