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You have probably heard the saying “why work harder when you can work smarter?” While this may seem like a cliché, there is no denying that smart work, or what might be more accurately termed “efficient effort,” not only alleviates worker stress but in doing so minimizes human error while creating opportunities for increased productivity and creativity.

In an earlier post on lab automation, we discussed how increased workloads and human error have contributed to a crisis of reproducibility and repeatability in the research community. To summarize, repeatability and reproducibility provide the foundation upon which the scientific method is built. The results of academic research only retain value for the wider scientific community when the conditions that produce such results can be repeated and shared amongst other researchers.

There are several best practices that can contribute to ensuring repeatability and reproducibility of research by maintaining the conditions under which lab work is conducted. These include, among other factors, consistency in the location or research environments, the tools used for measurement as well as other equipment used in experiments, and the routines and processes used to gather and analyze data.

As discussed in the previous blog post, automation of data gathering and analysis has been one of the best ways to ensure consistency and repeatability while helping to eliminate human error, as outlined in a 2019 article on improving reproducibility in synthetic biology through automation:

“The successful implementation of automation technology can help to improve both the throughput and reproducibility of experiments, although the high cost and lack of flexibility of traditional lab automation has so far hindered their wide-spread adoption in academia. Recently though, there have been advances in automation technology that, when combined with new protocol sharing methods and protocol management systems, may allow for researchers to gain the benefits of automation.”

—Jessop-Fabre and Sonnenschein

Before when discussing how to automate routines for data acquisition and analysis, the focus has been on the use of scripts to string together processes. While this achieves the goal of creating laboratory conditions that are more readily repeatable, scripting requires a specific skill set. This brings us back to the notion of working smarter, not harder.Plan Smart

Previous versions of BIOPAC’s own AcqKnowledge data gathering and analysis software offered a powerful Scripting tool as an add-on licensed feature. The latest version of AcqKnowledge supports a new licensed feature with Scripting called Workflow. Workflow takes all the functionality of scripts and places it in an easy-to-use, drag-and-drop interface that requires no prior scripting knowledge.

Workflow is the embodiment of the “work smarter, not harder” philosophy, allowing users to create automated routines to process and analyze data under consistent and repeatable conditions. By speeding signal conditioning and preparation for analysis, Workflow boosts efficiency. The ability to save and share workflows makes it easier for colleagues and reviewers to replicate research conditions. BIOPAC CEO, Frazer Findlay hosted a recent webinar in which he provided a detailed introduction to creating automated routines with Workflow.

For additional information on the latest version of BIOPAC’s AcqKnowledge software as well as other research tools and how they can help streamline your lab work, contact your local sales representative.

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