The Experimental Design Assistant: an interactive web-based tool to provide bespoke feedback on experimental plans for in vivo studies

C.E. Credits: RACE
Speaker

Abstract

There is growing concern about the reliability of biomedical research results. Poor experimental design, inappropriate analysis methods and incomplete reporting have all contributed to inconsistent results. The NC3Rs has developed resources to assist researchers in designing rigorous experiments, selecting the appropriate analysis methods and reporting experiments thoroughly. One such resource is the Experimental Design Assistant (EDA). The EDA is free online software with a supporting website to help researchers design more rigorous in vivo experiments. Experiments designed in the EDA are represented as machine readable diagrams, which the system analyses using computer-based logical reasoning to provide feedback. This feedback highlights the implication of particular design features and enables users to make informed choices, tailored to the objective of their own experiments. The system also suggests statistical analysis methods compatible with the design of the experiment. It includes inbuilt power calculators to determine the appropriate sample size, and features to facilitate randomisation and blinding. The EDA is also a very useful tool to communicate experimental plans as the diagram contains detailed information for each step of the experiment and provides a visual overview, which is helpful to support discussions. The EDA is endorsed by major biomedical research funders worldwide, to help researchers design experiments that are more likely to yield robust and reproducible data while using the minimum number of animals consistent with the scientific objectives.

Learning Objectives:

1. Understand the impact of subjective bias on the reliability of animal research results

2. Identify the experimental design features that can be used to reduce effects of bias and make results more reliable

3. Understand how the EDA can be used to design rigorous in vivo experiments that generate reliable results


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