• Clear experimental planning that clearly defines the questions, hypothesis, methods, and analysis BEFORE starting your project 
• Choose valid test methods that are not just replication of historical strategies
• Purposeful model selection that considers scientific validity, genetic and translational relevance, and ethics.
• Mandatory use of blinding, randomization, and appropriate controls (both positive & negative)
• Animals treated like patients in clinical trials with refined housing, handling, and procedures as their welfare affects data quality
• Consider using emerging technologies that collect translational, non-invasive objective data: digital biomarkers, optical imaging, infrared thermography, MRI/PET for longitudinal studies
• Purposeful inclusion of biological variability: sex as a biological variable, multiple strain, diverse age groups, etc.

Additional Recommendations: 

• Publish FAIR data that is Findable, Accessible, Interoperable, Reusable 
• Pre-registering your study  
• Implementing standard operating procedures (SOPs), self-audits, and quality assurance toolkits 

Role of the IACUC & Animal Review Bodies 

IACUCs should actively review and comment on: 

• Experimental design flaws 
• Proposed sample size and statistical analysis 
• Reproducibility & translational potential 
• Pilot studies (these generally increase the risk of having inaccurate effect sizes, non-reproducible results, and inappropriate samples sizes and shouldn’t be approved by IACUCs unless the purpose is to figure out procedural factors) 

Red Flags to Watch For (Begley, 2013): 

• Lack of blinding 
• Missing repetition of basic experiments 
• Incomplete results reporting 
• Missing positive/negative controls 
• Unvalidated reagents 
• Inappropriate statistical tests 

Tools & Resources 

• The 3Rs Certificate Course 
• Introduction to Experimental Design Course & NC3Rs Experimental Design Assistant 
• PREPARE Guidelines & ARRIVE 2.0 Guidelines  
• NIH FAIR Data Principles and GO FAIR 
• 3RsC’s Translational Digital Biomarkers Initiative 
• CCAC Guidelines on Training 
• Cancer-SOLES (Systematic Online Living Evidence Summary) 

Further Reading 

• Stanford’s Beyond3Rs Resource Hub with guidance and extensive references on the importance of Embracing Variability, Reproducibility & Transparency, and Housing & Husbandry 
• Garner 2014. The Significance of Meaning: Why Do Over 90% of Behavioral Neuroscience Results Fail to Translate to Humans, and What Can We Do to Fix It? 
• Gaskill & Garner 2020. Power to the People: Power, Negative Results and Sample Size. 
• Festing et al. 2020. The “completely randomised” and the “randomised block” are the only experimental designs suitable for widespread use in pre-clinical research 
• Voekl et al. 2020. Reproducibility of animal research in light of biological variation 
• Landi et al. 2021. Bioethical, Reproducibility, and Translational Challenges of Animal Models. 
• Townsend et al. 2025. A call to action to address critical flaws and bias in laboratory animal experiments and preclinical research