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Development of a fully automated toxicological LC-MS(n) screening system in urine using online extraction with turbulent flow chromatography


Mueller, D M; Duretz, B; Espourteille, F A; Rentsch, K M (2011). Development of a fully automated toxicological LC-MS(n) screening system in urine using online extraction with turbulent flow chromatography. Analytical and Bioanalytical Chemistry, 400(1):89-100.

Abstract

In clinical toxicology, fast and specific methods are necessary for the screening of different classes of drugs. Therefore, an online extraction high-performance liquid chromatography coupled to mass spectrometry (LC-MS(n)) screening method using a MS(2) and MS(3) spectral library for the identification of xenobiotic substances has been developed and validated. Samples were run twice, once native and once after enzymatic hydrolysis. Internal standards and buffer were added to the urine samples. Following centrifugation, the supernatant was injected into the system. Extraction was performed by online turbulent flow chromatography. The chromatographic separation was achieved using a Phenyl/Hexyl column. For detection, a linear ion trap, equipped with an APCI interface, was used and the different compounds were identified using a MS(2) and MS(3) spectral library containing 356 compounds. The turnaround time to report the results of the screening including hydrolysis was approximately 2 h. About 92% of the 356 substances could be identified with a limit of identification below 100 ng/ml. The recovery and matrix effect experiments showed suitable results, and in six drug-free urine samples of healthy volunteers analyzed for selectivity, no substances have been identified. Carryover could be well controlled, and the method had a good reproducibility. The comparison of the results of 103 real patient urine samples showed a good agreement between the existing GC-MS and LC-MS methods with offline extraction and the new online extraction LC-MS(n) screening method. The presented method allows a fast and sensitive analysis of a broad range of compounds.

Abstract

In clinical toxicology, fast and specific methods are necessary for the screening of different classes of drugs. Therefore, an online extraction high-performance liquid chromatography coupled to mass spectrometry (LC-MS(n)) screening method using a MS(2) and MS(3) spectral library for the identification of xenobiotic substances has been developed and validated. Samples were run twice, once native and once after enzymatic hydrolysis. Internal standards and buffer were added to the urine samples. Following centrifugation, the supernatant was injected into the system. Extraction was performed by online turbulent flow chromatography. The chromatographic separation was achieved using a Phenyl/Hexyl column. For detection, a linear ion trap, equipped with an APCI interface, was used and the different compounds were identified using a MS(2) and MS(3) spectral library containing 356 compounds. The turnaround time to report the results of the screening including hydrolysis was approximately 2 h. About 92% of the 356 substances could be identified with a limit of identification below 100 ng/ml. The recovery and matrix effect experiments showed suitable results, and in six drug-free urine samples of healthy volunteers analyzed for selectivity, no substances have been identified. Carryover could be well controlled, and the method had a good reproducibility. The comparison of the results of 103 real patient urine samples showed a good agreement between the existing GC-MS and LC-MS methods with offline extraction and the new online extraction LC-MS(n) screening method. The presented method allows a fast and sensitive analysis of a broad range of compounds.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Institute of Clinical Chemistry
Dewey Decimal Classification:610 Medicine & health
540 Chemistry
Date:2011
Deposited On:15 Feb 2011 14:48
Last Modified:05 Apr 2016 14:47
Publisher:Springer
ISSN:1618-2642
Publisher DOI:https://doi.org/10.1007/s00216-010-4560-4
PubMed ID:21174196

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