• Batch Characterisation of Polysorbates by Universal Hplc Detection

HPLC

Batch Characterisation of Polysorbates by Universal Hplc Detection

ESA Biosciences have announced the development of a sensitive, robust and precise method for the analysis of polysorbates using reverse-phase HPLC with Corona? CAD? (Charged Aerosol Detection). The approach, described in a new technical poster, can be used for either speciation of the various individual components of a non-ionic mixture, or to comparatively measure the variation in composition of polysorbates from batch to batch.

Using the Corona CAD detector in conjunction with reversed phase HPLC the authors present a simple isocratic method, capable of routinely separating and measuring the individual components of polysorbate mixtures. Six different batches of polysorbates were examined, results are given showing significant differences in the composition and levels of individual components in the polysorbate samples.

The CORONA CAD detector offers many advantages over ELSD and other approaches, including low nanogram sensitivity, a dynamic range exceeding four orders of magnitude (essential for looking at low levels of degradants in the presence of parent drug), good precision, response factors that are independent of structure and no low analyte level response ?drop-off'. Corona CAD is a robust, reliable, plug-and-play device, which requires no calibration or optimisation so even those with minimal training can run it. Corona CAD has been widely adopted by many leading pharmaceutical companies worldwide because it solves analytical challenges that no other technology can. The ideal complement to UV detection, Corona CAD delivers orders-of-magnitude advantages in sensitivity, dynamic range, consistency, reproducibility, and ease of use, providing universal high-performance liquid chromatography (HPLC) detection of virtually any non-volatile or semi-volatile compound, including proteins, lipids, carbohydrates, and small molecules.


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Lab Asia 31.6 Dec 2024

December 2024

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