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 administering treatments can have an important influence on the response of animals to experimental treatments. Factorial experimental designs can be used to explore which factors 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 efficient than the older approach of varying one factor at a time. Two examples of real factorial experiments reveal how using this approach can potentially lead to a reduction in animal use and savings in financial and scientific resources without loss of scientific validity.
Factorial experimental designs (FEDs) can be used to study the effects of controllable variables, such as an experimental treatment, sex, strain, age, diet and prior treatment of animals, on some defined response. Such designs have been widely used in optimising manufacturing processes, but have rarely been used in optimising animal experiments in drug discovery. FEDs generally provide more information than the alternative “one-variable-at-a-time” approach, because each animal contributes information on the effect of every factor, and because such designs can highlight any interactions among the variables. Although FEDs can have any number of factors and levels of each factor, where many factors are to be explored, it is common to do an initial experiment using two levels of each factor, and in some cases fractional factorial designs can be used to reduce the total number of treatment combinations to manageable levels. These designs have been used successfully at AstraZeneca in the optimisation of in vivo drug screening experiments, where their use has effectively reduced the numbers of animals used in some routine screens.
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