FULLY-AUTOMATED SYSTEMATIC TOXICOLOGICAL ANALYSIS OF DRUGS, POISONS, AND METABOLITES IN WHOLE-BLOOD, URINE, AND PLASMA BY GAS-CHROMATOGRAPHY FULL SCAN MASS-SPECTROMETRY
A. Polettini et al., FULLY-AUTOMATED SYSTEMATIC TOXICOLOGICAL ANALYSIS OF DRUGS, POISONS, AND METABOLITES IN WHOLE-BLOOD, URINE, AND PLASMA BY GAS-CHROMATOGRAPHY FULL SCAN MASS-SPECTROMETRY, Journal of chromatography B. Biomedical sciences and applications, 713(1), 1998, pp. 265-279
Citations number
13
Categorie Soggetti
Chemistry Analytical","Biochemical Research Methods
Journal title
Journal of chromatography B. Biomedical sciences and applications
The availability of automated, rapid and reliable methods for the syst
ematic toxicological analysis (STA) of drugs and poisons in biosamples
is of great importance in clinical and forensic toxicology laboratori
es. Gas chromatography-continuous scan mass spectrometry (GC-MS) posse
sses a high potential in STA because of its selectivity and identifica
tion power. However, in order to develop a fully automated STA method
based on GC-MS two main obstacles have to be overcome: (a) sample prep
aration is rather sophisticated owing to the need to isolate analytes
from the aqueous matrix and to allow a correct GC repartition of polar
analytes; (b) the large amount of information collected within a sing
le analysis makes it difficult to isolate relevant analytical informat
ion (mass spectra of analytes) from the chemical noise. Using a bench-
top GC-MS system equipped with a laboratory robot for sample preparati
on (the Hewlett-Packard 7686 PrepStation) and an original method for m
ass spectral purification, a fully automated STA procedure was develop
ed involving isolation of drugs from the sample (whole blood with mini
mal pretreatment, plasma, urine) by means of solid-phase extraction, d
erivatization (trimethylsilylation) of the acidic-neutral and of the b
asic extracts, GC-MS analysis, processing of data, and reporting of re
sults. Each step of the procedure, and the method for data analysis in
particular, can be easily integrated with other existing STA methods
based on GC-MS. (C) 1998 Elsevier Science B.V. All rights reserved.