How Are Animal Models Validated?

Animal models have led to significant leaps in understanding and advancement in human medicine. They are essential for drug discovery and connecting hypothesis-driven benchwork to the patient. However, scientists have struggled with how to define the value of a given animal model¹.

Animal Model Validation

In 1969, McKinney and Bunney were the first to propose criteria on external validity of animal models, mainly focused on affective disorders². In 1984, Wilner simplified these external validations to three: predictive, face, and construct validity⁴.

These remain the most widely-accepted criteria for model validation, although many other proposals exist^1-4,6. Although these three external validations were based on the psychiatric field of research, they can and should extend to any research where animal models are used. Of course, external validation does not occlude a scientist from internal validity (experimental design, reproducibility, randomization, control, etc.), which applies to all scientific research.

No Animal Model is Universal

An animal model may show a diverse outcome among the three categories of validation. Since no animal model perfectly replicates clinical conditions, no single model can show validity in all three criteria². A model could have strong predictive validity but completely lack face validity, or vice versa.

Instead, these criteria provide a general external validation, the importance of which should be grounded in the purpose of the model. Understanding what validity a model can and cannot provide can be crucial for accurate preclinical assessment of novel therapeutic agents^2,3,7. There is controversy in the ranked importance of the three criteria, mostly due to the divergence in their definition, but in general, predictive validity tends to hold the most weight^1,2,4. This is especially true in preclinical drug discovery⁸.

Defining Criteria for Animal Model Validation

Definitions of the three validity terms are vast. Here, we give a simplified explanation of each and give an example of a model that best represents that validity type:

In understanding the three terms, an investigator can assess how well a given animal model represents the human disease and the degree of therapeutic translation.

Multifactorial Validity in Animal Models

Although one model cannot perfectly recapitulate the clinical realm, the right combination of animal models that provide validity across the three generalized spectrums could get close. While the underlying disorder may limit access to all spectrums of validity regardless of the models employed, a multifactorial approach can generally be applied to all fields⁶.

Selecting the optimal combination of animal models depends on each of their external validities^3,6. Dramatic improvements in animal model validity and translational significance have occurred in oncology, through the use of humanized models³, while many fields — such as neurodegenerative medicine — still struggle with translatability^5,7.

Certainly, understanding and evaluating a model in the field of immuno-oncology is quite different from that of neurodegenerative disease. However, by understanding the general guidelines of external validation of an animal model, one can better evaluate the potential translational significance of the data generated in any field.

References:

1. Geyer M.A., Markou A. In: Psychopharmacology: the fourth generation of progress. Bloom FE, Kupfer DJ, editor. New York: Raven Press; 1995. Animal models of psychiatric disorders; pp. 787-798.

2. Belzung C. and Lemoine M. Criteria of validity for animal models of psychiatric disorders: focus on anxiety disorders and depression. Bio Mood Anxiety Disord. 2011 1:9.

3. Denayer T., Stohr T., Van Roy M. Animal models in translational medicine: validation and prediction. New Horiz. Transl. Med. 2014 2 5-11.

4. Willner P. The validity of animal models of depression. Psychopharmacology (Berl). 1984 83(1) 1-16.

5. Lutz C.M. and Osborne M.A. Optimizing mouse models of neurodegenerative disorders: are therapeutics in sight? Future Neurol. 2013 9(1) 67-75.

6. Markour A., Chiamulera C., Geyer M.A., Tricklebank M., Steckler T. Removing obstacles in neuroscience drug discovery: the future path for animal models. Neuropsychopharmacology. 2009 34 74-89.

7. Potashkin J.A., Blume S.R., Runkle N.K. Limitations of animal models of parkinson's disease. SAGE-Hindawi Access Review. 2011.

8. Sams-Dodd F. Strategies to optimize the validity of disease models in the drug discovery process. Drug Discovery Today. 2006 11 355-363.