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Fighting COVID-19 with Artificial Intelligence.
Monteleone, Stefania; Kellici, Tahsin F; Southey, Michelle; Bodkin, Michael J; Heifetz, Alexander.
  • Monteleone S; Evotec (UK) Ltd., Abingdon, Oxfordshire, UK. stefania.monteleone@evotec.com.
  • Kellici TF; Evotec (UK) Ltd., Abingdon, Oxfordshire, UK.
  • Southey M; Evotec (UK) Ltd., Abingdon, Oxfordshire, UK.
  • Bodkin MJ; Evotec (UK) Ltd., Abingdon, Oxfordshire, UK.
  • Heifetz A; Evotec (UK) Ltd., Abingdon, Oxfordshire, UK.
Methods Mol Biol ; 2390: 103-112, 2022.
Article in English | MEDLINE | ID: covidwho-1499335
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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Full text: Available Collection: International databases Database: MEDLINE Main subject: Antiviral Agents / Artificial Intelligence / Drug Discovery / Drug Repositioning / SARS-CoV-2 / COVID-19 Drug Treatment Type of study: Diagnostic study / Prognostic study Topics: Long Covid / Vaccines / Variants Limits: Animals / Humans Language: English Journal: Methods Mol Biol Journal subject: Molecular Biology Year: 2022 Document Type: Article Affiliation country: 978-1-0716-1787-8_3

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Antiviral Agents / Artificial Intelligence / Drug Discovery / Drug Repositioning / SARS-CoV-2 / COVID-19 Drug Treatment Type of study: Diagnostic study / Prognostic study Topics: Long Covid / Vaccines / Variants Limits: Animals / Humans Language: English Journal: Methods Mol Biol Journal subject: Molecular Biology Year: 2022 Document Type: Article Affiliation country: 978-1-0716-1787-8_3