Big data in veterinary medicines regulation: A data landscape analysis to support regulatory activities

This study describes the development of a data landscape analysis protocol that identifies and characterises animal health data sources to support key regulatory activities throughout the life cycle of veterinary medicines.

The protocol included: development of criteria to identify data sources; selection of variables to characterise the sources based on a metadata list adapted from the human to the veterinary domain; identification of data sources through surveys distributed in European countries, literature/desktop searches and direct contact with informants in Belgium, Italy and the Netherlands; characterisation of the data sources; and synthesis of the findings.

This study identified 652 data sources in the European region. These sources were mainly from public sector stakeholders and included disease registries, product registries and records on the use of antimicrobials. More data sources were identified for production animals than for companion animals. Only half of the identified sources were directly accessible.

The limitations of this study include the low survey response rate and the minimal input from private sector stakeholders.

This study represents the first example of using a landscape analysis approach to analyse animal health data sources in Europe. It provides an initial list of veterinary data with potential for being updated and expanded.