Reproducibility is a big talking point in the world of science. That’s perhaps even a slight understatement, considering that it’s been referred to as something of a crisis of the times. In fact, a survey showed that 52% of researchers thought there was a “significant” issue with reproducibility. So what exactly is it, and why is it such a problem? Different from repeatability, which requires all conditions of an experiment to be exactly the same, reproducibility is based on the idea that the same experiment can be done by a different scientist, in a different location, with different instruments – and get the same results. Reproducibility is not only important for replicating your own work, but so that others can confirm your findings. Without getting a handle on it, you run the risk of unsound or incorrect results – so what’s to be done? While it’s somewhat inevitable that you’ll see unreliable results in your experiments from time to time, there are some practices you can employ to help reduce the likelihood. Take a look at our recommendations on the best ways to boost reproducibility in the lab. Internal checking A second pair of eyes is often invaluable. Get a colleague to try to replicate the results – they’ll be able to identify anything that’s unclear. Involve more than one lab A study published in PLOS Biology showed that including even just a few other laboratories could greatly improve your odds of reproducible results – by as much as 42%. It found that including just two to four labs in an experiment produced more consistent results than single-lab studies. Share your data Sharing data is imperative when it comes to the quest for reproducible results. Hold regular talks in which your data, supporting information and lab notes are shared and discussed. Scientists should also share inconclusive or null results, to help prevent others making the same mistakes. Invest in Electronic Laboratory Notebooks Electronic Laboratory Notebooks, or ELNs, have the potential to be revolutionary when it comes to tackling this crisis. You can access data years after it was collected and search colleagues’ notebooks to compare work. You can even search the molecular structure of products, so it’s easier to keep track of reactions. There are a couple of downsides to ELNs, the first being their high cost to implement. You’d also need to consider time for proper training, due to being more complicated to use than a standard paper notebook. Simplify your experiment Large experiments can often see mistakes made during the process, as lots of data leaves lots of room for error. Try refining your experiment, with data that can be yielded in a format that’s easily interpretable. Write detailed protocols A detailed, well-written protocol is essential for maintaining consistency – having to read between the lines is a sure-fire way to inevitably get something wrong. You should treat it like a kind of brief: have a chronology of steps (in the form of bullet points), note down any equipment and materials used, and be aware of the language you use – will everyone understand what you’re referring to with that particular word? How can Radleys products help? Many of the Radleys products and equipment have been specifically designed to help create reliable, reproducible results. Our AVA Control Software is a good example: through automation, you remove human error when carrying out experiments and recording results. You also record set-up data, so that another chemist or lab has the information to carry out the same experiment. Some of our equipment also allows you to carry out multiple position, or ‘parallel’ reactions. This means you can carry out the same reaction in all positions and average the result. You could even have one of the positions as a control, so as to calibrate your other results. The StarFish, Carousel 12 Plus and Carousel 6 Plus reaction stations all have this functionality, so why not give it a go in your next experiment?