Rohaim, Mohammed and Clayton, Emily and Sahin, Irem and Vilela, Julianne and Khalifa, Manar and Al-Natour, Mohammad and Bayoumi, Mahmoud and Poirier, Aurore C. and Branavan, Manoharanehru and Tharmakulasingam, Makunthan and Choudhry, Mouman S. and Sodi, Ravinder and Brown, Amy and Burkhart, Peter and Hacking, Wendy and Botham, Judy and Boyce, Joe and Wilkinson, Hayley and Williams, Craig and Whittingham-Dowd, Jayde and Shaw, Elisabeth and Hodges, Matt and Butler, Lisa and Bates, Michelle and La Ragione, Roberto and Balachandran, Wamadeva and Fernando, Anil and Munir, Muhammad (2020) Artificial Intelligence-Assisted Loop Mediated Isothermal Amplification (ai-LAMP) for Rapid Detection of SARS-CoV-2. Viruses, 12 (9): 972. ISSN 1999-4915
Full text not available from this repository.Abstract
Until vaccines and effective therapeutics become available, the practical solution to transit safely out of the current coronavirus disease 19 (CoVID-19) lockdown may include the implementation of an effective testing, tracing and tracking system. However, this requires a reliable and clinically validated diagnostic platform for the sensitive and specific identification of SARS-CoV-2. Here, we report on the development of a de novo, high-resolution and comparative genomics guided reverse-transcribed loop-mediated isothermal amplification (LAMP) assay. To further enhance the assay performance and to remove any subjectivity associated with operator interpretation of results, we engineered a novel hand-held smart diagnostic device. The robust diagnostic device was further furnished with automated image acquisition and processing algorithms and the collated data was processed through artificial intelligence (AI) pipelines to further reduce the assay run time and the subjectivity of the colorimetric LAMP detection. This advanced AI algorithm-implemented LAMP (ai-LAMP) assay, targeting the RNA-dependent RNA polymerase gene, showed high analytical sensitivity and specificity for SARS-CoV-2. A total of ~200 coronavirus disease (CoVID-19)-suspected NHS patient samples were tested using the platform and it was shown to be reliable, highly specific and significantly more sensitive than the current gold standard qRT-PCR. Therefore, this system could provide an efficient and cost-effective platform to detect SARS-CoV-2 in resource-limited laboratories.