Use of factorial design to optimize animal experiments and reduce animals

Optimization of experiments, such as those used in drug discovery, can lead to useful savings of scientific resources. Factors such as sex, strain, and age of the animals and protocol-specific factors such as timing and methods of ad-ministering treatments can have an important influence on the response of animals to experimental treatments. Facto-rial experimental designs can be used to explore which fac-tors and what levels of these factors will maximize the difference between a vehicle control and a known positive control treatment. This information can then be used to design more efficient experiments, either by reducing the numbers of animals used or by increasing the sensitivity so that smaller biological effects can be detected. A factorial experimental design approach is more effective and effi-cient than the older approach of varying one factor at a time. Two examples of real factorial experiments reveal how us-ing this approach can potentially lead to a reduction in ani-mal use and savings in financial and scientific resources without loss of scientific validity. Key Words: animal testing alternatives; animal use alter-natives; case report; factorial analysis; models, animal; re