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Enzyme-Linked Immunosorbent Assay

Enzyme-Linked Immunosorbent Assay

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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Application of DOE to ELISA Robustness and Ruggedness Assessment.

Thy Follmer¹, Seth Clark¹, Thorsten Verch²

¹Merck & Co., Inc., Rahway, New Jersey, USA.

The AAPS Journal

|April 3, 2025

Summary

Statistical Design of Experiments (DOE) efficiently assessed vaccine ELISA robustness. This method identified critical factors impacting assay performance, reducing risks and improving reliability with minimal experimental runs.

Keywords:

DOE ELISA design of experiments robustness

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Area of Science:

Analytical Chemistry
Biotechnology
Pharmaceutical Sciences

Background:

Complex immunoassays, like ELISA, are susceptible to robustness and ruggedness issues.
Systematic performance assessment and control strategies are crucial for mitigating assay risks.
Evaluating numerous factors and their interactions poses a significant experimental challenge.

Purpose of the Study:

To apply statistical Design of Experiments (DOE) for efficient robustness evaluation of a vaccine potency ELISA.
To identify key factors influencing assay performance and implement control strategies.
To overcome the experimental challenges posed by a large number of factors and their interactions.

Main Methods:

Selected test factors based on development data, scientific expertise, and common variability sources.
Utilized a 16-run Resolution III Design of Experiments (DOE) within laboratory constraints.
Analyzed DOE data through visual inspection of concentration-response curves and statistical modeling of key assay parameters.

Main Results:

DOE enabled efficient evaluation of 15 factors within a limited 16-run design.
Initial factor confounding was managed by iterative model refinement using statistical and scientific judgment.
Identified a significant impact of plate manufacturer, interacting with coating concentration and incubation time.

Conclusions:

DOE is a powerful tool for assessing immunoassay robustness, even with numerous factors.
The selected DOE strategy successfully identified critical factors impacting vaccine ELISA performance.
This systematic approach enhances assay reliability and reduces associated risks in biopharmaceutical development.