Evidence map›Paper›PMID 38438748›Full record

ReviewLab animal2024

A minimal metadata set (MNMS) to repurpose nonclinical in vivo data for biomedical research.

Anastasios Moresis, Leonardo Restivo, Sophie Bromilow, Gunnar Flik, Giorgio Rosati, Fabrizio Scorrano, Michael Tsoory, Eoin C O'Connor, Stefano Gaburro, Alexandra Bannach-Brown

Abstract readReview
In one paragraph

Review in Lab animal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 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

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  12. Validation framework forFrontiers in toxicology · 2024
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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

10 authors.

Anastasios Moresis *Roche Pharma Research and Early Development, Data & Analytics, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland.ORCID 0000-0001-6688-3238
Leonardo Restivo *Neuro-Behavioral Analysis Unit, Faculty of Biology & Medicine, University of Lausanne, Lausanne, Switzerland.
Sophie BromilowGroup Legal Department, F. Hoffmann-La Roche Ltd, Basel, Switzerland.ORCID 0009-0000-5880-5547
Gunnar FlikDiscovery, Charles River Laboratories, Groningen, the Netherlands.
Giorgio RosatiTecniplast S.p.A., Buguggiate, Italy.
Fabrizio ScorranoEmerging Technologies, Comparative Medicine, Novartis International AG, Basel, Switzerland.
Michael TsooryBehavioral and Physiological Phenotyping Unit, Department of Veterinary Resources, Weizmann Institute of Science, Rehovot, Israel.
Eoin C O'ConnorRoche Pharma Research and Early Development, Neuroscience & Rare Diseases, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland. eoin.oconnor@roche.com.ORCID 0000-0002-7810-1915
Stefano GaburroTecniplast S.p.A., Buguggiate, Italy. stefano.gaburro@tecniplast.it.ORCID 0000-0001-9297-3472
Alexandra Bannach-BrownQUEST Center for Responsible Research, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany. Alexandra.Bannach-Brown@charite.de.ORCID 0000-0002-3161-1395

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although biomedical research is experiencing a data explosion, the accumulation of vast quantities of data alone does not guarantee a primary objective for science: building upon existing knowledge. Data collected that lack appropriate metadata cannot be fully interrogated or integrated into new research projects, leading to wasted resources and missed opportunities for data repurposing. This issue is particularly acute for research using animals, where concerns regarding data reproducibility and ensuring animal welfare are paramount. Here, to address this problem, we propose a minimal metadata set (MNMS) designed to enable the repurposing of in vivo data. MNMS aligns with an existing validated guideline for reporting in vivo data (ARRIVE 2.0) and contributes to making in vivo data FAIR-compliant. Scenarios where MNMS should be implemented in diverse research environments are presented, highlighting opportunities and challenges for data repurposing at different scales. We conclude with a 'call for action' to key stakeholders in biomedical research to adopt and apply MNMS to accelerate both the advancement of knowledge and the betterment of animal welfare.

Indexed as

Biomedical ResearchMetadataAnimalsAnimal WelfareReproducibility of Results

Identifiers

PMID38438748
PMCPMC10912024

What Socratic 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 Socratic graph.