Computer-aided screening for hallucinogenic and stimulant amphetamines with gas chromatography-Fourier transform infrared spectroscopy (GC-FTIR).

An expert system applied as a screening test for amphetamine analogues found in recreational-drug exhibits (tablets or powders) is described. The knowledge base defining the reference Fourier transform infrared spectroscopic (FTIR) spectral patterns has been built according to criteria encompassing toxicological, pharmacological, and neurochemical aspects. The class identity of a compound is determined within seconds using soft independent modeling of class analogy (SIMCA). The predictive value of the system, as assessed at a testing accuracy of 95%, is expressed by a total correct classification rate of 93.93% and by a 96.30% rate of true-positive amphetamines. The specificity and the selectivity of the screening test, evaluated by testing 159 toxicologically relevant compounds, are discussed, emphasizing the chemical and physical factors affecting these parameters. Medicinal amphetamines giving cross-reactions with traditional screening techniques produce a negative result. The specificity of the system characterizes the expert system as a highly sensitive, selective, fast, and user-friendly screening test that screens for amphetamines with prediction accuracy adequate for investigations in analytical toxicology.

Identification of novel illicit amphetamines from vapor-phase FTIR spectra - a chemometrical solution.

A computer-aided procedure automating the identification of illicit amphetamine analogs eluting from a gas chromatograph coupled to a Fourier transform infrared spectrometer is presented. The expert system discriminates novel amphetamines from other classes of drugs of abuse normally screened in illicit tablets or powders. The main analytical advantages of the system over the automated procedures dedicated to general unknown analysis are the objectivity and the accuracy in predicting the class identity of the compound (i.e. stimulant, hallucinogen) when the reference spectrum is not present in the spectral library. The expert system uses quantitative thresholds defining the similarity of the unknown to the classes of illicit amphetamines and checks the presence of the molecular skeletons associated with different psychotropic effects of amphetamines. The challenge in building the system was the fuzziness of vapor-phase Fourier transform infrared spectrometer spectra of low-weight molecules such as amphetamines. This paper emphasizes the chemometrical techniques found most appropriate for modeling such spectral behavior. An exploratory (principal component) analysis indicated the sample preparation and the feature weight function yielding the best input for the knowledge base. The class identity of a compound was assigned using Soft Independent Modeling of Class Analogy. A rule-based decision system was implemented to enhance the accuracy in identity assignment. The flow diagram optimizing the knowledge base content of each model is presented. Finally, up to 81.13% (out of 159 tested compounds) were classified with a 5% confidence level. The total correct classification rate was 93.93%, for a yield of 96.30% true positive amphetamines.

Pattern recognition techniques screening for drugs of abuse with gas chromatography-Fourier transform infrared spectroscopy.

As many drugs of abuse are relatively volatile substances, gas chromatography-mass spectrometry (GC-MS), and more recently gas chromatography-Fourier transform infrared spectroscopy (GC-FTIR) became the most powerful techniques applied for their identification. We are presenting a combination of pattern recognition techniques discriminating illicit amphetamines according to the substitution pattern associated with the psychotropic activity (stimulants and hallucinogens) for which they are abused, and with the corresponding level of health hazard. As we determined, GC-FTIR provides the best selectivity in identifying the structural features associated with the full constellation of pharmacological effects of amphetamines. The toxicological questions to be answered and the spectroscopic features enabling the screening based on soft independent modeling of class analogy (SIMCA) are discussed. The accuracy, sensitivity and selectivity of the system recommend its use for automating the investigations of illicit drugs for epidemiological, clinical, administrative and forensic purposes. As opposed to the traditional tests screening for drugs of abuse, the system may also be applied as a broad-spectrum screening test. The extent to which the output of a query for amphetamines may be used for assessing the class identity of a negative (i.e. other hallucinogens or stimulants, sympathomimetic amines, narcotics and precursors) was determined by a systematic principal component analysis (PCA). The basic information is summarized in tables according to the category or class of compounds found suitable for screening.

Tissue distribution of trichloroethylene and its metabolites in a forensic case.

A fatality that was due to the ingestion of the halogenated solvent trichloroethylene is presented. The decedent was a 43-year-old male who was found dead at his home. Screening of the blood and stomach contents with the enzyme multiplied immunoassay technique and radioimmunoassay demonstrated the presence of ethanol, amphetamine-like compounds, caffeine, cotinine, and acetaminophen. These compounds were present in toxicologically irrelevant concentrations as confirmed by thin-layer chromatography, high-performance liquid chromatography, and gas chromatography (GC). The Fujiwara reaction was performed on all available matrices, and it revealed the presence of chlorinated hydrocarbons in high concentrations. A specific GC method with electron capture detection allowed the quantitation of trichloroethylene and its metabolites trichloroethanol and trichloroacetic acid in different matrices. GC with Fourier-transform infrared detection was used for the confirmation of the identity of trichloroethylene.

Tissue distribution of amphetamine isomers in a fatal overdose.

A young man (22 years old) died of a cardiorespiratory arrest a few hours following admission to the emergency department of a hospital. He was found lying seriously ill in the parking lot of a dance club. Screening of postmortem blood and urine with enzyme multiplied immunoassay (EMIT) detected only amphetamines, caffeine, and cotinine. Further screening of blood, urine, and stomach contents with thin-layer chromatography (TLC) and high-performance liquid chromatography (HPLC) was negative for all three matrices. Specific conditions for amphetamines were used for the gas chromatographic (GC) screening (GC-mass spectrometric [MS] and GC-nitrogen-phosphorus detection). This resulted in the preliminary identification of amphetamine in both blood and urine. Confirmation of the presence of amphetamine in all available postmortem specimens was provided by mass and infrared spectral data (GC-MS and GC-Fourier transform infrared spectrometry) after derivatization. Quantitative results and differentiation between the enantiomers of amphetamine were obtained after chiral derivatization. The calculated concentrations disclosed amphetamine ingestion as the cause of this fatality.