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Fighting COVID-19 with Artificial Intelligence.
Monteleone, Stefania; Kellici, Tahsin F; Southey, Michelle; Bodkin, Michael J; Heifetz, Alexander.
Afiliación
  • 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 en En | MEDLINE | ID: mdl-34731465
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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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Antivirales / Inteligencia Artificial / Descubrimiento de Drogas / Reposicionamiento de Medicamentos / SARS-CoV-2 / Tratamiento Farmacológico de COVID-19 Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Animals / Humans Idioma: En Revista: Methods Mol Biol Asunto de la revista: BIOLOGIA MOLECULAR Año: 2022 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Antivirales / Inteligencia Artificial / Descubrimiento de Drogas / Reposicionamiento de Medicamentos / SARS-CoV-2 / Tratamiento Farmacológico de COVID-19 Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Animals / Humans Idioma: En Revista: Methods Mol Biol Asunto de la revista: BIOLOGIA MOLECULAR Año: 2022 Tipo del documento: Article País de afiliación: Reino Unido