Evidence map›Paper›PMID 37715073›Full record

ArticleThe AAPS journal2023

A Case Study for Critical Reagent Qualification for Ligand Binding Assays Using Equivalence Test Methodology.

Nancy A Niemuth, Cheryl A Triplett, Michael S Anderson, Karen A Sankovich, Thomas L Rudge

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Article in The AAPS journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Nancy A NiemuthBattelle Health Analytics, Columbus, OH, USA. niemuth616@gmail.com.ORCID 0000-0001-5166-7743
Cheryl A TriplettBattelle Health Analytics, Columbus, OH, USA.
Michael S AndersonBattelle Health Analytics, Columbus, OH, USA.
Karen A SankovichBattelle Biomedical Research Center, West Jefferson, OH, USA.
Thomas L RudgeBattelle Biomedical Research Center, West Jefferson, OH, USA.

Funding

NIAID NIH HHS HHSN272201200003I
6 · The paper itself

Abstract

Qualifying critical reagents in ligand binding assays by parallel testing of current and candidate reagent lots is recommended by regulatory agencies and industry groups, but specific guidance on the format of reagent qualification experiments is limited. Equivalence testing is a statistically sound approach that is consistent with the objective of critical reagent qualification. We present power analysis for equivalence regions ranging from 1.25- to 1.5-fold multiples of the GM ratio (centered on 1) of current and candidate lots, over a range of assay variability from 5 to 30% coefficient of variation (CV). A 1.25-fold equivalence region can be tested using 6 to 12 plates per lot for assays with up to 15% CV but is not practical for more variable assays. For these assays, wider equivalence regions are justified so long as care is taken to avoid assay drift and the assay remains suitable for the intended use. The equivalence test method is illustrated using historical data from passing and failing reagent qualification experiments. Simulation analysis was performed to support the design of qualification experiments using 6, 12, or 18 plates per lot over a broad range of assay variability. A challenge in implementing the equivalence test approach is selecting an appropriate equivalence region. Equivalence regions providing 90% power using 12 plates/lot were consistent with 1.5σ bounds, which are recommended for equivalence testing of critical quality attributes of biosimilars.

Indexed as

Biosimilar PharmaceuticalsBiological AssayComputer SimulationLigandsBiosimilar PharmaceuticalsLigandscritical reagent qualificationequivalence regionequivalence testpowersample size

Identifiers

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.