Technology shaping accuracy and precision in the lab

Managing data is vital in the lab industry – it is at the heart of all research and development. If data is improperly collected or stored it can be lost before analysis is done, impede the research process and prevent results from being verified. Whether or not you are using technology to record data or taking manual notes to store information, accuracy is crucial. The downside of manual data collection is that this method increases the risk of human error, poor data security and data siloes, and may result in incomplete data sets. Yet a global report shows that scientists, researchers and investigators still haven’t automated over half of their lab operations. The good news is that many would like to boost the use of new technologies in order to produce more reliable results, reduce errors, and improve trend analysis.

Other areas of technology that will reform the lab industry, supporting both accuracy and precision includes connectivity and data digitalization. The latter, which can be closely linked to the implementation of a LIMS and AI to manage data, focuses on the growing requirement for cloud-based storage. Hard drives and local servers can no longer be an option for labs who want to store their data securely and access it worldwide. Additionally, with concerns surrounding privacy and internet security, this will need to be combined with specialized encryption software and employee training on data-sharing, confidentiality as well as any relevant legislation. Interconnectivity between equipment and instruments will also improve processes within the lab. For example, monitoring equipment such as incubators and freezers – or even the wash temperatures and the dosage amount of your lab glasswashers – guarantees the protection of samples and instruments, ensures high quality results, and supports compliance. According to The Scientist, automated sequencers and data analysis software that can send information to digital notebooks will also aid lab professionals with the accuracy of results and data collaboration.