Internet of instruments: Connectivity of research instruments and artificial intelligence could drastically advance experimental science.

Abstract

EMBO Reports (2018) 19: e47267[OpenUrl][1][FREE Full Text][2] Biologists were among the first who embraced computers and the Internet. In the early 1990s, they used these technologies not only for communication but also for online databases to store, search, and analyze gene and protein sequence data, for protein design, or for protein folding simulation on supercomputers and distributed computer networks. It eventually spawned the field of bioinformatics, which has made an enormous impact on research in the life sciences. Curiously though, biologists have been rather slow to adopt data connectivity in the laboratory itself: while computers are ubiquitous, many instruments and tools from PCR machines to gel imaging or microscopes are still operated manually. Now, the Internet of Things (IoT) is entering biomedical research facilities, hooking up equipment for remote monitoring and data collection, which both saves costs and creates more consistent conditions for experiments. It thus paves the way for artificial intelligence (AI) and machine learning (ML) for further analysis of experimental data and images. Some scientists speculate that once AI and ML become incorporated into research, the potential of IoT could go much further than cutting costs and streamlining laboratory workflows to fundamentally change the way research is done in the life sciences. While this remains to be seen, there is already huge potential for operating laboratories more effectively and maintaining greater control over experiments, which will itself lead to improved outcomes. Indeed, greater reproducibility has been cited as one crucial benefit of being able to guarantee more consistent conditions within research equipment and the laboratory environment. An obvious advantage of IoT is the ability to monitor, for example, refrigeration units to ensure the safety of precious, sometimes irreplaceable samples, which prompted Harvard University to invest in monitoring systems to minimize risk of the freezers failing. The laboratory of Peter … [1]: {openurl}?query=rft.jtitle%253DEMBO%2BReports%26rft_id%253Dinfo%253Adoi%252F10.15252%252Fembr.201847267%26rft_id%253Dinfo%253Apmid%252F30404816%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/ijlink?linkType=FULL&journalCode=embor&resid=19/12/e47267&atom=%2Fembor%2F19%2F12%2Fe47267.atom