Culture of Care
Scientific Integrity
Advancing strong, reproducible, and ethical science
How it Connects to a Greater Culture of Care
- Strong study design (e.g., ARRIVE, PREPARE, EDA) reduces animal numbers while increasing reliability of results.
- Thoughtful protocols support better welfare outcomes, reduce confounding variables, and consider the cumulative experience of the animals.
- Scientific transparency helps build public trust in research quality.
- Clear design also reduces stress and ambiguity for the people carrying out the work.
A strong scientific foundation is essential for a Culture of Care. This means research must be robust, valid, replicable, reproducible, and translatable. The pillar of strong science is intertwined with the 3Rs principles of refinement and reduction (as well as the animal welfare pillar).
Core Principles of Strong Science
- 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
Acknowledgments: Thank you especially to Joe Garner, Anna Ratuski, and Brianna Gaskill for their work in this area including publications, presentations, effort on our certificate course and more that have helped inform the development of this resource page.

