Informing selection of drugs for COVID-19 treatment through adverse events analysis

Abstract Coronavirus disease 2019 (COVID-19) is an ongoing pandemic and there is an urgent need for safe and effective drugs for COVID-19 treatment. Since developing a new drug is time consuming, many approved or investigational drugs have been repurposed for COVID-19 treatment in clinical trials. T...

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Autores principales:	Wenjing Guo, Bohu Pan, Sugunadevi Sakkiah, Zuowei Ji, Gokhan Yavas, Yanhui Lu, Takashi E. Komatsu, Madhu Lal-Nag, Weida Tong, Tucker A. Patterson, Huixiao Hong
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/cec1715e9fd24f53a1ff4e77983d08f9
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spelling	oai:doaj.org-article:cec1715e9fd24f53a1ff4e77983d08f92021-12-02T15:23:16ZInforming selection of drugs for COVID-19 treatment through adverse events analysis10.1038/s41598-021-93500-52045-2322https://doaj.org/article/cec1715e9fd24f53a1ff4e77983d08f92021-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-93500-5https://doaj.org/toc/2045-2322Abstract Coronavirus disease 2019 (COVID-19) is an ongoing pandemic and there is an urgent need for safe and effective drugs for COVID-19 treatment. Since developing a new drug is time consuming, many approved or investigational drugs have been repurposed for COVID-19 treatment in clinical trials. Therefore, selection of safe drugs for COVID-19 patients is vital for combating this pandemic. Our goal was to evaluate the safety concerns of drugs by analyzing adverse events reported in post-market surveillance. We collected 296 drugs that have been evaluated in clinical trials for COVID-19 and identified 28,597,464 associated adverse events at the system organ classes (SOCs) level in the FDA adverse events report systems (FAERS). We calculated Z-scores of SOCs that statistically quantify the relative frequency of adverse events of drugs in FAERS to quantitatively measure safety concerns for the drugs. Analyzing the Z-scores revealed that these drugs are associated with different significantly frequent adverse events. Our results suggest that this safety concern metric may serve as a tool to inform selection of drugs with favorable safety profiles for COVID-19 patients in clinical practices. Caution is advised when administering drugs with high Z-scores to patients who are vulnerable to associated adverse events.Wenjing GuoBohu PanSugunadevi SakkiahZuowei JiGokhan YavasYanhui LuTakashi E. KomatsuMadhu Lal-NagWeida TongTucker A. PattersonHuixiao HongNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-7 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Wenjing Guo Bohu Pan Sugunadevi Sakkiah Zuowei Ji Gokhan Yavas Yanhui Lu Takashi E. Komatsu Madhu Lal-Nag Weida Tong Tucker A. Patterson Huixiao Hong Informing selection of drugs for COVID-19 treatment through adverse events analysis
description	Abstract Coronavirus disease 2019 (COVID-19) is an ongoing pandemic and there is an urgent need for safe and effective drugs for COVID-19 treatment. Since developing a new drug is time consuming, many approved or investigational drugs have been repurposed for COVID-19 treatment in clinical trials. Therefore, selection of safe drugs for COVID-19 patients is vital for combating this pandemic. Our goal was to evaluate the safety concerns of drugs by analyzing adverse events reported in post-market surveillance. We collected 296 drugs that have been evaluated in clinical trials for COVID-19 and identified 28,597,464 associated adverse events at the system organ classes (SOCs) level in the FDA adverse events report systems (FAERS). We calculated Z-scores of SOCs that statistically quantify the relative frequency of adverse events of drugs in FAERS to quantitatively measure safety concerns for the drugs. Analyzing the Z-scores revealed that these drugs are associated with different significantly frequent adverse events. Our results suggest that this safety concern metric may serve as a tool to inform selection of drugs with favorable safety profiles for COVID-19 patients in clinical practices. Caution is advised when administering drugs with high Z-scores to patients who are vulnerable to associated adverse events.
format	article
author	Wenjing Guo Bohu Pan Sugunadevi Sakkiah Zuowei Ji Gokhan Yavas Yanhui Lu Takashi E. Komatsu Madhu Lal-Nag Weida Tong Tucker A. Patterson Huixiao Hong
author_facet	Wenjing Guo Bohu Pan Sugunadevi Sakkiah Zuowei Ji Gokhan Yavas Yanhui Lu Takashi E. Komatsu Madhu Lal-Nag Weida Tong Tucker A. Patterson Huixiao Hong
author_sort	Wenjing Guo
title	Informing selection of drugs for COVID-19 treatment through adverse events analysis
title_short	Informing selection of drugs for COVID-19 treatment through adverse events analysis
title_full	Informing selection of drugs for COVID-19 treatment through adverse events analysis
title_fullStr	Informing selection of drugs for COVID-19 treatment through adverse events analysis
title_full_unstemmed	Informing selection of drugs for COVID-19 treatment through adverse events analysis
title_sort	informing selection of drugs for covid-19 treatment through adverse events analysis
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/cec1715e9fd24f53a1ff4e77983d08f9
work_keys_str_mv	AT wenjingguo informingselectionofdrugsforcovid19treatmentthroughadverseeventsanalysis AT bohupan informingselectionofdrugsforcovid19treatmentthroughadverseeventsanalysis AT sugunadevisakkiah informingselectionofdrugsforcovid19treatmentthroughadverseeventsanalysis AT zuoweiji informingselectionofdrugsforcovid19treatmentthroughadverseeventsanalysis AT gokhanyavas informingselectionofdrugsforcovid19treatmentthroughadverseeventsanalysis AT yanhuilu informingselectionofdrugsforcovid19treatmentthroughadverseeventsanalysis AT takashiekomatsu informingselectionofdrugsforcovid19treatmentthroughadverseeventsanalysis AT madhulalnag informingselectionofdrugsforcovid19treatmentthroughadverseeventsanalysis AT weidatong informingselectionofdrugsforcovid19treatmentthroughadverseeventsanalysis AT tuckerapatterson informingselectionofdrugsforcovid19treatmentthroughadverseeventsanalysis AT huixiaohong informingselectionofdrugsforcovid19treatmentthroughadverseeventsanalysis
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Informing selection of drugs for COVID-19 treatment through adverse events analysis

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