how those questions are asked, and how the results are interpreted. When failures in translation occur, some potential questions to ask are: was it the animal model itself, the analysis, the clinical trial, or another factor? In this regard, the importance of training in skillful study design and appropriate statistical analysis was discussed.

Humans are uniquely different from animals in many ways and there really is no such thing as an animal model of human disease (e.g., an “animal model of depression”). It is important to recognize that animal models are only models of what is being modeled. In other words, these animals are modeling specific perturbations in an effort to understand the biology and assess potential therapies.

Bringing a new drug to market has numerous challenges and significant costs and many potential therapies fail to meet expectations in Phase III clinical trials. Solving the problem of attrition of investigational new drugs will require a “renaissance,” Zorn suggested. Preclinical and clinical scientists need to reunite and redefine what is needed to enhance translation from preclinical models to human clinical trials. Precompetitive alliances and cross-sector collaborations were mentioned as potential approaches. An issue that was raised by multiple participants was that effective, cross-discipline discussion will require a better understanding of each other’s vocabulary.

Also discussed was the need for better definition of the behaviors and physiological measures examined in both the animal model and the human condition. Clearly defining what is measured is important in terms of gauging reproducibility and validity of model systems. There was much discussion about the importance of measuring “the right thing,” but exactly what that is for a given model or disease was, and will continue to be, passionately debated.

Another factor impacting the use of animal models is publication bias, including the tendency in the literature to publish more positive than negative findings; the publication of poorly designed, executed, or analyzed studies that could contribute to uninformative conclusions; and cultural assumptions about what constitutes “good science.”

To foster discussion it was suggested that perhaps it is time to design a whole new set of animal models based on emerging knowledge (e.g., from imaging and genetics), rather than trying to refine existing models. It was also suggested that much can now be learned from sophisticated, non-invasive studies in the living human brain that can inform development of animal models.

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