Scientists want to strengthen the use of laboratory automation

In total, 74% of scientists said less than half of their lab operations are automated. Of those surveyed, 19% of those surveyed said their labs were between 51% and 75% automated and only 6% reported a percentage of automation above 76%.

Survey respondents were members of, with data collection completed on April 20.

Of the 960 study participants, 66% were scientists, researchers or researchers; 26% were pharmaceutical or biotechnology scientists; 15% were laboratory staff; and 9% were postdoctoral researchers. Most of the participants were associated with a university (41%) or a pharmaceutical (20%) or life sciences (15%) company. On a regional basis, 33% of the participants were based in North America, 24% in Europe and 36% in Asia, while the remaining 7% were from various other locations around the world.

Laboratory automation can be divided into two main categories: (1) hardware and equipment used to manually collect data and (2) software and IT tools to manage data.

The different types of laboratory automation tools are:

Automation hardware and equipment

  • Liquid Handling Systems: These systems dispense and sample liquids in tubes or wells and are often integrated as automated injection modules.
  • Microplate Readers: Microplate readers are instruments used to detect biological, chemical, or physical events of samples in microtiter plates, which allows many samples to be measured simultaneously.
  • High Throughput Screening / Sequencing Systems: Such systems can prepare, incubate and analyze multiple plates simultaneously, thereby speeding up the data collection process.
  • Multiplex Systems: These systems use multiple dyes / markers in image-based assays to provide a means of reporting multiple cell components simultaneously and therefore their effects on each other.
  • Laboratory robots: they are used to move biological or chemical samples to synthesize new chemical entities or to test the pharmaceutical values ​​of existing chemical material. Advanced laboratory robotics can be used to fully automate the scientific process (e.g. pick / place, liquid and solid additions, heating / cooling, mixing, stirring and testing).

Laboratory software and computer tools

  • Bioinformatics: This term refers to the intersection of biology and computer science concerned with the acquisition, storage, analysis and dissemination of biological data, most commonly DNA and amino acid sequences. .
  • Cheminformatics: Cheminformatics deals with the storage, indexing, searching, retrieval and application of information about chemical compounds.
  • Enterprise Content Management Systems (aka Document or Records Management): These systems are used to manage the entire content lifecycle of an organization (including documents and spreadsheets).
  • Electronic lab notebooks: Electronic notebooks reproduce an interface much like a page in a paper lab notebook.
  • Laboratory Information Management Systems (LIMS / LIS): These software solutions provide workflow and data tracking support, flexible architecture, and data exchange interfaces (sometimes including IT management). laboratory).
  • Scientific Data Management Systems (SDMS): SDMS capture, catalog and archive data generated by laboratory instruments (high performance liquid chromatography [HPLC] and mass spectrometry) and applications (LIMS, analytical applications, electronic laboratory notebooks). Specialized SDMSs focus on acquiring data from individual instruments.
  • Laboratory Workflow Automation Systems: These systems follow a set of procedural rules to manage and coordinate tasks between people and systems in the laboratory. Laboratory workflows for sample management ensure that all steps and requirements of a defined process are correct.

How do researchers use laboratory automation?

In the survey, most researchers indicated that they currently use liquid handling systems, microplate readers and, to a lesser extent (about 49%), multiplex and high-throughput systems. Far fewer scientists reported using advanced robots, but around 45% said they would like to use robotics in the future. Almost 60% of the researchers also said they would like to use multiplex and broadband systems in the future.

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The most commonly used software and tools in the current survey were bioinformatics / pathformatics, LIMS, and specialized SDMS. Researchers wanted to increase the use of electronic laboratory notebooks, SDMS, and laboratory workflow automation systems in the future.

Click on the image to enlarge.

When asked to select the top three benefits of laboratory automation and computing, respondents indicated the following:

  1. More reliable results
  2. Reduction of errors
  3. Ability to visualize and analyze cumulative trends in data

Fast data traceability and ease of report generation and distribution are other top-rated benefits.

If the benefits of laboratory automation are so widely recognized, why aren’t more researchers using tools already available? Unsurprisingly, cost is the main factor limiting the use of lab automation, with 65% of respondents citing lack of funds as the main restriction. More than a quarter of scientists surveyed either have no purchasing power or plan to invest in lab automation next year.

Another 33% plan to spend less than $ 50,000 in the coming year, and 27% plan to spend between $ 50,000 and $ 200,000. Thus, while it is clear that laboratory automation is a priority in many organizations, cost remains a limiting factor for practical implementation in many laboratories.

Another limitation to the implementation of laboratory automation is the COVID-19 pandemic: 56% of scientists reported that the pandemic had delayed their plans for capital investments in laboratory automation. This group likely included teams focused on non-COVID-19 research. Separately, a small percentage of researchers (12%) said the pandemic has accelerated their investments – a trend seen in many companies trying to help with solutions related to the pandemic.

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