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3 ways automation can lead to better biolab results

Accuracy in laboratory experiments is critical but often elusive—especially in life sciences laboratories. Here are 3 areas where automation can help. Accuracy in laboratory experiments is critical but often elusive—especially in life sciences laboratories. This is primarily because many protocols and procedures are done manually, leaving systematic opportunities for pipetting errors, wasted materials, and lost time.

Automation can eliminate these difficulties and greatly reduce inaccuracies, resulting in more consistent results. Here are 3 areas where automation is particularly beneficial for life sciences laboratories.

1) Replicability Replicability—the ability of researchers to test the feasibility of experimental results using the same methods on the same samples and check whether data sets are consistent—is key to conducting successful research. This is also the best way to ensure consistency between experiments.

However, if you perform these procedures manually, errors may occur simply depending on who performs the experiment. This is the myth of the “magic hand” in biology—researchers can make a measurement almost exactly the same way every time. There is often no documentation describing this "magical" technique, so there is almost no way to replicate it accurately. Additionally, anyone else trying to recreate a specific assay may still encounter errors due to using different techniques.

移液器生物實驗

With automation, replicating results is closer to downloading the protocol and running it on a robot. Each assay is performed in the same way, eliminating any doubts or difficulties in replication.

2) Reproducibility Reproducibility (or the ability to analyze an experiment's original methods and data and use them to produce similar results in another laboratory) is also critical to conducting successful research. It is also the best way to ensure consistency between protocols and to determine whether data analysis can be successfully repeated.

Many labs still keep their protocol collections in hard copy form—PDFs in binders, with notes scrawled in the margins as guidance. Since these protocols are often performed manually, given the researcher's interpretation of these annotations, errors can occur throughout all aspects of the protocol from execution to results.

With automation, experimental protocols do not need to be redesigned: they are created once and run the same way every time, eliminating any chance of systematic errors. Additionally, because documentation can be added, protocols are often more comprehensive, accessible, and actionable than manual protocols.

3) Sharing In addition to copying and reproducing experimental protocols, the ability to share experimental protocols is critical to continue creating new knowledge and contributing to the inheritance of scientific discoveries. However, there is no standard format or requirement for sharing methods or the reagents and laboratory equipment used in publications. There are also no standards for sharing protocols, as most information is conveyed in person in the lab, shared in binders, or informally. Researchers also don’t share empty data, meaning they don’t share what didn’t work for them or any insights that led them to this approach to their work.

Automation provides a standard format for recording and sharing experimental protocols, reagents, labware, and any other necessary information needed to perform experiments. It also eliminates all variables when sharing any information and provides a common platform for sharing information with lab members and colleagues around the world.

All of these benefits are not only useful, but critical to how life research is conducted. In biology, the only way to ensure all of these things is through automation.

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