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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2023
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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. |
format | Online Article Text |
id | pubmed-10041137 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
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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