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

Autor: 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
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Scientific Reports, Vol 11, Iss 1, Pp 1-7 (2021)
Druh dokumentu: article
ISSN: 2045-2322
DOI: 10.1038/s41598-021-93500-5
Popis: 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.
Databáze: Directory of Open Access Journals