High-Multiplex Proteomics: Analytical Trade-Offs and a Practical Selection Framework for Emerging Platforms

Classical liquid chromatography-tandem mass spectrometry (LC-MS/MS) remains a cornerstone of proteomics, but deep profiling of complex biofluids is constrained by the extreme dynamic range of protein abundance and low sample throughput. Emerging high-multiplex platforms address these limitations through distinct high-throughput configurations, including antibody-based proximity assays, modified aptamers, nanoparticle-assisted mass spectrometry, and digital single-molecule immunoassays. Despite their discovery potential, these technologies operate within alternative bottom-up or affinity-based frameworks, meaning that they are not interchangeable. Quantitative measurements of nominally identical proteins frequently show poor to moderate cross-platform agreement, reflecting fundamental differences in chemistry, epitope accessibility, matrix susceptibility, genetic variants, and peptide-level protein inference. Crucially, because these platforms generally yield aggregate quantitative readouts, they typically average across the proteoform spectrum, limiting their ability to differentiate whether an abundance shift is driven by specific splice variants, localized post-translational modifications, or a uniform increase in the protein's overall concentration. This review provides a balanced, decision-oriented comparison of the Olink Proximity Extension Assay, SomaLogic SomaScan, Seer Proteograph and Quanterix Simoa, delineating their operational utility alongside their respective technical limitations. We propose a practical framework to guide platform selection based on the specific biological question, cohort size, and required structural resolution, while evaluating strategies to enhance cross-platform reproducibility via standardized reference matrices, structure-informed interpretation, and multi-tiered validation workflows.