Adding Mass Detection to LC/UV-Based Workflows for Routine Analysis and Monitoring of Biologics in Development and Quality Control Laboratories

Library Number:
PSTR134956656
Author(s):
Brooke M. Koshel, Ximo Zhang, Robert Birdsall, and Ying Qing Yu
Source:
Waters
Content Type:
Posters
Content Subtype:
PAMS
Related Products:
 
 
 

Many of the top-selling pharmaceuticals currently on the market and in the pipeline are biologics. Like with any pharmaceutical product, rigorous characterization and purification is needed to ensure safety and efficacy. Many of the analytical methods used for the analysis of biologics are traditionally carried out using reversed-phase LC methods with optical detection. While this provides a basic level of assurance, by incorporating mass detection as an orthogonal technique, improved sensitivity, expanded detection limits, and increased confidence about peak homogeneity are achieved. Regulators also recognize and support the notion for improving process performance through lifecycle management to expand the body of knowledge surrounding a product.

In this study, we present a strategy for the acquisition of optical data with added mass detection for enabling identification of a model peptide, eledoisin, and its impurities using compliant-ready software. With processing and reporting methods in place, user error is eliminated, and treatment of the data is automated. Furthermore, any standards or samples not meeting established criteria are flagged for user intervention, with added mass detection readily allowing for further interrogation of samples that do not meet specification.

Mass detection is further used to demonstrate improved product quality compared to a traditional optical-based workflow through method modernization at the intact and peptide level using insulin drugs from three different manufacturers. Methods for peptide mapping were adapted from the USP monograph for human insulin. The insulin data demonstrates that added mass detection provides the specificity and sensitivity needed to discern subtle differences in the differentiation of highly similar small biotherapeutics. Incorporating cost-effective MS detection to existing workflows as an in-line orthogonal detection technique provides an efficient means to improve productivity of drug development and quality control.


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