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LC-MS-sMRM Method Development and Validation of Different Classes of Pain Panel Drugs and Analysis of Clinical Urine Samples

  1. Author:
    Athar Masood, M
    Veenstra, Timothy D
  2. Author Address

    Laboratory of Proteomics and Analytical Technologies, Advanced Technology Program, SAIC-Frederick, Inc, Frederick National Laboratory for Cancer Research, Frederick, Maryland, USA.,
    1. Year: 2017
    2. Date: Aug 26
    3. Epub Date: 2017 Aug 26
  1. Journal: Basic & Clinical Pharmacology & Toxicology
  2. Type of Article: Article
  1. Abstract:

    Urine Drug Testing (UDT) is an important analytical/bio-analytical technique that has inevitably become an integral and vital part of a testing program for diagnostic purposes. This manuscript presents a tailor-made LC-MS/MS quantitative assay method development and validation for a custom group of 33 pain panel drugs and their metabolites belonging to different classes (opiates, opioids, benzodiazepines, illicit, amphetamines, etc.) that are prescribed in pain management and depressant therapies. The LC-MS/MS method incorporates two experiments to enhance the sensitivity of the assay and has a run time of about 7 min. with no prior purification of the samples required and a flow rate of 0.7 mL/min. The method also includes the second stage metabolites for some drugs that belong to different classes but have first stage similar metabolic pathways that will enable to correctly identify the right drug or to flag the drug that might be due to specimen tampering. Some real case examples and difficulties in peak picking were provided with some of the analytes in subject samples. Finally, the method was deliberated with some randomly selected de-identified clinical subject samples, and the data evaluated from "direct dilute and shoot analysis" and after "glucuronide hydrolysis" were compared. This method is now used to run routinely more than 100 clinical subjects samples on a daily basis. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

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External Sources

  1. DOI: 10.1111/bcpt.12877
  2. PMID: 28843027

Library Notes

  1. Fiscal Year: FY2016-2017
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