Statistical Methodology to Develop Robust Dengue qRT-PCR Assays

• Activity Number: 547
• Type: Contributed
• Date/Time: Wednesday, August 7, 2013 : 10:30 AM to 12:20 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Lingyi Zheng*+ and Linda Starr-Spires
• Companies: GCI, Sanofi Pasteur and GCI, Sanofi Pasteur
• Keywords: qRT-PCR ; Bioassay ; Robustness ; Split-plot ; Mixed Model

Abstract

It is critical for the biopharmaceutical industry to develop suitable bioassays in the early phases of projects and validate them before testing Phase III clinical samples. For vaccine trials where detection of infectious agents is part of case definition and study endpoint, PCR-based assays play an increasingly important role. Developing fast, robust, reliable and sensitive quantitative reverse transcriptase-based PCR (qRT-PCR) is a critical step in supporting late stage clinical studies of RNA viral vaccines. Operating a qRT-PCR assay typically requires multiple steps and the robustness of the PCR can be assessed using split-plot design to evaluate the impact of changes in PCR parameters. To validate the qRT-PCR, mixed models can be used to determine PCR repeatability and intermediate precision whereas the positive detection rate can be used to identify the lower limit of PCR detection and quantitation cutoff. The approach to statistical design support of assay development and validation has greatly enhanced the quality and robust qRT-PCR. The knowledge acquired from statistical design has helped to design qRT-PCR suitable for supporting large-scale multi-year clinical studies.