February 26–March 1, 2007, PITTCON® 2007, Chicago, IL

Identification of Impurities Using Liquid Chromatography Hyphenated with Tandem Mass Spectrometry

Mark Bayliss

Abstract

"Why is it that as analysts we still invest huge numbers of hours into the extraction of potential impurities from LC/MS and fragment related data by having to perform manual data work-up? Is this not a perfect situation for software to provide a solution?"
Ensuring coverage of all potential impurities both in terms of extraction and identification forms a complex interdependency between the need to determine both molecular weight and obtain sufficient fragmental information to be able to support structure identification.
The potential to perform extraction and determination of molecular weight, obtain fragment and neutral loss data in a single pass experiment using an increased level of source voltage offers significant opportunities for automation by software. A similar approach applied to metabolism data by Bateman et al., and impurities by Rourick et al, provides an insight that from an instrumental and concept approach, this mode of data acquisition can be useful in screening type environments. In extending this concept, our group wanted to consider the feasibility of automating the extraction and identification of potential impurities using a software approach to auto-componentization, fragment extraction and elucidation. In this presentation we discuss the challenges of auto-componentization of MS data that ensure the accurate detection of appropriate fragment ions to enable the extraction of closely eluting impurities. In particular we were particularly interested in the potential to perform data extraction and elucidation of potential impurities eluting within the elution space of the parent drug substance. We also discuss the co-detection of related fragments and auto-calculation of neutral losses that provide a powerful multi-dimensional screening method with potential for downstream software automation.

Download the presentation in MS PowerPoint (747 Kb ZIP file) or Adobe Acrobat format (337 Kb PDF file).

Relevant Products: ACD/MS Manager, ACD/IntelliXtract

Relevant Solutions: Identification of Impurities and Degradants, Metabolite ID