Evidence map›Paper›PMID 35867862›Full record

ArticleALTEX2023

Technical framework for enabling high quality measurements in new approach methodologies (NAMs).

Elijah J Petersen, John T Elliott, John Gordon, Nicole C Kleinstreuer, Emily Reinke, Mattias Roesslein, Blaza Toman

Abstract readEditorial
In one paragraph

Article in ALTEX, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. New approach methodologies (NAMs) for theFrontiers in toxicology · 2024
    Review
  7. Current Perspectives in Antiviral Research.International journal of molecular sciences · 2023
    Article
  8. Review
  9. Review
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

7 authors.

Elijah J PetersenNational Institute of Standards and Technology (NIST), Gaithersburg, MD, USA.
John T ElliottNational Institute of Standards and Technology (NIST), Gaithersburg, MD, USA.
John GordonUS Consumer Product Safety Commission, Rockville, MD, USA. jgordon@cpsc.gov.
Nicole C KleinstreuerNational Institute of Environmental Health Sciences, National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, Research Triangle Park, NC, USA.
Emily ReinkeU.S. Army Public Health Center, Aberdeen Proving Ground, MD, USA.
Mattias RoessleinEmpa, Swiss Federal Laboratories for Material Testing and Research, Particles-Biology Interactions Laboratory, St. Gallen, Switzerland.
Blaza TomanNational Institute of Standards and Technology (NIST), Gaithersburg, MD, USA.

Funding

Scientific Cyberinfrastructure Research ProgramZIAES103385 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI WALKER, VICKIE · 2022 to 2025
$17.4M
Research Operations Supporting the National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological MethodsZICES103386 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI HOGBERG-DURDOCK, HELENA · 2022 to 2025
$3.3M
Intramural NIST DOC 9999-NIST
6 · The paper itself

Abstract

New approach methodologies (NAMs) are in vitro, in chemico, and in silico or computational approaches that can potentially be used to reduce animal testing. For NAMs that require laboratory experiments, it is critical that they provide consistent and reliable results. While guidance has been provided on improving the reproducibility of NAMs that require laboratory experiments, there is not yet an overarching technical framework that details how to add measurement quality features into a protocol. In this manuscript, we discuss such a framework and provide a step-by-step process describing how to refine a protocol using basic quality tools. The steps in this framework include 1) conceptual analysis of sources of technical variability in the assay, 2) within-laboratory evaluation of assay performance, 3) statistical data analysis, and 4) determination of method transferability (if needed). While each of these steps has discrete components, they are all inter-related, and insights from any step can influence the others. Following the steps in this framework can help reveal the advantages and limitations of different choices during the design of an assay such as which in-process control measurements to include and how many replicates to use for each control measurement and for each test substance. Overall, the use of this technical framework can support optimizing NAM reproducibility, thereby supporting meeting research and regulatory needs.

Indexed as

Animal Testing AlternativesAnimalsReproducibility of Resultsbasic quality toolsBenchMarks seriesin vitro methodsreliabilityreproducibilitystandardization

Identifiers

PMID35867862
PMCPMC12431630

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.