Automation and standardisation of clinical molecular testing using PCR.Ai - A comparative performance study

Area of Science:

• Clinical diagnostics
• Molecular biology
• Infectious disease research

Background:

• Routine clinical pathogen testing relies on manual data analysis and quality control for real-time PCR (qPCR).
• Automating these steps can improve efficiency and accuracy in diagnostic laboratories.

Purpose of the Study:

• To evaluate the accuracy and impact of PCR.Ai in automating manual data analysis and quality control for clinical qPCR assays.
• To assess time savings and complexity reduction in qPCR analysis.

Main Methods:

• A prospective clinical study was conducted to compare PCR.Ai with manual interpretation for routine in-house qPCR tests.
• Evaluated 22,200 interpretations for respiratory pathogens and norovirus detection.

Main Results:

• PCR.Ai demonstrated 100% concurrence with manual methods for respiratory virus and norovirus detection.
• Achieved significant time savings: 45 minutes per respiratory run and 32 minutes per norovirus run.
• Reduced hands-on time and complexity of qPCR analysis.

Conclusions:

• PCR.Ai is a highly accurate, time-saving tool for qPCR analysis.
• It reduces the need for specialists and minimizes the risk of errors.
• Enables faster results, lower costs, and improved diagnostic workflow.