lateral sclerosis are most likely “noise … as opposed to actual drug effect” (Scott et al., 2008).
Koroshetz offered his own perspective on some of the goals of standardization:
• Improve best laboratory practices to decrease the publication of spurious results.
• Facilitate the reproducibility of results.
• Facilitate the dissemination of valuable animal models into more laboratories.
• Improve comparability across studies using “identical” animal models (requires knowledge of laboratory-to-laboratory variability).
• Restore trust before disaster strikes.
He also suggested several potential risks to keep in mind:
• The increased burden posed by over-standardization could stifle innovation.
• Research might gravitate toward standardized models, thereby restricting development of better models or the testing of multiple models.
• There could be decreased generalizability due to convergence of studies on a limited number of standardized models.
Standardization is not an “all-or-none” question but rather a “when and how much” consideration, Koroshetz said, and he referred workshop participants to recent recommendations from NINDS for experimental design, minimizing bias, results reporting, and results interpretation.1
CHALLENGES TO STANDARDIZATION OF BEHAVIORAL MODELS
Andrew Holmes, chief of the Laboratory of Behavioral and Genomic Neuroscience at the National Institute on Alcohol Abuse and Alcoholism, discussed standardization of behavioral models in the context of preclinical models and assays of anxiety. Holmes described several tests that have been the basis for much of the preclinical research in anxiety