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NC3Rs | 20 Years: Pioneering Better Science

Tackling experimental design in your funding proposal

Over recent years grants panels from many funders have been placing increasing importance on the methodology and experimental design in applications. Well designed and correctly analysed experiments not only lead to a reduction in animal use but also increase the scientific validity of results.

To help applicants for NC3Rs funding identify and provide the detail needed in their application, we have gathered resources and advice from our funding and experimental design teams and Panel members from the NC3Rs Grant Assessment Panel. You find a table listing all the resources referred to at the end of this post. 

Good experimental design sets a solid foundation for a grant application and demonstrates to the Panel your ability to do rigorous science. There are a number of common pitfalls we have identified, use this post to make sure you’ve not fallen foul of one of them and give your proposal the best chance of success.

You can also check out our other resources designed to help when writing about the 3Rs in your NC3Rs application, including a recorded webinar.

For further information on the application process for NC3Rs funding schemes please refer to the NC3Rs Applicant and Grant Holder Handbook.

A table of all resources referred to is shown below:


Pitfall to avoid Resources
You've assumed experimental design is only important for in vivo experiments. Webinar: Best practice in experimental design (Dr Natasha Karp, Associate Director of Biostatistics, Astrazeneca)
Your scientific question is unclear or poorly defined. Guidance: Eleven ways your funding application could be failing
You haven’t described your experiments in enough detail.

Worked examples: Different types of experiments written up by the MRC

The Experimental Design Assistant (EDA)

Your sample size is poorly justified.

Video: Statistical power and the perils of chance (Dr Kate Button, University of Bath)

The ARRIVE guidelines

Guidance: How to decide your sample size when the power calculation is not straightforward (Dr Simon Bate, Statistical Sciences, GSK)

Video: Study design: effect sizes and statistical analyses (Professor Hazel Inskip, University of Southampton)

Guidance: Conducting a pilot study

Your statistical analysis is unclear or inappropriate.

EDA: Statistical Analysis

EDA: Independent Variables

You’ve incorrectly identified the experimental unit.

The ARRIVE guidelines: Experimental units

Journal article: What exactly is ‘N’ in cell culture and animal experiments? (Lazic et al. Plos Biology)

You’ve not explained how you are avoiding bias.

EDA: Allocation

EDA: Nuisance variables

Video: Blinding reduces bias in experimental design (British Pharmacological Society)

The ARRIVE guidelines: Blinding

You have not provided enough information about sex in your experiments

Video: MRC/NC3Rs webinar: Using both sexes in animal experiments 

EDA: Considering sex when designing your studies