Monitoring
and quantifying host cell proteins (HCPs) in biotherapeutic
production processes is crucial to ensure product quality, stability,
and safety. Liquid chromatography–mass spectrometry (LC–MS)
analysis has emerged as an important tool for identifying and quantifying
individual HCPs. However, LC-MS-based approaches face challenges due
to the wide dynamic range between HCPs and the therapeutic protein
as well as laborious sample preparation and long instrument time.
To address these limitations, we evaluated the application of parallel
accumulation–serial fragmentation combined with data-independent
acquisition (diaPASEF) to HCP analysis for biopharmaceutical process
development applications. We evaluated different library generation
strategies and LC methods, demonstrating the suitability of these
workflows for various HCP analysis needs, such as in-depth characterization
and high-throughput analysis of process intermediates. Remarkably,
the diaPASEF approach enabled the quantification of hundreds of HCPs
that were undetectable by a standard data-dependent acquisition mode
while considerably improving sample requirement, throughput, coverage,
quantitative precision, and data completeness.