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. 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. 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 the performance of the 96-well plate method was reduced for 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 (see Figure ). In total, around 25% of the analytes were poorly extracted from plasma and 20% from urine using the plate-based protocol. The observed discrepancies might be explained by differences in the manufacturing process, including 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 in plasma, such as p-hydroxybenzoic acid (pOHBA), monobutyl phthalate (MBP), 2-naphthol (2-Napht) or perfluorooctanesulfonic acid (PFOS), were reported with "poor" RE. This was due to their background levels being 2 to 10 times higher than the spiked levels. In general, RE and SSE was only slightly better when using cartridges compared to 96-well plates (see Figure ). Despite the slightly reduced performance in selected examples, the application of 96well plates still holds promise for large-scale applications due to its comparable performance to the cartridges in combination with notable improvement in sample throughput, and handling. A schematic representation of the SPE workflow based on 96-well plates is presented in Figure and more details are given in Table . To assess the full potential for high-throughput applications, the 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 plate-based SPE protocol allows extracting 1000 biological samples within 3 days, whereas the same amount of samples would require 29 days using a 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 96well plate-based SPE were analyzed using LC-HRMS(/MS) (see Figure ), and results were compared on the feature level. Extracts of NIST SRM 1950 (plasma) and SRM 3672 (urine) were analyzed on an LC-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 and identified features. Values of fold change (FC > 2) and significance (pvalue < 0.05) were analyzed using MetaboAnalyst . Approximately 50% of the annotated features detected in SRM 1950 (plasma), showed significantly higher AUCs (FC > 2, pvalue < 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 were not significantly affected by the choice of sample preparation. For SRM 3672 (urine), we observed significantly higher AUCs using PPT in 32% of cases, whereas 10% were significantly enhanced using SPE, and 58% of annotated features were not significantly different (Table ). Figure ) shows results of the comparison of relative feature intensities as fold changes of AUC as a function of the RT, whereas results are summarized on the compound class level in Figure (C). For SRM 1950 (plasma), higher relative signal intensities in PPT extracts were observed 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 lowabundance biomarkers were observed with significantly higher AUCs using SPE, like nicotine in urine (SRM3672) and cocaine in plasma (SRM 1950, see Figure ). Interestingly, no significant differences between PPT and SPE were observed 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 and diverse compound classes including amino acids, carnitines, natural products, or synthetic compounds such as medical drugs and pesticides. 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 in the plasma with comparable AUCs using both methods. In conclusion, the PPT workflow offers wider coverage of annotated features, but comparable results were obtained for many annotated compounds. In urine, the results were comparable for 58% of annotated features detected in extracts using both methods. However, PPT extraction provided broader feature coverage for the analysis of plasma samples, particularly endogenous polar metabolites, whereas SPE extraction improved the detection of lowabundance exogenous compounds at the cost of losing several polar metabolites. Limitations While the established workflow is effective for most analytes in targeted multi-class analysis of human samples and performs comparably well for a relative majority of analytes in NTA, several limitations remain. The analytes selected for method optimization were highly diverse and yet still represent only a limited subset of the known chemical exposome. Although analytes were selected with a special emphasis on covering a wide range of physicochemical properties, coverage needs to be further expanded for exposomescale 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 .