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Artificial Intelligence-Assisted Loop Mediated Isothermal Amplification (ai-LAMP) for Rapid Detection of SARS-CoV-2

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Artificial Intelligence-Assisted Loop Mediated Isothermal Amplification (ai-LAMP) for Rapid Detection of SARS-CoV-2. / Rohaim, Mohammed; Clayton, Emily; Sahin, Irem et al.
In: Viruses, Vol. 12, No. 9, 972, 01.09.2020.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Rohaim, M, Clayton, E, Sahin, I, Vilela, J, Khalifa, M, Al-Natour, M, Bayoumi, M, Poirier, AC, Branavan, M, Tharmakulasingam, M, Choudhry, MS, Sodi, R, Brown, A, Burkhart, P, Hacking, W, Botham, J, Boyce, J, Wilkinson, H, Williams, C, Whittingham-Dowd, J, Shaw, E, Hodges, M, Butler, L, Bates, M, La Ragione, R, Balachandran, W, Fernando, A & Munir, M 2020, 'Artificial Intelligence-Assisted Loop Mediated Isothermal Amplification (ai-LAMP) for Rapid Detection of SARS-CoV-2', Viruses, vol. 12, no. 9, 972. https://doi.org/10.3390/v12090972

APA

Rohaim, M., Clayton, E., Sahin, I., Vilela, J., Khalifa, M., Al-Natour, M., Bayoumi, M., Poirier, A. C., Branavan, M., Tharmakulasingam, M., Choudhry, M. S., Sodi, R., Brown, A., Burkhart, P., Hacking, W., Botham, J., Boyce, J., Wilkinson, H., Williams, C., ... Munir, M. (2020). Artificial Intelligence-Assisted Loop Mediated Isothermal Amplification (ai-LAMP) for Rapid Detection of SARS-CoV-2. Viruses, 12(9), Article 972. https://doi.org/10.3390/v12090972

Vancouver

Rohaim M, Clayton E, Sahin I, Vilela J, Khalifa M, Al-Natour M et al. Artificial Intelligence-Assisted Loop Mediated Isothermal Amplification (ai-LAMP) for Rapid Detection of SARS-CoV-2. Viruses. 2020 Sept 1;12(9):972. doi: 10.3390/v12090972

Author

Rohaim, Mohammed ; Clayton, Emily ; Sahin, Irem et al. / Artificial Intelligence-Assisted Loop Mediated Isothermal Amplification (ai-LAMP) for Rapid Detection of SARS-CoV-2. In: Viruses. 2020 ; Vol. 12, No. 9.

Bibtex

@article{bc479cb6087a418c8cf634bdaf4c393d,
title = "Artificial Intelligence-Assisted Loop Mediated Isothermal Amplification (ai-LAMP) for Rapid Detection of SARS-CoV-2",
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.",
keywords = "SARS-CoV-2, diagnosis, LAMP, point of care, artificial intelligence",
author = "Mohammed Rohaim and Emily Clayton and Irem Sahin and Julianne Vilela and Manar Khalifa and Mohammad Al-Natour and Mahmoud Bayoumi and Poirier, {Aurore C.} and Manoharanehru Branavan and Makunthan Tharmakulasingam and Choudhry, {Mouman S.} and Ravinder Sodi and Amy Brown and Peter Burkhart and Wendy Hacking and Judy Botham and Joe Boyce and Hayley Wilkinson and Craig Williams and Jayde Whittingham-Dowd and Elisabeth Shaw and Matt Hodges and Lisa Butler and Michelle Bates and {La Ragione}, Roberto and Wamadeva Balachandran and Anil Fernando and Muhammad Munir",
year = "2020",
month = sep,
day = "1",
doi = "10.3390/v12090972",
language = "English",
volume = "12",
journal = "Viruses",
issn = "1999-4915",
publisher = "MDPI AG",
number = "9",

}

RIS

TY - JOUR

T1 - Artificial Intelligence-Assisted Loop Mediated Isothermal Amplification (ai-LAMP) for Rapid Detection of SARS-CoV-2

AU - Rohaim, Mohammed

AU - Clayton, Emily

AU - Sahin, Irem

AU - Vilela, Julianne

AU - Khalifa, Manar

AU - Al-Natour, Mohammad

AU - Bayoumi, Mahmoud

AU - Poirier, Aurore C.

AU - Branavan, Manoharanehru

AU - Tharmakulasingam, Makunthan

AU - Choudhry, Mouman S.

AU - Sodi, Ravinder

AU - Brown, Amy

AU - Burkhart, Peter

AU - Hacking, Wendy

AU - Botham, Judy

AU - Boyce, Joe

AU - Wilkinson, Hayley

AU - Williams, Craig

AU - Whittingham-Dowd, Jayde

AU - Shaw, Elisabeth

AU - Hodges, Matt

AU - Butler, Lisa

AU - Bates, Michelle

AU - La Ragione, Roberto

AU - Balachandran, Wamadeva

AU - Fernando, Anil

AU - Munir, Muhammad

PY - 2020/9/1

Y1 - 2020/9/1

N2 - 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.

AB - 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.

KW - SARS-CoV-2

KW - diagnosis

KW - LAMP

KW - point of care

KW - artificial intelligence

U2 - 10.3390/v12090972

DO - 10.3390/v12090972

M3 - Journal article

VL - 12

JO - Viruses

JF - Viruses

SN - 1999-4915

IS - 9

M1 - 972

ER -