ArticleEnvironmental health perspectives2012
Information Quality in Regulatory Decision Making: Peer Review versus Good Laboratory Practice.
Article in Environmental health perspectives, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed, 37 citations in OpenAlex.
- Evaluation of the Quality Decision-Making Practices Utilized by the Zambia Medicines Regulatory Authority Technical Committees.Pharmaceutical medicine · 2026Article
- Hypothesis-driven weight of evidence evaluation indicates ethylbenzene lacks endocrine disruption potential by EATS pathways.EXCLI journal · 2025Article
- Does GLP enhance the quality of toxicological evidence for regulatory decisions?Toxicological sciences : an official journal of the Society of Toxicology · 2016Article
- NIEHS/FDA CLARITY-BPA research program update.Reproductive toxicology (Elmsford, N.Y.) · 2015Review
- Taking financial relationships into account when assessing research.Accountability in research · 2013Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThere is an ongoing discussion on the provenance of toxicity testing data regarding how best to ensure its validity and credibility. A central argument is whether journal peer-review procedures are superior to Good Laboratory Practice (GLP) standards employed for compliance with regulatory mandates.
objectiveWe sought to evaluate the rationale for regulatory decision making based on peer-review procedures versus GLP standards.
methodWe examined pertinent published literature regarding how scientific data quality and validity are evaluated for peer review, GLP compliance, and development of regulations. DISCUSSION: Some contend that peer review is a coherent, consistent evaluative procedure providing quality control for experimental data generation, analysis, and reporting sufficient to reliably establish relative merit, whereas GLP is seen as merely a tracking process designed to thwart investigator corruption. This view is not supported by published analyses pointing to subjectivity and variability in peer-review processes. Although GLP is not designed to establish relative merit, it is an internationally accepted quality assurance, quality control method for documenting experimental conduct and data.
conclusionsNeither process is completely sufficient for establishing relative scientific soundness. However, changes occurring both in peer-review processes and in regulatory guidance resulting in clearer, more transparent communication of scientific information point to an emerging convergence in ensuring information quality. The solution to determining relative merit lies in developing a well-documented, generally accepted weight-of-evidence scheme to evaluate both peer-reviewed and GLP information used in regulatory decision making where both merit and specific relevance inform the process.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.