Indicators for the use of robotic labs in basic biomedical research: a literature analysis.

Paul Groth,Jessica Cox

doi:10.7717/peerj.3997

Abstract

Robotic labs, in which experiments are carried out entirely by robots, have the potential to provide a reproducible and transparent foundation for performing basic biomedical laboratory experiments. In this article, we investigate whether these labs could be applicable in current experimental practice. We do this by text mining 1,628 papers for occurrences of methods that are supported by commercial robotic labs. Using two different concept recognition tools, we find that 86%–89% of the papers have at least one of these methods. This and our other results provide indications that robotic labs can serve as the foundation for performing many lab-based experiments.

Highlights

The reproducibility of a scientific experiment is an important factor in both its credibility and overall usefulness to a given field
Our results show that that 86%–89% of these papers have some methods that are currently supported by cloud-based robotic labs
Using the Solr Dictionary Annotator (SoDA) mapping, we identified 1,404 articles or roughly 86% of the total corpus to have at least one known robotic method

Summary

Introduction

The reproducibility of a scientific experiment is an important factor in both its credibility and overall usefulness to a given field. There has been an uptick in discussion surrounding scientific reproducibility, and it is increasingly being called into question. Baker (2016) conducted a 2016 survey of 1500 researchers for Nature in which 70% were unable to reproduce their colleague’s experiments. Over 50% of the same researchers agreed that there was a significant crisis in reproducibility. While these issues arise in all fields, special attention has been paid to reproducibility in cancer research. Major pharmaceutical companies like Bayer and Amgen have reported the inability to reproduce results in preclinical cancer studies, potentially explaining the failure of several costly oncology trials (Begley & Ellis, 2012)

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