Hı, G power analyses is used for determining the number. You can search for that programme or you can connect with the people ın the ethical committee for guidance

Dear Ebru,

You should seek guidance from your advisory committee, but here is my advice:

For grouping, How will you be able to draw a useful conclusion from your experiment without control groups? I suggest you include at least the following 3 groups in your experiment: a negative control group (healthy untreated animals), a disease model group (diseased untreated animals), and a treatment group (diseased animals which receive your treatment of interest). These groups are essential for assessing any drug-related effect.

Regarding sample size, I recommend you the following article which discusses different methods for sample size calculation, but you have to have a decent knowledge of biostatistics in the first place:

Charan J, Biswas T. How to calculate sample size for different study designs in medical research? Indian J Psychol Med. 2013 Apr;35(2):121-6. doi: 10.4103/0253-7176.116232. PMID: 24049221; PMCID: PMC3775042.

All the best!

Statistically, you need to have at least 7 animals in each group to be able to analyze your data effectively. Usually, 3 groups are needed, including a control group (left untreated), a model group (induction of lesion without treatment), and a treatment group (induction of lesion with treatment). Additionally, it's better to use two doses for your treatment if you have enough supplies.

Regarding the type of animal, remember to choose the strain carefully. If you need more than 3 ml of blood sample from each animal, then you may consider using rat. Otherwise, mice would be a perfect choice.

Good luck

The number of animals and groups required in an experiment is typically determined through power analysis to ensure the study has enough statistical power. Key factors include effect size, variance, significance level (α), and power (1-β). Referring to previous studies with similar methodologies can also help estimate the appropriate sample size. Following the 3Rs principle (Reduction, Replacement, Refinement) is crucial to minimize the number of animals while maintaining scientific validity. Software like G*Power or consulting a biostatistician can assist in refining these calculations based on the study design.