Abstract
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.
Highlights
Veterinary clinical studies are designed to determine whether a medical intervention is safe and effective when used in clientowned animals
While such studies are typically performed in veterinary patients with spontaneous disease, occasionally studies are performed in healthy client owned dogs
In addition to benefiting animal health, an increasing number of clinical trials in veterinary patients are being undertaken to evaluate a novel therapeutic or device prior to initiation of human clinical trials. Such studies are based on the premise that spontaneous disease in veterinary patients more closely recapitulates similar human diseases and data generated from these trials would be more informative than that generated using induced models of disease
Summary
Veterinary clinical studies are designed to determine whether a medical intervention (e.g. device, treatment, approach) is safe and effective when used in clientowned animals. Veterinary clinical trials conducted within regulated research programs are partially constrained to meet regulatory requirements established to ensure patient safety and maintain data integrity In spite of these differences, the scientist-driven development of a common approach to basic data quality that spans the non-regulated and regulated veterinary clinical trial spectrum would be an effective strategy for demonstrating data quality and enhancing research reliability. Resources for improving and demonstrating research quality The resources listed in Table 1 were developed to maintain research flexibility and support (and monitor) data quality and reconstruction They encourage basic research scientists to integrate QA activities and commit to good documentation practices within their research. Project Management: Ensure that research objectives, approach, timeline and budget are planned, communicated and understood
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