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Scientia Pharmaceutica is published by MDPI from Volume 84 Issue 3 (2015). Articles in this Issue were published by another publisher in Open Access under a CC-BY (or CC-BY-NC-ND) licence. Articles are hosted by MDPI on as a courtesy and upon agreement with Austrian Pharmaceutical Society (Österreichische Pharmazeutische Gesellschaft, ÖPhG).
Open AccessAbstract
Sci. Pharm. 2009, 77(Short Lectures (SL)), 183; (registering DOI)

Improved “General Unknown” Drug Screening Using GCxGCqMS

Shimadzu Europa GmbH, Albert Hahn-Str. 6–10, 47269 Duisburg, Germany
MVZ für Mikrobiologie, Labordiagnostik und Hygiene Dessau GmbH, Bauhüttenstr. 6, 06847 Dessau, Germany
Author to whom correspondence should be addressed.
Received: 16 April 2009 / Accepted: 16 April 2009 / Published: 16 April 2009
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Drug screening in the clinical setting is very often started or even solely performed with a limited selection of enzyme immunoassays in urine samples. As a general rule positive results must be confirmed by more specific and sensitive methods like GC/MS or LC/MS(-MS). GC/MS full scan mode giving the highest level of specificity often faces the problem of co-elution which esp. at high concentrations cannot be circumvented even with modern deconvolution software in many cases. However, broad, undirected “general unknown” screening for drugs of abuse not covered by the EIA/GC/MS-SIM combinations is of increasing importance. In the present study we therefore investigated if the common drawbacks encountered in a standard GC/MS full-scan method could be improved by increased chromatographic resolution by means of comprehensive GCxqGCMS in full-scan mode [1]. To perform comprehensive GCxGC measurements a two stage loop modulator (ZOEX cooperation USA) was used. By use of a modulation frequency of 6 seconds together with the selected GC parameters results in 3 modulated peaks per compound. The results out of the comprehensive GCxGCqMS were compared with the one dimensional data set.
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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BÖHME, S.; BÖTTCHER, M. Improved “General Unknown” Drug Screening Using GCxGCqMS. Sci. Pharm. 2009, 77, 183.

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