Beyond3Rs  >  Research  >  Reproducibility and Translation

Reproducibility, translatability, and scientific rigor are inherently connected to animal well-being.

Poor animal well-being has the potential to lead to poor quality data, poor reproducibility, and poor translation to humans. Failure of an experiment to produce benefits to humans or animals is in itself an animal welfare issue. To go Beyond3Rs, we need to prioritize scientific rigor to improve the ultimate success of experiments using animals.

While they are sometimes thought of as failures, negative results are also an important part of the scientific process and can be learned from, systematically analyzed, and built upon by future research. Negative results are different from inconclusive results – negative results suggest looking for a different experimental target, while inconclusive results suggest looking for a different experimental design.

We encourage researchers to look for ways to make better use of animals, such as applying modern statistical methods, using appropriate and innovative experimental designs, and collecting more qualitative and individualized information about each animal. Reproducibility can additionally be aided through more rigorous planning (e.g. following the PREPARE guidelines) and transparent reporting of animal experiments (e.g., following the ARRIVE guidelines).

Prioritizing rigor and reproducibility at all points throughout the experimental process takes us Beyond3Rs.

Key Definitions

  • The following concepts represent critical components of the knowledge cycle of biomedical research:
  • Preclinical Reproducibility
    Replication of results from animal studies in other animal studies.
  • Clinical Reproducibility
    Replication of results from human studies in other human studies.
  • Forward Translation
    Demonstrating results from animal studies in human studies.
  • Reverse Translation
    Demonstrating results from human studies in animal studies.

    Reverse translation involves predicting animal responses to treatments through human data modeling, and applying clinical experimental design methods to preclinical trials. One example of reverse translation is heterogenization, which applies the clinical approach of utilizing natural variation rather than removing it. Reverse translation can help produce more specific experimental targets, more valid animal models, and more generalizable results.  

Research: Reproducibility and Translation

Our findings suggest that environmental standardization is a cause of, rather than a cure for, poor reproducibility of experimental outcomes. Environmental standardization can contribute to spurious and conflicting findings in the literature and unnecessary animal use.

From "Environmental standardization: cure or cause of poor reproducibility in animal experiments?"

Systematic heterogenization revisited: Increasing variation in animal experiments to improve reproducibility?

Vanessa T von Kortzfleisch, S Helene Richter (2024), Journal of Neuroscience Methods

Life sciences are currently facing a reproducibility crisis. Originally, the crisis was born out of single alarming failures to reproduce findings at different times and locations. Nowadays, systematic studies indicate that the prevalence of irreproducible research does in fact exceed 50%. In this respect, animal research has come under particular scrutiny, as the stakes are high in terms of both research ethics and societal impact. To counteract this, it is essential to identify sources of poor reproducibility as well as to iron out these failures. We here review the current debate, briefly discuss potential reasons, and summarize steps that have already been undertaken to improve reproducibility in animal research. We argue that systematic variation rather than strict homogenization of experimental conditions benefits the robustness of research findings, and hence their reproducibility.

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Environmental standardization: cure or cause of poor reproducibility in animal experiments?

S Helene Richter, Joseph P Garner, Hanno Würbel (2009), Nature Methods

It is widely believed that environmental standardization is the best way to guarantee reproducible results in animal experiments. However, mounting evidence indicates that even subtle differences in laboratory or test conditions can lead to conflicting test outcomes. Because experimental treatments may interact with environmental conditions, experiments conducted under highly standardized conditions may reveal local 'truths' with little external validity. Our findings suggest that environmental standardization is a cause of, rather than a cure for, poor reproducibility of experimental outcomes. This conclusion calls for research into practicable and effective ways of systematic environmental heterogenization to attenuate these scientific, economic and ethical costs.

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Why do over 90% of behavioral neuroscience results fail to translate to humans, and what can we do to fix it?

Joseph P Garner (2014), ILAR Journal

The vast majority of drugs entering human trials fail. This problem (called "attrition") is widely recognized as a public health crisis, and has been discussed openly for the last two decades. Attrition does reflect a lack of predictive validity of animal experiments, but it would be a mistake to conclude that animal models cannot show predictive validity. In essence, this review advocates a fundamental shift, where we treat every aspect of an animal experiment that we can as if it was a clinical trial in a human population. "Validation with known failures" is proposed as a solution. By using a library of known failures we can thereby empirically test the impact of suggested solutions such as enrichment, controlled heterogenization, biomarker-based models, or reverse-translated measures.

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Power to the People: Power, Negative Results and Sample Size

Brianna N Gaskill, Joseph P Garner (2020), JAALAS

The practical application of statistical power is becoming an increasingly important part of experimental design, data analysis, and reporting. Power is essential to estimating sample size as part of planning studies and obtaining ethical approval for them. Furthermore, power is essential for publishing and interpreting negative results. In this manuscript, we review what power is, how it can be calculated, and reporting recommendations if a null result is found. Power can be thought of as reflecting the signal to noise ratio of an experiment. The conventional wisdom that statistical power is driven by sample size (which increases the signal in the data), while true, is a misleading oversimplification. 

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Reproducibility of animal research in light of biological variation

Bernhard Voelkl, Naomi S. Altman, Anders Forsman, Wolfgang Forstmeier, Jessica Gurevitch, Ivana Jaric, Natasha A. Karp, Martien J. Kas, Holger Schielzeth, Tom Van de Casteele & Hanno Würbel (2020), Nature Reviews Neuroscience

Context-dependent biological variation presents a unique challenge to the reproducibility of results in experimental animal research, because organisms’ responses to experimental treatments can vary with both genotype and environmental conditions. In contrast to the current gold standard of rigorous standardization in experimental animal research, we recommend the use of systematic heterogenization of study samples and conditions by actively incorporating biological variation into study design through diversifying study samples and conditions. Here we provide the scientific rationale for this approach in the hope that researchers, regulators, funders and editors can embrace this paradigm shift.

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