Veterinary clinical trials generate data that advance the transfer of knowledge from clinical research to clinical practice in human and veterinary settings. The translational success of non-regulated and regulated veterinary clinical studies is dependent upon the reliability and reproducibility of the data generated. Clinician-scientists that conduct veterinary clinical studies would benefit from a commitment to research quality assurance and best practices throughout all non-regulated and regulated research environments. Good Clinical Practice (GCP) guidance documents from the FDA provides principles and procedures designed to safeguard data integrity, reliability and reproducibility. While these documents maybe excessive for clinical studies not intended for regulatory oversight it is important to remember that research builds on research. Thus, the quality and accuracy of all data and inference generated throughout the research enterprise remains vulnerable to the impact of potentially unreliable data generated by the lowest performing contributors. The purpose of this first of a series of statement papers is to outline and reference specific quality control and quality assurance procedures that should, at least in part, be incorporated into all veterinary clinical studies.
Bibliographical noteFunding Information:
supported by the COHA
© 2017 The Author(s).