Open AccessA Structured Approach to Optimizing Animal Model Selection for Human Translation: The Animal Model Quality Assessment
Author(s) -
Joanne Storey,
Thomas Gobbetti,
Alan R. Olzinski,
Brian R. Berridge
Publication year - 2021
Publication title -
ilar journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.129
H-Index - 75
eISSN - 1930-6180
pISSN - 1084-2020
DOI - 10.1093/ilar/ilac004
Subject(s) - animal model , drug development , computer science , quality (philosophy) , translation (biology) , translational research , relevance (law) , human disease , medicine , drug , disease , pathology , biology , pharmacology , philosophy , epistemology , political science , law , endocrinology , biochemistry , messenger rna , gene
Animal studies in pharmaceutical drug discovery are common in preclinical research for compound evaluation before progression into human clinical trials. However, high rates of drug development attrition have prompted concerns regarding animal models and their predictive translatability to the clinic. To improve the characterization and evaluation of animal models for their translational relevance, the authors developed a tool to transparently reflect key features of a model that may be considered in both the application of the model but also the likelihood of successful translation of the outcomes to human patients. In this publication, we describe the rationale for the development of the Animal Model Quality Assessment tool, the questions used for the animal model assessment, and a high-level scoring system for the purpose of defining predictive translatability. Finally, we provide an example of a completed Animal Model Quality Assessment for the adoptive T-cell transfer model of colitis as a mouse model to mimic inflammatory bowel disease in humans.