Proteomics platforms are evolving rapidly, with advances in mass spectrometry and affinity-based approaches expanding what researchers can detect and at what scale. As the field moves toward deeper proteome coverage and clinical applications, scientists face an increasingly complex landscape of tools. This article will explore how researchers are navigating these choices to find the right platform for their work.
The systematic characterization of the human proteome has established itself as a fundamental pillar of precision medicine, providing dynamic insights that structural genomics cannot capture in isolation.1 Historically, there is a divergence between the unbiased depth of mass spectrometry and the targeted sensitivity and high throughput of antibody-based assays. However, today, these technological boundaries are blurring due to rapid, parallel innovations on both fronts. This convergence is driving increasing clinical applications, satisfying the critical need for highly scalable tools to conduct proteomic studies.
The evolution of mass spectrometry
Mass spectrometry (MS) is a traditional technique used since the early 20th century to measure the mass-to-charge ratio of ions.2 The primary benefit of mass spectrometry lies in its capacity for comprehensive, unbiased characterization, enabling the precise detection of post-translational modifications (PTMs), splice variants, and truncated protein isoforms. In recent years, mass spectrometry has reinvented itself to compete in throughput, sensitivity, and depth with other analytical strategies.
Next-generation data-independent acquisition (DIA) mass spectrometry platforms have achieved scanning speeds and ion transfer efficiencies capable of sequencing tens of thousands of peptides per sample.3 For instance, Orbitrap Astral from Thermo Fisher Scientific and timsTOF Ultra/ Automated Ion Profiling (AIP) systems from Bruker, are recent hardware breakthroughs. Thermo Fisher Scientific expanded its Orbitrap platform with deep learning algorithms and enhanced dynamic range for complex sample analysis.4 Simultaneously, Bruker’s advances in ion mobility improved molecular separation and fragmentation, enhancing label-free protein identification and quantification at industrial-scale throughput.4 A leap in depth for Orbitrap Astral and the timsTOF Ultra relative to the conventional DDA methodology have been reported, enabling the quantification of more than 13,000 proteins while reducing the required sample mass by 66%.3
While these next-generation platforms have redefined high-throughput bulk proteomics, the physical principles of mass spectrometry have also been adapted to address cellular heterogeneity and spatial organization. Standard BioTools further advanced mass cytometry with its CyTOF and Hyperion platforms. CyTOF combines isotope-tagged antibodies with time-of-flight mass spectrometry to enable high-parameter single-cell profiling, overcoming fluorescence limitations. Its evolution into imaging mass cytometry (Hyperion) enables multiplexed spatial mapping of proteins within tissue architecture.
Despite these innovations, mass spectrometry is faced with substantial unit costs for instrument acquisition, requirements for highly specialized personnel, and robust computational infrastructure to process large-scale proteomic datasets.1 Regarding this challenge, Daniel Hornburg, Vice President of Biomarkers & Precision Medicine at Bruker Daltonics, says the company is making mass spectrometry more accessible, particularly for non-expert users. “For example, our AI-based quality control system, TwinScape™, creates a digital twin of the entire MS pipeline, learning to predict and mitigate deviations before they affect results. Ultimately, MS should become easier to use and more amenable to the clinical routine.”
The scalable expansion of affinity reagents
Multiplex affinity platforms use coupled nucleic acids to translate protein binding into a digital sequencing or hybridization readout.5 Antibody- and aptamer-based affinity platforms have expanded their multiplex capacity beyond 10,000 analytes, enabling population studies of unprecedented scale.6,7
The Olink Proximity Extension Assay (PEA) technology, available in targeted formats (Target 96 and Target 48) based on high-precision qPCR readout, or in the global proteomic discovery format (Explore HT) with NGS readout, offers high specificity by using pairs of antibodies with complementary oligonucleotide tails. The signal is generated only under strict proximity hybridization, which substantially mitigates the non-specific cross-reactivity and binding events that typically plague traditional antibody-based assays.
