April 1st 2025
Interest in applying artificial intelligence (AI) and machine learning (ML) to chromatography is greater than ever. In this article, we discuss data-related barriers to accomplishing this goal and how rethinking chromatography data systems can overcome them.
Combining HIC, SEC, and IEX with Fluorescence Polarization for Drug Target Discovery
May 1st 2017Fluorescence polarization (FP) is a highly regarded technique for studying drug–protein interactions, but has limited value regarding protein mixtures. As a novel approach to drug target discovery, the possibility of combining FP with liquid chromatography (LC) was explored. Nondenaturing protein LC principles such as size-exclusion chromatography (SEC), hydrophobic interaction chromatography (HIC), and ion exchange chromatography (IEX) were found to be orthogonal and compatible with FP because the mobile phases used do not negatively affect detection. For simple protein mixtures, the SEC/HIC/IEX–FP approach was able to identify tankyrase as the target of a triazole-based inhibitor of the Wnt signaling pathway, which is heavily associated with colon cancer. However, the total peak capacity of the three LC dimensions was not sufficient to resolve at cell-proteome level, calling for higher resolution of intact proteins to enable stand-alone drug target discovery with LC and FP.
Characterizing SEC Columns for the Investigation of Higher-Order Monoclonal Antibody Aggregates
April 1st 2016With many new biopharmaceuticals now being developed, robust analytical methods are needed to ensure that these protein-based drugs are of high purity and safe with a minimum amount of side effects. Size-exclusion chromatography is an important technique in investigating purity and is useful to identify and monitor protein aggregation, which can have economic and immunogenicity effects. This article discusses those column parameters that are most important in the selection of the optimum phase for SEC separations.
On-line SEC–Py-GC–MS for the Automated Comprehensive Characterization of Copolymers
September 1st 2007Size-exclusion chromatography (SEC) and pyrolysis-gas chromatography (Py-GC) are commonly used to characterize copolymers. SEC is a powerful method to determine the molecular-weight distribution of polymers whereas Py-GC provides valuable information on their chemical composition. The combination of these two techniques could yield combined size and composition information for copolymers or polymer mixtures. A fully automated system was constructed to perform these two-dimensional (2D) characterizations. Several examples of the use of this new technique to comprehensively characterize polymers are described.