Optimized Sample Preparation and Data Processing of Data-Independent Acquisition Methods for the Robust Quantification of Trace-Level Host Cell Protein Impurities in Antibody Drug Products

Host
cell proteins (HCPs) are a major class of bioprocess-related
impurities generated by the host organism and are generally present
at low levels in purified biopharmaceutical products. The monitoring
of these impurities is identified as an important critical quality
attribute of monoclonal antibody (mAb) formulations not only due to
the potential risk for the product stability and efficacy but also
concerns linked to the immunogenicity of some of them. While overall
HCP levels are usually monitored by enzyme-linked immunosorbent assay
(ELISA), mass spectrometry (MS)-based approaches have been emerging
as powerful and promising alternatives providing qualitative and quantitative
information. However, a major challenge for liquid chromatography
(LC)-MS-based methods is to deal with the wide dynamic range of drug
products and the extreme sensitivity required to detect trace-level
HCPs. In this study, we developed powerful and reproducible MS-based
analytical workflows coupling optimized and efficient sample preparations,
the library-free data-independent acquisition (DIA) method, and stringent
validation criteria. The performances of several preparation protocols
and DIA versus classical data-dependent acquisition (DDA) were evaluated
using a series of four commercially available drug products. Depending
on the selected protocols, the user has access to different information:
on the one hand, a deep profiling of tens of identified HCPs and on
the other hand, accurate and reproducible (coefficients of variation
(CVs) < 12%) quantification of major HCPs. Overall, a final global
HCP amount of a few tens of ng/mg mAb in these mAb samples was measured,
while reaching a sensitivity down to the sub-ng/mg mAb level. Thus,
this straightforward and robust approach can be intended as a routine
quality control for any drug product analysis.