Definitive benchmarking of DDA and DIA for host cell protein analysis on the Orbitrap Astral in a regulatory-aligned framework

Host cell proteins (HCPs) are critical quality attributes in biotherapeutics that require accurate, specific, and comprehensive quantification. Mass spectrometry (MS)-based workflows are increasingly adopted to overcome the coverage and specificity limitations of immunoassays. This study benchmarks the performance of the Orbitrap Astral mass spectrometer for label-free HCP analysis, comparing data-dependent acquisition (DDA, Top80) and data-independent acquisition (DIA, 4 m/z non-staggered windows) modes. We applied a statistically rigorous framework integrating a stable isotope-labeled HCP mixture for traceable quantification, entrapment-based empirical false discovery proportion estimation, deterministic protein inference, and stratified bootstrapping. Both acquisition modes demonstrated exceptional quantitative fidelity (R ² ≥ 0.99 for absolute abundance, total error within ±30% acceptance limits). DIA outperformed DDA in identifications, yielding 45% more proteins and 68% more peptides. Hierarchical Bayesian modeling revealed superior differential linearity in DIA (mean slope ≈ 1.0) compared to DDA (slope ≈0.8). Stratified bootstrap analysis confirmed linearity and accuracy across the dynamic range, with DIA achieving lower limits of quantification (0.6 ppm) versus DDA (1.6 ppm). While both workflows reliably quantified most high-risk HCPs, DIA provided expanded proteome coverage and enhanced fold-change precision. These findings validate the Orbitrap Astral as a high-fidelity platform for HCP analysis in both modes and establish a defensible, regulatory-aligned MS-based framework for routine use in quality control environments.