Literature DB >> 20942391

Identification of multiple impurities in a pharmaceutical matrix using preparative gas chromatography and computer-assisted structure elucidation.

Anna Codina1, Robert W Ryan, Richard Joyce, Don S Richards.   

Abstract

Gas chromatography (GC) with a preparative fraction collector (PFC) has been used to facilitate the identification of a number of volatile impurities at major and minor percentage levels in a pharmaceutical matrix by nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS). The trapping process was optimized using liquid sorbents, and the impurities were trapped directly into a deuterated solvent. Challenges related to the pharmaceutical matrix were overcome by derivatization with boron trifluoride in methanol and extraction with heptane, producing the methyl esters of the carboxylic acid impurities and main component. GC coupled to atmospheric pressure chemical ionization mass spectrometry (APCI-MS) with a time-of-flight (TOF) detector was used to acquire accurate mass and isotopic data for the impurities, leading to the determination of their molecular formulas (MF). One dimensional (1D) and two-dimensional (2D) NMR experiments were also acquired to unambiguously determine the impurities' structure. The acquisition time of the latter experiments was minimized by using a high-resolution instrument equipped with a small (1.7 mm) cryogenic probe. The quality of the data was such that the structure of the impurities could be determined semiautomatically by using a computer-assisted structure elucidation (CASE) approach, even though the total amount of one of the isolated impurities was less than 60 nmol.

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Year:  2010        PMID: 20942391     DOI: 10.1021/ac102151g

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  1 in total

1.  An efficient computer-aided structural elucidation strategy for mixtures using an iterative dynamic programming algorithm.

Authors:  Bo-Han Su; Meng-Yu Shen; Yeu-Chern Harn; San-Yuan Wang; Alioune Schurz; Chieh Lin; Olivia A Lin; Yufeng J Tseng
Journal:  J Cheminform       Date:  2017-11-15       Impact factor: 5.514

  1 in total

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