Evidence map›Paper›PMID 42182927›Full record

ArticleFrontiers in veterinary science2026

Unified framework for human and veterinary antibiotics: mapping international drug classifications (ATC and ATCvet) to support antimicrobial resistance research.

Mélanie Daligault, François Caron, Albertine Leon, Julien Grosjean

Abstract read
In one paragraph

Article in Frontiers in veterinary science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Mélanie DaligaultDYNAMICURE UMR 1311, Department of Digital Health, CHU Rouen, Univ Rouen Normandie, Rouen, France.
François CaronDYNAMICURE UMR 1311, Department of Infectious Diseases, CHU Rouen, Univ Rouen Normandie, Rouen, France.
Albertine LeonResearch Department, LABÉO, Saint-Contest, France.
Julien GrosjeanAIMS, Department of Digital Health, CHU Rouen, Univ Rouen Normandie, Rouen, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antimicrobial resistance (AMR) presents a global challenge requiring a One Health approach that integrates data from both human and veterinary sectors. However, cross-sector analyses are limited due to the lack of interoperability between antibiotic consumption and resistance datasets. The aim of the study was to map the Anatomical Therapeutic Chemical (ATC) classification used in human health and its veterinary equivalent, ATCvet. Systemic antibacterials from therapeutic groups J01 (ATC) and QJ01 and QJ51 (ATCvet) were selected for analysis. Automatic mapping was performed by pairing ATC and ATCvet codes based on corresponding codes. To illustrate the reuse of this reference framework, the criticality assessments from the World Health Organization (WHO) and the World Organisation for Animal Health (WOAH) were mapped onto this table, enabling automated combined analysis. The mapping identified 430 ATC + ATCvet codes, of which 59.3% showed strict equivalence between the two classifications. Additionally, there were 371 unique substances, with 73.0% found in both classifications. The majority of antibiotic classes were shared between the two classifications, while some such as pleuromutilins and quinoxalines were exclusive to veterinary medicine. The discrepancies in classification were primarily linked to specific characteristics of the ATCvet classification system and veterinary-specific indications. Integration with criticality assessments revealed broad correspondence between WHO and WOAH prioritization, with most critically important classes shared across sectors. The distribution of antibiotic classes across animal species showed extensive overlap, particularly within livestock species, underscoring the need for harmonized analyses. The ATC-ATCvet mapping provides a structured and interoperable framework suitable for cross-sector analyses of AMR. This harmonization enables consistent identification of antibiotic molecules, facilitates the integration of heterogeneous datasets, and supports One Health studies by bridging human and veterinary data sources.

Indexed as

antibiotic classificationantimicrobial resistance (AMR)ATC classification systemclassification mappingdata interoperabilityhuman antibioticsveterinary antibiotics

Identifiers

PMID42182927
PMCPMC13189884

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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.