Reproducibility is an initiative many researchers struggle to achieve, and one some don’t even take into consideration during experimental design. A survey by Nature confirms this fact, finding that more than 70% of scientists have failed to reproduce another scientist’s results, and another 50% have failed to reproduce the results of their own research.
As a contract research organization for immunology and inflammation research, reproducibility is something we take very seriously. We have identified four key sources of variability that can be controlled to improve intra-lab and inter-lab reproducibility of research findings.
The infographic below contains our highlights and takeaways. For a more in-depth exploration of each factor along with tips and data from our lab, view our white paper on the same topic.
If you’ve reached a stumbling block in your research or need an extra set of hands, learn about our outsource research capabilities.
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4 Factors That Affect Research Reproducibility
Improve Reproducibility in Your Lab by Focusing on These Key Sources of Variability
Factor #1: Reagents
Antibodies & Cells
Verifying the quality of reagents used in research can prevent wasted time, wasted resources and unverifiable results.
Differences in culture media environment can have a major impact on cell behavior and thus cause reproducibility issues.
Factor #2: Equipment
Make sure all equipment is calibrated and capable of measuring its intended results with accuracy, precision and safety.
All equipment wears differently, even if used for the same purposes over the same time period in the same lab conditions.
Factor #3: Personnel
Training & Mentorship
Ensure every researcher under your management is adequately trained in experimental design and put in place an expectation and foundation of strong mentorship from senior researchers.
The desire to publish research in high-visibility, prestigious journals can lead to cherry-picking results that, while promising or interesting, may not be reproducible.
Factor #4: Methods
Variation in Cell-Based Assays
Understanding the degree of variability in a cell-based assay and the sources of it will help researchers account for inherent variations in the assay to avoid improper conclusions.
Beefing up your design standards, method selection and measurement techniques will increase your intra-lab and inter-lab reproducibility.