Method validation and new peak detection for the liquid chromatography-mass spectrometry multi-attribute method.
J Pharm Biomed Anal
; 234: 115564, 2023 Sep 20.
Article
em En
| MEDLINE
| ID: mdl-37451094
The multi-attribute method (MAM) is a liquid chromatography-mass spectrometry (LC-MS) peptide mapping technique that has been proposed as a replacement for several conventional quality control (QC) methods for therapeutic proteins. In addition to quantification of multiple product quality attributes (PQAs), MAM can also monitor impurities using a new peak detection (NPD) feature. Here, results are provided from method validation and NPD studies of an MAM approach applied to rituximab as a model monoclonal antibody (mAb). Twenty-one rituximab PQAs were monitored, including oxidation, pyroglutamination, deamidation, lysine clipping, and glycosylation. The PQA monitoring aspect of the method was validated according to ICH Guidance. Accuracy, precision, specificity, detection and quantitation limits, linearity, range, and robustness were demonstrated for this MAM approach with minimal issues. All PQAs were successfully validated except for several oxidation sites, which did not pass intermediate precision criteria. The variability found in oxidation measurements was attributed to artificial oxidation during sample preparation and could likely be alleviated through several approaches. The NPD aspect of the method was also evaluated. A spike-in approach was used to assess the limits of detection and quantitation (LOD/LOQ) of the NPD feature of MAM. For NPD, the peak intensity threshold was found to be the most critical parameter for accurate detection of impurities since a low threshold can result in false positives while a high threshold can obscure the detection of true peaks. Overall, the MAM approach presented and validated here has been demonstrated to be suitable for both targeted monitoring of rituximab PQAs and non-targeted detection of new peaks that represent impurities.
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Base de dados:
MEDLINE
Assunto principal:
Anticorpos Monoclonais
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article
País de afiliação:
Estados Unidos