How to ensure lab reproducibility with automation


In this short blog, we explore the value of reproducibility in the lab, and how automation can help teams across the globe collaborate from a single source of reproducible truth.

What is lab reproducibility and why is it important?

Lab reproducibility is being able to repeat research with the same input data and experimental methods and analysis, to achieve results that are consistent with the original findings.2 

Scientific discoveries must be reproducible to be trustworthy, but there’s a reproducibility crisis in science according to a survey conducted by Nature in 2016.1

In the survey, over 70% of the 1,576 researchers that were questioned described having tried and failed to reproduce another scientist’s experiment. Whilst a level of uncertainty is inevitable in science, once the statistical analysis has been performed, the results between repetitions should fit within the bounds of the error.

Reproducibility is the key to impactful and collaborative research.

Laboratories across the world can be completely disparate environments, using different experimental procedures and operating conditions. Yet, experiments performed on one side of the globe must be able to be reproduced on the other for us to be truly confident in the conclusions we draw.3

How do you ensure the reproducibility of results?

To ensure reproducibility in research, we need to strictly adhere to basic scientific principles. For example:

  • Optimising robust experimental protocols
    Over time, experimental procedures used by different members of the same lab can diverge. Whilst these differences can be subtle, the effects can be huge, causing large discrepancies in results. Optimising protocols for synchronicity between researchers is essential for reproducibility. This can be ensured by preparing standard operating procedures (SOPs) to be followed by all users, which in turn can easily be widely distributed to researchers in other lab groups.
  • Publication of all data, statistical analysis, and full results
    Publishing meaningful results through a process of rigorous peer review is fundamental to the scientific method. However, papers are often published without disclosing all of their data, complete methods of analysis, or full results, including the negative or confusing. To ensure reproducibility in the lab, transparency is key. We must endeavour to publish everything so that other scientists can properly review our work.
  • Automation of lab processes
    Typically in the lab, human researchers undertake the experiments. Fundamentally, it is a well-known fact that humans make errors, no matter how careful they may try to be. And, as mentioned above, experimental protocols can subtly vary from researcher to researcher. Automation of common lab processes can reduce human error, and prevent variation between experiment repetitions, thus improving the reproducibility and reliability of experimental results.

The impact of automation on lab reproducibility

Automation in the lab can significantly enhance the reproducibility of experiment results, even between separate laboratories across the globe. A typical day in the lab often involves many repetitive, tedious tasks that are common throughout research, such as aliquoting, centrifugation or sample sorting. 

It is these monotonous processes that are the most prone to human error, and it is precisely these tasks that lab automation can impact. Automating routine techniques forgoes the risk of subtle protocol divergence between researchers, and increases lab productivity.4

The quality of experimental protocol and output results can be improved through automation. The ability to programme automated processes in the lab allows for the precise operation of experiments. Protocols can more easily be shared and distributed between researchers, enabling standardisation of experiments and improved quality control

Automation allows for faster, more efficiently run experiments. Whilst humans tire, lab robots do not, thus high throughput screening and analysis of large data sets provide improved reliability of the output results.5 Therefore, we can ensure the reproducibility of experimental results, supporting scientific discovery and innovation by providing confidence to researchers in the outputs they obtain in the lab.

Automation solutions from Automata

Automata LINQ is a lab automation platform that enables life Sciences labs to fully automate their workflows.

We do this with our automated lab bench, which fits into the same footprint as a regular lab bench, and lab orchestration software, which enables true walkaway time.


1. Baker, M. 1,500 scientists lift the lid on reproducibility. Nature 533, 452–454 (2016). 

2. Ensuring Reproducible Data in the Laboratory. Lab Manager

3. Reproducibility: 8 steps to make your results reproducible.

4. Holland, I. & Davies, J. A. Automation in the Life Science Research Laboratory. Frontiers in Bioengineering and Biotechnology 8, (2020).

5. Jessop-Fabre, M. M. & Sonnenschein, N. Improving Reproducibility in Synthetic Biology. Frontiers in Bioengineering and Biotechnology7, (2019).