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Poor reproducibility can have a significant impact on your research, career, and scientific progress as a whole. However, small changes, like selecting recombinant antibodies, can make a big difference.
Achieving a result, whether it’s an important novel finding or reproducing another scientist’s work, is a thrilling moment. However, if you have experienced the frustration of irreproducible results, you will know how much time, precious samples, and money this wastes.
Not only is irreproducibility frustrating for researchers, but it also slows down the progression of science. Scientific discovery builds on previous findings to answer new questions and further the field of research. Therefore, being unable to reproduce previous work has a huge impact on both the scientific community and the general public.
This is the reproducibility crisis in science.
A survey of 1,576 researchers by Nature revealed that over 70% of researchers cannot reproduce another scientist’s experiments1. If you consider how often your work relies on protocols or results from other labs, you can begin to comprehend the size of the problem. This irreproducibility correlates to an enormous amount of wasted time and money, in addition to the potential impact on your publication and career success.
A paper by Andrew Bradbury in 2015 estimated that $1.6 billion was spent on poorly characterized antibodies world-wide2. However, since this paper was written, this estimate has more than doubled to $3.5 billion3.
Figure 2: Examples of how many papers are affected by non-specific antibodies from Abcam’s Reproducible Science Week webinars. Speakers: Andrew Bradbury, Pablo Engel, Peter McPherson, and Angelo De Marzo.
Choosing the most reliable type of antibody is a simple solution to avoiding irreproducibility. To achieve accurate, reproducible results, the antibodies used in your research need to have high specificity and low batch-to-batch variability but these factors differ between polyclonal, monoclonal, and recombinant monoclonal antibodies.
Validating your antibodies before use is essential to ensure application-specific performance, regardless of the antibody type being used. However, selecting highly specific and reproducible antibodies can reduce the time and resources required for validation.
Figure 3: Abcam's recombinant anti-TLE1 [EPR9386(2)] antibody (left) being tested on knock-out and wild-type samples against our monoclonal anti-TLE1 [OTI1F5] antibody (right).
Solving the reproducibility crisis is a substantial task that requires coordination and input from all researchers. But, like the many small grains of sand that make up a beach, taking small steps to improve reproducibility in your own experiments can have a large impact on solving the bigger problem.
Whether it’s ensuring correct validation of reagents in your application, optimizing data analysis, or making the switch to recombinant antibodies, you can have a vital role in improving scientific reproducibility.