Computer assisted substance identification in systematic toxicological analysis: New life for old methods?

Abstract Systematic toxicological analysis is a major task in clinical and forensic toxicology, usually being addressed with mass spectrometric methods. As an alternative to approach substance identification in resource limited laboratories, we developed an Internet-based software to process analyti...

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Bibliographic Details
Published in:Forensic science international 2010-10, Vol.202 (1), p.e53-e60
Main Authors: Linden, Rafael, Feltraco, Lilian L, Comerlato, Luana Christine, Kellermann, Estefânio, Antunes, Marina V
Format: Article
Language:English
Subjects:
Chromatographic analysis
Chromatography
Chromatography, Gas
Chromatography, High Pressure Liquid
Database retrieval
Databases, Factual
Forensic sciences
Forensic Toxicology - methods
Humans
Laboratories
Mass spectrometry
Metabolites
Methods
Models, Biological
Pathology
Pharmaceutical Preparations - urine
Probability
Software
Software development
Standard deviation
Studies
Substance identification
Systematic toxicological analysis
Toxicology
Ultraviolet Rays
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Summary:Abstract Systematic toxicological analysis is a major task in clinical and forensic toxicology, usually being addressed with mass spectrometric methods. As an alternative to approach substance identification in resource limited laboratories, we developed an Internet-based software to process analytical data, obtaining corrected identification parameters and using a probabilistic approach to retrieve a database comprised of retention indices in gas chromatography and relative retention times and absorption maxima in the UV range in high performance liquid chromatography, obtained at standardized conditions. The probabilistic approach allowed ranking candidate substances on basis of a Similarity Index. A Mean List Length of 1.6 was obtained when all analytical data was informed, considering a database of 1762 compounds. In 34 of 35 spiked samples, the software ranked the correct substance at the higher Similarity Index. List lengths similar to those obtained with more sophisticated methods can be found with the software, which represents a valuable alternative to resource limited laboratories.
ISSN:0379-0738
1872-6283
DOI:10.1016/j.forsciint.2010.05.011