The plasma proteome provides a comprehensive snapshot of an individual’s physiological state and is widely used to study human health and disease. The ready availability and informative nature of plasma make it an invaluable resource for the discovery of new biomarker proteins. Mass spectrometry (MS) is the gold standard for proteome analysis, due to its unparalleled sensitivity, specificity and ability to identify and quantify thousands of proteins simultaneously. Despite its immense potential, MSbased plasma proteomics faces several significant challenges, including the complexity and dynamic range of the plasma proteome. The wide dynamic range – up to 12 orders of magnitude – limits access to the full proteome, as low abundance proteins are masked by more abundant species. Sophisticated sample preparation techniques are therefore required to enrich low abundance proteins and ensure in-depth and accurate proteome profiling. However, manual processing of large sample cohorts requires considerable hands-on time, which can slow down the speed of studies and creates the risk of human error. Automation addresses these challenges to ensure sufficient throughput for large cohorts, offering both scalability and reproducible results.
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