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Protein Quantification Platforms For Use In Critical Care Precision Medicine Trials: A Scoping Review
Ross R McMullan1, Donovan Campbell1, Anna Rea1
1Wellcome-Wolfson Institute for Experimental Medicine, Queen's University Belfast, Northern Ireland, United Kingdom.
Objectives:
Among precision medicine approaches in critical care, protein biomarker quantification offers a timely and reproducible route to patient subtyping, but the landscape of automated platforms suitable for near-patient deployment remains unclear. This review aimed to identify available automated platforms for quantitative measurement of human protein biomarkers in blood, serum, or plasma, in order to support planning for precision medicine trials.
Data Sources:
PubMed, Embase, and Espacenet were searched for eligible sources. Relevant company correspondence was also included where available.
Study Selection:
Publication reports, patent reports, and company correspondence were eligible if they described commercially available platforms meeting a prespecified definition of automation for quantitative measurement of one or more human protein biomarkers in blood, serum, or plasma.
Data Extraction:
Data were extracted on device model, manufacturer, and analytes measured. Eligible devices were extracted as separate device records, including multiple devices reported within a single source.
Data Synthesis:
Overall, 228 sources were included, comprising 211 publication reports, 14 patent reports, and three company correspondence reports. Publications contributed 256 publication-derived device records representing 74 distinct automated device models from 34 manufacturers. The most frequently represented devices were Ella (n = 48), LUMIPULSE G1200 (n = 25), LUMIPULSE G600II (n = 17), cobas e 411 (n = 13), and Simoa HD-X (n = 12). Multiplex capability was identified for eight devices in included publications, with two additional multiplex-capable platforms identified through company correspondence. Across publication-derived device records, inflammatory and neurologic biomarkers predominated. The most frequently reported inflammatory biomarkers were procalcitonin (n = 36), interleukin (IL)-6 (n = 35), tumor necrosis factor (TNF)-α (n = 22), and IL-10 (n = 14). The most frequently reported neurologic biomarkers were neurofilament light chain (n = 34), p-tau217 (n = 31), Aβ42 (n = 29), Aβ40 (n = 27), and p-tau181 (n = 27).
Conclusions:
Automated platforms for quantitative protein biomarker measurement span numerous devices and manufacturers, but multiplex capability remains limited. More standardized device-level reporting would strengthen platform selection for biomarker-enabled trials and future clinical implementation.
