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Biostatistics Research for Laboratory Studies Most therapeutic advances for human populations are initially tested in an animal model. Statistical questions frequently arise in in vitro and animal studies regarding study design, data analysis and interpretation of results. Appropriate design and analyses are crucial for these animal experiments, especially when there is a focus on moving advances rapidly from the laboratory to the clinic. It is particularly important in the context of a translational research program that biostatistical collaboration is involved in the “three Rs” of refinement, reduction, and replacement in animal experiments such that pre-clinical studies are optimally designed to inform future human experimentation. Much of the methodology developed for clinical studies is directly applicable to animal studies. The importance of novel study designs to meet the standards for use of animals in research has been recognized in both biostatistics and pharmacology. Rodent toxicology studies that involve the identification of some treatment construct as the “best” among those tested are an example where statistical methodology could improve animal experiments. The use of adaptive/sequential methods in this context can both reduce overall costs and, perhaps reduce the expected number of animals used. One approach is to use statistical ranking and selection procedures. There is a substantial literature on these methods in various fields and they have been applied to the design and analysis of clinical trials. However, to our knowledge these methods have not been applied to the area of animal experimentation, and can be. Other methods that are familiar within clinical trials also have direct application to optimizing animal experiments, although there are specific issues such as serial sacrifice that may require new methods. |