ArticleJournal of immunological methods2026
A semi-automated ELISA workflow for SARS-CoV-2 Nucleocapsid IgG detection significantly improves throughput and reduces hands-on time.
Article in Journal of immunological methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundEnzyme-linked immunosorbent assay (ELISA) is widely used in clinical and research laboratories for applications such as disease surveillance, immunogenicity assessment, and vaccine evaluation. Traditional manual ELISA workflows, however, are labor-intensive, time-consuming, and susceptible to operator-dependent variability, which can limit throughput and reproducibility. Incorporating semi-automation into established protocols offers a potential strategy to improve efficiency while maintaining analytical performance.
methodsA validated manual ELISA protocol for SARS-CoV-2 Nucleocapsid IgG detection was adapted into a semi-automated workflow using an automated multichannel pipette, microplate washer-dispenser, and plate stacker to streamline key steps. Performance was compared across 10 manual and 30 semi-automated plates. Sixteen pre-characterized serum samples were analyzed to evaluate precision, accuracy, and overall assay validity, and internal controls were monitored to ensure compliance with predefined acceptance criteria.
resultsThe semi-automated workflow doubled assay throughput from 6 to 12 plates per analyst per day and reduced hands-on time by 75% (from 5.5 h to 1 h). Internal controls for all 40 plates met established acceptance ranges. Precision, measured as relative standard deviation, remained below 25% for all samples, and accuracy, expressed as percent error, remained below 20%. No loss of analytical performance was observed when transitioning from manual to semi-automated processing.
conclusionSemi-automation markedly increases ELISA throughput and reduces hands-on time while maintaining precision, accuracy, and overall assay validity. These results underscore its feasibility as an efficient workflow enhancement with potential for broader application across diverse ELISA platforms pending further validation.
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