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Fighting COVID-19 with Artificial Intelligence

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Artificial Intelligence in Drug Design

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2390))

Abstract

The development of vaccines for the treatment of COVID-19 is paving the way for new hope. Despite this, the risk of the virus mutating into a vaccine-resistant variant still persists. As a result, the demand of efficacious drugs to treat COVID-19 is still pertinent. To this end, scientists continue to identify and repurpose marketed drugs for this new disease. Many of these drugs are currently undergoing clinical trials and, so far, only one has been officially approved by FDA. Drug repurposing is a much faster route to the clinic than standard drug development of novel molecules, nevertheless in a pandemic this process is still not fast enough to halt the spread of the virus. Artificial intelligence has already played a large part in hastening the drug discovery process, not only by facilitating the selection of potential drug candidates but also in monitoring the pandemic and enabling faster diagnosis of patients. In this chapter, we focus on the impact and challenges that artificial intelligence has demonstrated thus far with respect to drug repurposing of therapeutics for the treatment of COVID-19.

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Authors and Affiliations

  1. Evotec (UK) Ltd., Abingdon, Oxfordshire, UK

    Stefania Monteleone, Tahsin F. Kellici, Michelle Southey, Michael J. Bodkin & Alexander Heifetz

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  1. Stefania Monteleone
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  2. Tahsin F. Kellici
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  3. Michelle Southey
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  4. Michael J. Bodkin
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  5. Alexander Heifetz
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Correspondence to Stefania Monteleone .

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Editors and Affiliations

  1. Computational Drug Discovery, Evotec (UK) Ltd., Abingdon, Oxfordshire, UK

    Alexander Heifetz

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Monteleone, S., Kellici, T.F., Southey, M., Bodkin, M.J., Heifetz, A. (2022). Fighting COVID-19 with Artificial Intelligence. In: Heifetz, A. (eds) Artificial Intelligence in Drug Design. Methods in Molecular Biology, vol 2390. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1787-8_3

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  • DOI: https://doi.org/10.1007/978-1-0716-1787-8_3

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1786-1

  • Online ISBN: 978-1-0716-1787-8

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