Reducing time and error rates by automating qPCR workflows

Matjaž Hren1, Kristina Gruden2, Klemen Zupančič1, Nataša Mehle2, Manca Pirc1,2, Urška Čepin1, Maja Ravnikar2
1BioSistemika LLC, Slovenia; 
2National Institute of Biology, Slovenia

Abstract
Advanced technologies are being employed in the labs with the main aim to solve problems, improve existing solutions and help achieve the goals set by and for researchers. The major challenges researchers are facing today are: keeping up with the ever-rising workload and data analysis requirements. Lab automation market research conclusions suggest that almost 50% of researchers’ time is still spent on data and information tasks. Therefore, the most dramatic changes are expected to occur in hardware and software technologies and regulatory areas. Due to the overall complexity and non-flexibility of most solutions available today, there is a growing need for smart solutions which combine the ease of use, flexibility and reliability.
A growing challenge in laboratories dealing with high throughput real-time PCR (qPCR) analyses for diagnostic or research purposes is how to make the complete process from sample preparation to data analysis, interpretation and reporting faster without compromising traceability and reliability of the results. We are presenting a case study on detection of bacteria with qPCR in plant samples, showing improvements on two levels: at the level of wet-lab automation and at the level of complete process management using a web-based smart qPCR dedicated set of software tools.
New improvements on sample handling such as automated simple and quick homogenization and automated magnetic bead based DNA extraction method greatly increase the speed of sample processing without compromising the DNA extraction. Additional improvements include facilitation of loading of mastermixes and samples onto qPCR plates using a smart pipetting assistant device. Further on, the use of dedicated software tools automates and reduces the time needed for complex, repetitive, time consuming actions like experiment design, creation of templates for lab work, data analysis, result interpretation and reporting. The full traceability of all researchers’ actions within the qPCR workflow is automatically being saved. All information is being stored in one place in a quality assurance compliant way (ISO 17025). Powerful search enables researchers to instantly find any needed data. Communication with LIMS and different qPCR thermal cyclers is also being established. In addition, external protocols and files including sample images and similar are being easily uploaded and stored. The set of software tools enables lab managers to have complete overview on the work progress in their labs and access to real time lab performance from different locations.
Such modern approach can save up to 40% of time spent on data and information tasks. It reduces error rates and the burden of ever-rising workload on the key lab personnel, which is of extreme importance in case of high throughput qPCR.

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