Transferring SPE Method from Cartridges to 96-Well Plate Format. For maximizing sample throughput, the SPE protocol was transferred to 96-well plates (plate-based SPE) and performance was compared to the initially optimized cartridgebased SPE protocol. In total, 72% of all analytes fulfilled the criteria for "good" RE when using the cartridge-based protocol for extracting urine or plasma samples, and 86% and 90% of the analytes were classified as "good" in terms of SSE (Figure (A) and (C)). When using 96-well plates, 71% and 60% of the analytes achieved "good" REs while 76% and 78% of all analytes obtained "good" SSE in urine and plasma, respectively (Figure and). Most analytes with "good" REs using the cartridge-based workflow were also categorized as "good" using the 96-well plate workflow for the extraction of urine, whereas 96-well plates performed worse for the extraction of 12% of the analytes in plasma. Similarly, the cartridge-based protocol outperformed the plate-based SPE method in 10% of the cases in terms of matrix-induced SSE (Figure (C) and (D)). In total, around 25% of the analytes were poorly extracted from plasma and 20% from urine using the plate-based protocol and the observed discrepancies might be explained by differences in the manufacturing process, e.g., differences of SPE sorbent packing, or differences in sample handling when working with 96-well plates. In addition to weakly retained compounds (low-mass acids, see above), additional compounds with high background levels in plasma, such as mono-butyl phthalate or perfluorooctanoic acid (PFOA), were reported with "poor" RE. The performance of RE and SSE values was only marginally better when using cartridges compared to 96-well plates (see Figure ). Despite the slightly worse performance, the application of 96-well plates still holds promise for large-scale applications due to its relatively comparable performance to SPE cartridges combined with the notable improvement in throughput, and sample handling. A schematic representation of the SPE workflow based on 96-well plates is presented in Figure (A) and more details are in Table . Total analysis time of the 96-well plate-based SPE workflow was predicted for the analysis of 1000 samples, and time estimates were compared to our routinely used PPT protocol. The new platedbased SPE protocol allows extracting 1000 biological samples within 3 days, whereas the same amount of samples would require 29 days using our routinely used PPT workflow as shown in Table . Assessing the Potential of SPE for NTA and Suspect Screening. While systematic optimization and characterization of sample preparation methods for targeted (multi-analyte) assays can be performed easily, full-performance comparison for non-targeted applications is less straightforward. We aimed to characterize the applicability of the developed SPE method for NTA and suspect screening, by comparing performance to a well-established protein precipitation method (PPT). Thus, extracts obtained with PPT and 96-well plate-based SPE were analyzed using LC-HRMS(/MS), see Figure (B) and results were compared on feature level. Extracts of NIST SRM 1950 (plasma) and SRM 3672 (urine) were analyzed on a Thermo Exploris 480 HRMS instrument. Peak picking, feature alignment and compound annotation were performed using MS-DIAL together with reference mass spectra from MassBank of North America (MoNA). Relative intensities were determined for annotated features as the area under curve (AUC), and results of the PPT and SPE workflows were compared for annotated or identified features. Values of fold change (FC > 2) and significance (pvalue < 0.05) were analyzed using MetaboAnalyst . Generally, for SRM 1950 (plasma), 50% of the annotated features showed significantly higher AUCs (FC > 2, p-value < 0.05) when using the PPT workflow (see Table ). Yet, SPE extraction resulted in significantly higher signal intensities for 13% of the features and 36% of the features not significantly affected by the choice of sample preparation. For SRM 3672 (urine), we observed significantly higher AUCs in PPT in 32% of the cases, whereas 10% were significantly enhanced using SPE, and 58% of all annotated features were not significantly different between the two protocols (Table ). Figure ) show the comparison of relative feature intensities by plotting fold changes as a function of the retention time, whereas results are discussed based on compound class in Figure (C). In SRM 1950 (plasma), we observed higher relative intensities for polar compounds, mainly amino acids and organic acids with RT <3 min, which is well in line with the results from the targeted assay. Additionally, several nonpolar features, mainly lipids with RT > 10 min were higher in the PPT extracts. Similar results were observed for SRM 3672 urine, with polar compounds including amino acids and derivatives or organic acids with RT < 3 min showing higher AUCs in PPT extracts compared to SPE. However, some key low-abundant biomarkers were observed with significantly higher AUCs using SPE, like nicotine (SRM3672 (urine) and cocaine in SRM 1950 (plasma)in Figure . Interestingly, there was no significant difference in AUCs between PPT and SPE for major metabolites of nicotine and cocaine such as benzoylecgonine for cocaine, and hydroxycotinine and cotinine for nicotine. Despite these differences, comparable results were obtained for a large fraction of features from different compound classes including amino acids, carnitines, natural products, or synthetic compounds such as medical drugs or pesticides in urine and plasma. For instance, 16 drugs were detected with comparable AUCs in PPT and SPE extracts of SRM 3672 urine. Similarly, twelve drug-related features were detected with comparable AUCs using both methods. In conclusion, the PPT workflow offered more extensive coverage of annotated features. In human urine, the results were comparable with 58% of annotated features overlapping between SPE and PPT extractions. For plasma samples, the PPT extraction provided broader feature coverage, particularly for endogenous polar metabolites, while SPE extraction may focus more on low-abundant exogenous compounds but led, as expected, to the loss of several metabolites including amino acids and organic acids. Limitations While the established workflow is effective for most analytes in targeted multi-class analysis and performs comparably well for a relative majority of analytes in NTA of human samples, several limitations remain. It needs to be considered that the analytes selected for method optimization, while highly diverse and comprehensive, still represent only a limited subset of the known chemical exposome. Although special emphasis was paid on covering a wide range of physicochemical properties during analyte selection, this can always be expanded for exposome-scale work. A broader selection of compounds and wider chemical coverage would be needed for a truly holistic representation of the exposome in future work. Moreover, certain analytes, especially polar acidic compounds, are partly lost during the SPE process due to weak retention by the sorbent, which was expected. Although different workflows could address these specific shortcomings by targeting particular sets of analytes, conducting multiple measurements to gather sufficient information is time-consuming. Therefore, achieving favorable performance in terms of comprehensive analyte coverage, efficient cleanup, and minimal time consumption simultaneously is not always feasible and not always required .