Estimation of ELISA results using a parallel curve analysis

Francis Bursa; Ann Yellowlees; Alka Bishop; Angela Beckett; Bassam Hallis; Mary Matheson

doi:10.1016/j.jim.2020.112836

Estimation of ELISA results using a parallel curve analysis

J Immunol Methods. 2020 Nov:486:112836. doi: 10.1016/j.jim.2020.112836. Epub 2020 Aug 20.

Authors

Francis Bursa¹, Ann Yellowlees², Alka Bishop³, Angela Beckett⁴, Bassam Hallis⁵, Mary Matheson⁶

Affiliations

¹ Quantics Biostatistics, Edinburgh, UK. Electronic address: [email protected].
² Quantics Biostatistics, Edinburgh, UK. Electronic address: [email protected].
³ Porton Biopharma Limited, Porton Down, UK. Electronic address: [email protected].
⁴ Porton Biopharma Limited, Porton Down, UK; Centre for Enzyme Innovation, University of Portsmouth, UK. Electronic address: [email protected].
⁵ Public Health England, Porton Down, UK. Electronic address: [email protected].
⁶ Public Health England, Porton Down, UK. Electronic address: [email protected].

PMID: 32827492
DOI: 10.1016/j.jim.2020.112836

Abstract

We introduce a new method for the analysis of enzyme-linked immunosorbent assay (ELISA) data. The new method can use data near the asymptotes and does not give undue weight to responses on the flatter parts of the dose-response curve. We apply it to simulated data and to two real-world assays and show it is more accurate and more precise than the traditional interpolation method. In particular, the new method works much better for very low-concentration samples for which the traditional method is often unable to give a result.

Keywords: Concentration estimation; ELISA; ELISA statistics; Immunoassay.

Publication types

Comparative Study

MeSH terms

Biomarkers / blood*
Computer Simulation
Data Interpretation, Statistical
Enzyme-Linked Immunosorbent Assay* / standards
Humans
Models, Statistical
Reference Standards
Reproducibility of Results

Substances

Biomarkers