期刊
JOURNAL OF PHARMACEUTICAL ANALYSIS
卷 8, 期 2, 页码 138-146出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jpha.2017.12.008
关键词
Surface plasmon resonance; EC50; Sensorgram comparison; Calibration free concentration analysis; Surrogate potency assay; TNF-alpha
Surface plasmon resonance (SPR) systems are widely used for detailed characterization of antibody activities including antigen and Fc-receptor binding. During the later stages of development, where the focus is to ensure that established critical quality attributes (CQAs) are maintained during cell culture, purification and formulation processes, analysis is simplified, and relative potencies are often determined. Here, simulation of binding data revealed that relative potency values, determined via parallel line analysis (PLA) and half maximal effective concentration (EC50) analysis accurately reflect changes in active concentration only if binding kinetics remain unchanged. Changes in the association rate constant shifted dose response curves, and therefore relative potencies, in the same way as changes in analyte concentration do. However, for interactions characterized by stable binding, changes in the dissociation rate constant did not result in any shift, suggesting that this type of change may go unnoticed in the dose response curve. Thus, EC50 and PLA analyses of dose response curves obtained with an anti-TNF-alpha antibody were complemented with the Biacore functionality for sensorgram comparison analysis, whereby changes in antigen and Fc-receptor binding profiles could be detected. Next, analysis of temperature stressed TNF-alpha antibody revealed that calibration free concentration analysis (CFCA) data correlated perfectly with relative potency values. Together, these results demonstrate that combinations of SPR based dose response curves, sensorgram comparison and CFCA can be used to strengthen the confidence in relative potency assessments, and suggest that SPR can potentially be used as a surrogate potency assay in the quality control of biotherapeutic medicines. (C) 2018 Xi'an Jiaotong University. Production and hosting by Elsevier B.V.
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