Latest qPCR software introduced

Gilson, a leader in manual and automated liquid sample preparation solutions, has announced the launch of the new qPCR Assistant software, which reduces the hands-on sample preparation burden for researchers running PCR and qPCR experiments in translational science and other research areas.

With the increasing need for biomarker validation using qPCR and PCR techniques across a variety of biological samples, researchers are seeking new ways to maximise qPCR sample preparation accuracy and reproducibility, eliminate inherent variability and minimise sources of contamination. The qPCR Assistant is a workflow-focused solution, based on the recently introduced PIPETMAX automated ‘lab assistant’ pipetting station. Developed by molecular biologists, it puts molecular biologists in the driver’s seat by combining an intuitive user interface and versatile qPCR-focused design of experiment workflow with a familiar Gilson PIPETMAN-inside accurate automated ‘lab assistant’.

“I created a qPCR experiment from scratch in minutes with PIPETMAX qPCR Assistant, without having to know any details about liquid handling. The PIPETMAX qPCR Assistant also instructed me on the labware positions, how and what to prepare for each run, and exported a template file for my thermocycler, which made the whole process of creating and running the protocol very time efficient. The optimised qPCR plate setup enabled method and pipetting efficiency and the method traceability provides the reassurance of reproducible results,” said David Dobnik, PhD, GMO detection lab, Department of Systems Biology and Biotechnology, National Institute of Biology, Ljubljana, Slovenia.

The qPCR Assistant software also generates a traceability output report that provides the experimental design details and plate locations for the thermocycler. Repeating qPCR experiments is simplified with a drop-down menu and selecting your previously designed method. In addition, the traceability provides an added level of electronic security helping to eliminate manual errors, maximising reproducibility and further saving the researcher time.

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