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Computational prediction of interactions between Paxlovid and prescription drugs

Pfizer’s Paxlovid has recently been approved for the emergency use authorization (EUA) from the US Food and Drug Administration (FDA) for the treatment of mild-to-moderate COVID-19. Drug interactions can be a serious medical problem for COVID-19 patients with underlying medical conditions, such as h...

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Detalles Bibliográficos
Autores principales: Kim, Yeji, Ryu, Jae Yong, Kim, Hyun Uk, Lee, Sang Yup
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10041137/
https://www.ncbi.nlm.nih.gov/pubmed/36913586
http://dx.doi.org/10.1073/pnas.2221857120
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author Kim, Yeji
Ryu, Jae Yong
Kim, Hyun Uk
Lee, Sang Yup
author_facet Kim, Yeji
Ryu, Jae Yong
Kim, Hyun Uk
Lee, Sang Yup
author_sort Kim, Yeji
collection PubMed
description Pfizer’s Paxlovid has recently been approved for the emergency use authorization (EUA) from the US Food and Drug Administration (FDA) for the treatment of mild-to-moderate COVID-19. Drug interactions can be a serious medical problem for COVID-19 patients with underlying medical conditions, such as hypertension and diabetes, who have likely been taking other drugs. Here, we use deep learning to predict potential drug–drug interactions between Paxlovid components (nirmatrelvir and ritonavir) and 2,248 prescription drugs for treating various diseases.
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spelling pubmed-100411372023-03-28 Computational prediction of interactions between Paxlovid and prescription drugs Kim, Yeji Ryu, Jae Yong Kim, Hyun Uk Lee, Sang Yup Proc Natl Acad Sci U S A Biological Sciences Pfizer’s Paxlovid has recently been approved for the emergency use authorization (EUA) from the US Food and Drug Administration (FDA) for the treatment of mild-to-moderate COVID-19. Drug interactions can be a serious medical problem for COVID-19 patients with underlying medical conditions, such as hypertension and diabetes, who have likely been taking other drugs. Here, we use deep learning to predict potential drug–drug interactions between Paxlovid components (nirmatrelvir and ritonavir) and 2,248 prescription drugs for treating various diseases. National Academy of Sciences 2023-03-13 2023-03-21 /pmc/articles/PMC10041137/ /pubmed/36913586 http://dx.doi.org/10.1073/pnas.2221857120 Text en Copyright © 2023 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by/4.0/This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY) (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Biological Sciences
Kim, Yeji
Ryu, Jae Yong
Kim, Hyun Uk
Lee, Sang Yup
Computational prediction of interactions between Paxlovid and prescription drugs
title Computational prediction of interactions between Paxlovid and prescription drugs
title_full Computational prediction of interactions between Paxlovid and prescription drugs
title_fullStr Computational prediction of interactions between Paxlovid and prescription drugs
title_full_unstemmed Computational prediction of interactions between Paxlovid and prescription drugs
title_short Computational prediction of interactions between Paxlovid and prescription drugs
title_sort computational prediction of interactions between paxlovid and prescription drugs
topic Biological Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10041137/
https://www.ncbi.nlm.nih.gov/pubmed/36913586
http://dx.doi.org/10.1073/pnas.2221857120
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