Evidence map›Paper›PMID 32579547›Full record

ArticlePloS one2020

Are in vitro and in silico approaches used appropriately for animal-based major depressive disorder research?

Constança Carvalho, Susana A M Varela, Tiago A Marques, Andrew Knight, Luís Vicente

Abstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Constança CarvalhoFaculdade de Ciências, Centro de Filosofia das Ciências, Universidade de Lisboa, Lisboa, Portugal.ORCID 0000-0002-6902-4241
Susana A M VarelaFaculdade de Ciências, cE3c - Centre for Ecology, Evolution and Environmental Changes, Universidade de Lisboa, Lisboa, Portugal.
Tiago A MarquesCentre for Research into Ecological and Environmental Modelling, University of St Andrews, St Andrews, Scotland.
Andrew KnightCentre for Animal Welfare, University of Winchester, Winchester, United Kingdom.
Luís VicenteFaculdade de Ciências, Centro de Filosofia das Ciências, Universidade de Lisboa, Lisboa, Portugal.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current paradigm for biomedical research and drug testing postulates that in vitro and in silico data inform animal studies that will subsequently inform human studies. Recent evidence points out that animal studies have made a poor contribution to current knowledge of Major Depressive Disorder, whereas the contribution of in vitro and in silico studies to animal studies- within this research area- is yet to be properly quantified. This quantification is important since biomedical research and drug discovery and development includes two steps of knowledge transferability and we need to evaluate the effectiveness of both in order to properly implement 3R principles (Replacement, Reduction and Refinement). Here, we used the citation tracking facility within Web of Science to locate citations of original research papers on in vitro and in silico related to MDD published identified in PubMed by relevant search terms. 67 publications describing target papers were located. Both in vitro and in silico papers are more cited by human medical papers than by animal papers. The results suggest that, at least concerning MDD research, the current two steps of knowledge transferability are not being followed, indicating a poor compliance with the 3R principles.

Indexed as

Major Depressive DisorderAnimal ExperimentationAnimalsBibliometricsBiomedical ResearchComputer SimulationHumansIn Vitro TechniquesResearch Design

Identifiers

PMID32579547
PMCPMC7313753

What OpenQuestion holds

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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.