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

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.