Evidence map›Paper›PMID 26364776›Full record

ArticleCambridge quarterly of healthcare ethics : CQ : the international journal of healthcare ethics committees2015

The flaws and human harms of animal experimentation.

Aysha Akhtar

Abstract read
In one paragraph

Article in Cambridge quarterly of healthcare ethics : CQ : the international journal of healthcare ethics committees, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 224 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
224citing papers in PubMed, 2 pooled it
–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

224 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Importance of Systematic Reviews and Meta-analyses of Animal Studies: Challenges for Animal-to-Human Translation.Journal of the American Association for Laboratory Animal Science : JAALAS · 2020
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  15. Natural variation suggests candidate genes underlying Caenorhabditis elegans susceptibility to diverse toxicants.Toxicological sciences : an official journal of the Society of Toxicology · 2026
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164 more citing papers are in PubMed but not listed here.

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

1 author.

Aysha Akhtar

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nonhuman animal ("animal") experimentation is typically defended by arguments that it is reliable, that animals provide sufficiently good models of human biology and diseases to yield relevant information, and that, consequently, its use provides major human health benefits. I demonstrate that a growing body of scientific literature critically assessing the validity of animal experimentation generally (and animal modeling specifically) raises important concerns about its reliability and predictive value for human outcomes and for understanding human physiology. The unreliability of animal experimentation across a wide range of areas undermines scientific arguments in favor of the practice. Additionally, I show how animal experimentation often significantly harms humans through misleading safety studies, potential abandonment of effective therapeutics, and direction of resources away from more effective testing methods. The resulting evidence suggests that the collective harms and costs to humans from animal experimentation outweigh potential benefits and that resources would be better invested in developing human-based testing methods.

Indexed as

Animal RightsAnimal ExperimentationAnimalsAnimal WelfareDisease Models, AnimalDrug IndustryHumansToxicity Testsanimal ethicsanimal researchdrug developmenthuman ethicshuman healthmedical testing

Identifiers

PMID26364776
PMCPMC4594046

What OpenQuestion holds

Textmetadata
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.