Abstract
Within preclinical research, attention has focused on experimental design and how current practices can lead to poor reproducibility. There are numerous decision points when designing experiments. Ethically, when working with animals we need to conduct a harm-benefit analysis to ensure the animal use is justified for the scientific gain. Experiments should be robust, not use more or fewer animals than necessary, and truly add to the knowledge base of science. Using case studies to explore these decision points, we consider how individual experiments can be designed in several different ways. We use the Experimental Design Assistant (EDA) graphical summary of each experiment to visualise the design differences and then consider the strengths and weaknesses of each design. Through this format, we explore key and topical experimental design issues such as pseudo-replication, blocking, covariates, sex bias, inference space, standardisation fallacy and factorial designs. There are numerous articles discussing these critical issues in the literature, but here we bring together these topics and explore them using real-world examples allowing the implications of the choice of design to be considered. Fundamentally, there is no perfect experiment; choices must be made which will have an impact on the conclusions that can be drawn. We need to understand the limitations of an experiment's design and when we report the experiments, we need to share the caveats that inherently exist.