How to ensure quality control in a lab

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Automation is present in every aspect of life, from our daily visits to the shops, using our phones, and even commuting to work. In line with this, we are seeing a greater proportion of industry, academia, and healthcare sectors shifting towards automated technology to benefit their science. As we move towards a paperless lab, many manual processes are utilising automation to streamline workflows, and this includes quality control. Automation of quality control processes reduces the error and variability seen with manual processes, therefore offering the opportunity to revolutionise this work (1).

What is quality control in the laboratory?

Quality control within a laboratory measures the precision and reproducibility of workflow outcomes compared to benchmarked thresholds. It safeguards the accuracy, and reliability of practices in laboratories, to eliminate the risk of non-conforming outcomes.

Quality control is split into two parts, internal and external (2). Internal quality control assesses the daily precision and accuracy of workflows, generally using internal positive and negative standards within protocols at each step of a set process. Contrastingly,  external quality control looks at the long-term precision and accuracy of workflows. This is typically completed by comparing data from other laboratories performing the same workflows. Both internal and external quality control can benefit from incorporating automation into their protocols, offering companies the potential to save both time and money.

What is automated quality control?

By removing high volumes of manual intervention, automation can support enhanced consistency throughout workflows. This can be achieved through the use of optimised metrics that are time-saving and efficient, thus requiring less human effort to complete quality auditing. Embedding automated software and machinery in laboratories eases the burden of manual intervention and data processing for quality control and assurance. This allows for real-time detection of issues and faults in samples or data, thus supporting labs to become more cost-effective and increasing productivity (3).

Which QC processes can be automated?

Detailed and consistent monitoring of laboratory processes, can lead to fewer investigations, saving companies both money and time. The digitalisation of internal and external quality control in the laboratory allows for faster detection and action in response to quality control issues. 

For example, automating data transcription within Laboratory Information Management systems (LIMS) for cell line development, allows laboratories to share data externally with quality control assessors, to streamline external quality control analysis. Embedded control spots throughout laboratory processes allow for internal inspection to run continuously which safeguards cell line quality. Automation offers sophisticated reporting and quicker interventions which reduces the waste of reagents and samples required for repeating work. Ultimately this saves time and enhances cost efficiency, therefore increasing revenue. 

The benefits of automated QC in the lab

Automation is integral to drive forward scientific breakthroughs and improve precision medicine. Automated quality control enables faster problem-solving and intervention when failings in product compliance threaten a loss in revenue. The ability to target specific areas of discrepancy in quality control enables teams to direct resources and resolutions more efficiently. 

Manual quality control inspections are intense, laborious jobs, susceptible to human error and subjective observations. Removing the subjectivity and risk of error by automating quality control processes improves laboratory efficiency. Additionally, improvements in error reporting through the provision of detailed paper trails allow users to trace back historical records for effective quality control and laboratory management.

As laboratories in industry, healthcare, and academia begin to embrace automation throughout their workflows, investments into automation and artificial intelligence will offer a new direction for fully automated laboratory systems. Ultimately, providing effective automated quality control procedures will enhance the laboratory landscapes of the future.

References:

  1. Shah M. Introducing AI-Powered Automated Quality Control to Accelerate Data-Driven Drug Development – Proscia [Internet]. Proscia. 2022. Available from: https://proscia.com/introducing-ai-powered-automated-quality-control-to-accelerate-data-driven-drug-development/
  2. Digitization, automation, and online testing: Embracing smart quality control [Internet]. 2021 Available from: https://www.mckinsey.com/industries/life-sciences/our-insights/digitization-automation-and-online-testing-embracing-smart-quality-control
  3. inc. L. Automated Quality Control Systems [Internet]. Creaform’s Blog – News, Tips & Tricks about 3D technologies, 3D Scanning, QC/Inspection, Reverse Engineering & More. . Available from: https://www.creaform3d.com/blog/automated-quality-control-systems/

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