qPCR error rates

Studies have shown prevalent qPCR methods to have as high as a 20% error rate. In fact, a recent article in the Wall Street Journal called lab testing the “Wild West of Medicine.” In academic literature, global diagnostic rates for all test types are recorded as averaging 1 in 20 (National Academies of Sciences, Engineering, and Medicine (2015); Improving diagnosis in health care; The National Academies Press).

An NHS hospital, Edinburgh Royal Infirmary, recorded error rates of up to 20% (“mainly due to errors in manual analysis”) when using a semi-automated qPCR test for monitoring CMV infections in immunocompromised patients.
In comparison, results demonstrating that pcr.ai technology had no analysis errors when used with a semi-automated CMV test were published by NHS G&C hospital (Journal of Clinical Virology: Volume 70, Supplement 1 (Sept 2015)- abstracts 1585 and 1736 respectively).

Jurisdiction Number    
Australia 2009352527
Canada 2855922
Canada 2817220
European Union 2766718
United States 8660968
United States 8738303
United States 9026481
United States 9043249
Title Partner Year Results & key findings
[Work-in-progress] Johns Hopkins University 2017 250,000+ samples processed, comparison so far with manual shows concordance well above 99%
AccuCall™: A Novel Solution for the Automated Interpretation and QC of in-house, Real Time PCR Results NHS Glasgow, UK 2015 -2250 samples; 100% concordance
- 90% quicker than a technician
Utilization of Azure PCR AccuCall Software to Improve Analysis of PCR Data University of Washington, USA 2015 -4496 samples, 100% concordance
-more accurate than ABI
-quicker, more efficient
Novel Solution Automates qPCR Diagnostics for Qualitative and Quantitative Data without Loss of Accuracy NHS Glasgow, UK 2013 2500+ samples; 100% concordance
Novel, Fully Automated Method Allows Efficient Analysis of qPCR Data for Qualitative Calling Based on Comparative Cq DuPont Pioneer, USA 2012 4000+ samples; 99.8% concordance
Automated data interpretation of H1N1/09 ('swine') influenza Real-time PCR data St. Georges NHS Trust, UK 2010 2,500+ samples; 99.1% concordance