Residual host cell proteins (HCPs) in therapeutic proteins pose a persistent challenge to detect due to their low abundance and wide dynamic range relative to the drug substance. To address this, we developed a "deep field scan" liquid chromatography tandem mass spectrometry (LC-MS/MS) method that enhances HCP detection without sample enrichment or clean-up, by leveraging an automated, cumulative target mass exclusion list and iterative data acquisition. Built on the Thermo Orbitrap AcquireX platform, this method optimizes MS efficiency by reducing redundant peptide sampling and improving MS/MS spectral quality, enabling higher-confidence HCP identification. Applying this method to NISTmAb demonstrated superior performance over traditional top10 data-dependent acquisition (DDA), confirming its viability as an alternative to native digest for monoclonal antibodies (mAbs). More importantly, its compatibility with non-antibody (non-mAb) biologics broadens its usage across diverse therapeutic modalities. Additionally, we established a benchmark HCP library from three additional commercial antibody standards, providing a valuable resource for cross-comparison within the HCP research community. By offering an automated and adaptable workflow, this method represents a novel and notable advancement in biologics impurity HCP characterization, supporting more efficient and comprehensive data collection for therapeutic protein development.