Journal of Analytical, Bioanalytical and Separation TechniquesJournal of Analytical, Bioanalytical and Separation TechniquesJournal of Analytical, Bioanalytical and Separation TechniquesJournal of Analytical, Bioanalytical and Separation Techniques2476-1869Ommega Online PublishersNew Jersey, USA104710.15436/2476-1869.16.1047Research ArticleDevelopment of an Automated “Just-in-Time” Derivatization Process for Gas Chromatography-Mass Spectrometry Analysis Applied to Metabolomics SamplesDevelopment of an Automated “Just-in-Time” Derivatization Process for Gas Chromatography-Mass Spectrometry Analysis Applied to Metabolomics SamplesDieterDrexlerBristol-Myers Squibb Company Research and Development Pharmaceutical Candidate Optimization - Bioanalytical and Discovery Analytical Research 5 Research Parkway Wallingford CT USAEditor* E-mail: dieter.drexler@bms.com
The authors have declared that no competing interests exist.
20162508201611JABST-16-RA-104707082016160820162016Creative Commons Attribution LicenseThis is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. nbsp emsp emsp The systems biology tool metabolomics is utilized to explore the question rdquo What qualitative and quantitative endogenous molecular species differentiate the samples from the respective study groups representing a control diseased and treated status rdquo utilizing a comparative analysis Among the analytical tools gas chromatography- mass spectrometry GC-MS provides in-depth data However the required sample preparation includes chemical derivatization steps which raise concerns about the stability of analytes especially when dealing with large sample sets resulting in long analyses queues To address these issues an automated ldquo just-in-time rdquo derivatization methodology was developed whereby samples are processed in a ldquo serial individual mode rdquo resulting in high quality and reproducible data 10