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Related Concept Videos

Enzyme-Linked Immunosorbent Assay01:33

Enzyme-Linked Immunosorbent Assay

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In 1971, Peter Perlman and Eva Engvall developed an Enzyme-linked immunosorbent assay (ELISA or EIA). ELISA differs from western blot in that the assays are conducted in microtiter plates or in vivo rather than on an absorbent membrane.
There are many different types of ELISAs, but they all involve an antibody molecule whose constant region binds an enzyme, leaving the variable region free to bind its specific antigen.  Enzyme-substrate reaction allows the antigen to be visualized or...
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Interval estimation for concentration in the ELISA setting.

Matthew Stephenson1, Francis Bursa2, Christophe Ladroue2

  • 1Department of Mathematics & Statistics, University of New Brunswick - Saint John, 100 Tucker Park Road, P.O. Box 5050, Saint John, New Brunswick E2L 4L5, Canada; Quantics Biostatistics, Exchange Tower, 19 Canning Street, Edinburgh EH3 8EG, United Kingdom.

Journal of Immunological Methods
|August 8, 2021
PubMed
Summary
This summary is machine-generated.

Profile likelihood methods provide better concentration estimates for Enzyme-linked immunosorbent assays (ELISAs) compared to Wald intervals. These methods offer superior coverage and robustness in ELISA data analysis.

Keywords:
Concentration estimationELISAELISA statisticsHost cell proteinsInterval estimationProfile likelihood

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Area of Science:

  • Biochemistry
  • Immunology
  • Statistical analysis

Background:

  • Enzyme-linked immunosorbent assays (ELISAs) are widely used for quantifying biological substances.
  • Accurate interval estimation for non-linear dose-response models in ELISAs remains a challenge.
  • Traditional Wald-based interval estimates can exhibit poor coverage and invalid parameter boundaries.

Purpose of the Study:

  • To compare the performance of profile likelihood interval estimation with Wald-based intervals for ELISA concentration determination.
  • To evaluate the robustness of different interval estimation methods across various assay designs.

Main Methods:

  • A comprehensive simulation study was conducted.
  • Profile likelihood interval estimation procedures were compared against Wald-type intervals.
  • The focus was on interval estimation of concentration in the ELISA setting.

Main Results:

  • Profile likelihood methods demonstrated superior coverage compared to Wald intervals.
  • Profile likelihood intervals were more robust to variations in assay design.
  • Wald intervals showed limitations in accuracy and boundary adherence.

Conclusions:

  • Profile likelihood offers a more reliable approach for interval estimation in ELISA analyses.
  • These findings suggest a preferred method for improving the precision of concentration quantification in ELISAs.
  • The study highlights the limitations of Wald methods for complex biological assays.