The diagnostic potential of plasma proteomes is consistently constrained by challenges of high abundant proteins masking the presence of clinically-relevant proteins. The dynamic range of this biofluid exceeds 10 orders of magnitude, therefore profiling low abundant proteins in plasma has often necessitated complex sample preparation (i.e depletion or fractionation), notably increasing processing times both in terms of sample handling and MS analysis. Meanwhile, DIA approaches have elevated standards for unbiased, precise and reproducible quantification in proteome analyses. For plasma, these benefits of increased depth alongside decreased missingness make DIA approaches an attractive strategy towards desired workflows achieving rapid and comprehensive quantification. More recently, dia-PASEF acquisition methods on the timsTOF pro mass spectrometer have coupled ion mobility separation data to DIA, adding the ‘4th dimension’ via measurement of collisional cross sections (CCS) values, demonstrably boosting library-based matching. Consequently, we have explored dia-PASEF approaches for plasma in terms of throughput and depth, including benchmarking library and library-free approaches leveraging DIA-NN and FragPipe software [1]. We have acquired plasma proteomes using a method of two windows in each diaPASEF scan, with window placement overlapping the diagonal scan line for doubly and triply charged peptides in the m/z – ion mobility plane across 16 × 25 m/z precursor isolation windows (32 windows) in both longer (90 min) and shorter (30 min) LC gradients. By using high-pH fractionation to generate both cohort-specific and cohort-independent plasma libraries, we have also explored how these can be implemented to maximise identification and proteome depth and compared their performance to library-free methods. Lastly, we are exploring protein separation strategies prior to dia-PASEF which widen the dynamic range of proteins captured in a single LC-MS/MS run, further extending our sampling depth across the dynamic range of plasma. Together, these demonstrate dia-PASEF approaches can maximize sample throughput alongside improvements in depth in these challenging proteomes.