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Objective: In the present study, the feasibility of a systematic record of clinical study data from marketing authorisation applications for veterinary medicinal products (VMP) and benefits of the selected approach were investigated.

Background: Drug registration dossiers for veterinary medicinal products contain extensive data from drug studies, which are not easily accessible to assessors.

Evidentiary value: Fast access to these data including specific search tools could facilitate a meaningful use of the data and allow assessors for comparison of test and studies from different dossiers.

Methods: First, pivotal test parameters and their mutual relationships were identified. Second, a data model was developed and implemented in a relational database management system, including a data entry form and various reports for database searches. Compilation of study data in the database was demonstrated using all available clinical studies involving VMPs containing the anthelmintic drug Praziquantel.
By means of descriptive data analysis possibilities of data evaluation including graphical presentation were shown. Suitability of the database to support the performance of meta-analyses was tentatively validated.

Results: The data model was designed to cover the specific requirements arising from study data. A total of 308 clinical studies related to 95 VMPs containing Praziquantel (single agent and combination drugs) was selected for prototype testing. The relevant data extracted from these studies were appropriately structured and shown to be basically suitable for descriptive data analyses as well as for meta-analyses.

Conclusion: The database-supported collection of study data would provide users with easy access to the continuously increasing pool of scientific information held by competent authorities. It enables specific data analyses. Database design allows expanding the data model to all types of studies and classes of drugs registered in veterinary medicine. The needs for detailed data recording and versatility of the data model must be carefully balanced.

Application: The database will be used by regulatory authorities.