SomaScan technology uses chemically modified aptamers composed of synthetic single-stranded DNA oligonucleotides enhanced with hydrophobic residues to extend the residence time of the protein-reagent complex and reduce the dissociation rate, allowing for stringent washes to remove non-specific interactions. Ultimately, these modifications yield exceptional reproducibility, high data completeness, and minimal missing values across large-scale cohorts.8
Finally, NULISA (Nucleic Acid-Linked Immuno-Sandwich Assay) technology focus on the ultra-sensitive quantification of ultra-low abundance analytes, such as cytokines and chemokines, using a dual mechanism of affinity capture and magnetic purification to remove excess reagents prior to amplification and sequencing.9 Comparative analyses reveal robust genetic concordance between Olink Explore and SomaScan, highlighting SomaScan’s data completeness.7 Moreover, NULISA present an excellent precision.8
However, a critical caveat in affinity-based approaches lies in protein-altering variants (PAVs), which modify epitopes and affect the physical affinity of antibodies or aptamers.7 In this regard, Luis Maurício Trambaioli da Rocha e Lima, Full Professor at the Federal University of Rio de Janeiro (UFRJ) and coordinator of the Pharmaceutical and Nutritional Biotechnology Laboratory, highlights that “affinity-based platforms excel at cost-effective, high-throughput and cohort screening while mass spectrometry remains non-negotiable for absolute quantification, PTM mapping, and regulatory validation.”
Choosing the right technology
In this rapidly expanding landscape, selecting the ideal proteomic platform has become a critical, multi-factorial decision, directly influencing accuracy, data missingness, operational costs, and data reproducibility. Experimental design now demands a deep understanding of the biochemical and statistical nuances that underpin each technology.5
Professor Maurício believes that “choosing a platform is never all-or-nothing and it relies on strategic questioning if the study is hypothesis-driven or discovery-based, if it prioritizes proteomic depth or cohort size and what are the matrix, dynamic range, and regulatory needs. Mauricio says that “Ultimately, the choice depends on your study design, as affinity platforms and mass spectrometry should be treated as complementary, not competing, tools.”
A laboratory or clinical consortium’s final decision on which proteomic platform to adopt must be guided by an analytical decision matrix. Professor Maurício sees the future of proteomics as a complementary workflow—“The future lies in combining technologies strengths. Affinity-based platforms are ideally suited for high-throughput screening and hypothesis generation in large cohorts, while mass spectrometry provides orthogonal validation and structural characterization of the most promising targets.” Ultimately, the best platform is defined not by the number of proteins it measures, but by its ability to answer the biological or clinical question.
References
1. Aebersold R, Mann M. Mass-spectrometric exploration of proteome structure and function. Nature. 2016;537(7620):347-355. doi:10.1038/nature19949.
2. Gross, J. H. (2017). Mass Spectrometry: A Textbook. Springer.
3. Blasco Tavares Pereira Lopes F, Schlatzer D, Sudhadevi T, et al. What Does Next-Generation Mass Spectrometry Offer for Proteomics? A Comprehensive Platform Comparison. J Proteome Res. 2026;25(4):1929-1940. doi:10.1021/acs.jproteome.5c01007.
4. Corona A. Mass spectrometry platforms push deeper into proteomics and biopharma at ASMS 2026. Drug Discovery News. Published June 24, 2026. Accessed July 15, 2026. https://www.drugdiscoverynews.com/ma...sms-2026-17277.
5. Cai X, Geyer PE, Perez-Riverol Y, et al. A standardized framework for circulating blood proteomics. Nat Genet. 2025;57(10):2371-2380. doi:10.1038/s41588-025-02319-7.
6. Rooney MR, Chen J, Ballantyne CM, et al. Correlations Within and Between Highly Multiplexed Proteomic Assays of Human Plasma. Clin Chem. 2025;71(6):677-687. doi:10.1093/clinchem/hvaf030.
7. Wang B, Pozarickij A, Mazidi M, et al. Comparative studies of 2168 plasma proteins measured by two affinity-based platforms in 4000 Chinese adults. Nat Commun. 2025;16(1):1869. Published 2025 Feb 21. doi:10.1038/s41467-025-56935-
8. Candia J, Fantoni G, Delgado-Peraza F, et al. Variability of 7K and 11K SomaScan Plasma Proteomics Assays. J Proteome Res. 2024;23(12):5531-5539. doi:10.1021/acs.jproteome.4c00667
9. Feng W, Beer JC, Hao Q, et al. NULISA: a proteomic liquid biopsy platform with attomolar sensitivity and high multiplexing. Nat Commun. 2023;14(1):7238. Published 2023 Nov 9. doi:10.1038/s41467-023-42834-x
About the author: Luiza Erthal, Ph.D., is a former biomedical scientist who found her passion in communicating science in different formats. She graduated in Biomedical Sciences in 2014 (UFRJ- Brazil), then she completed a Masters in Biochemistry in 2016 (UFRJ-Brazil) and a Ph.D. in Pharmaceutical Sciences in 2021 (TCD-Ireland). She works as a freelance medical writer writing for blogs, health & science companies, and universities. She loves to talk about science and share research findings with other people. Her mission is to write about science to empower people and make their lives better.