Molnupiravir, an urgently approved drug during the Coronavirus Disease 2019 (COVID-19) pandemic, serves as the basis for our study, which relies on the Food and Drug Administration Adverse Event Reporting System (FAERS). The objective is to extract adverse event (AE) signals associated with molnupiravir from the FAERS database, thereby providing a reference for post-marketing monitoring of adverse events. Specifically, we extracted individual case safety reports (ICSRs) from the database, focusing on cases with COVID-19 indications and molnupiravir identified as the primary suspect drug. Descriptive analysis of the extracted data was performed, followed by four disproportionality analyses using the reporting odds ratio (ROR) method. These analyses were conducted across four levels, encompassing overall data, reports by health professionals, as well as age and gender differentiations, ensuring the robustness of the analysis results. In total, 116,576 ICSRs with COVID-19 indications and 2,285 ICSRs with molnupiravir as the primary suspect were extracted. Notably, after excluding cases with unknown age or gender, a higher proportion of molnupiravir-related ICSRs were observed among individuals aged 65 years and older (70.07%) and women (54.06%). The most frequently reported adverse events and AE signals were associated with gastrointestinal disorders, as well as skin and subcutaneous tissue disorders. Moreover, individuals aged 65 years and older exhibited a higher risk of cardiac disorders, hepatobiliary disorders, renal and urinary disorders, and vascular disorders. In conclusion, this study found molnupiravir demonstrated a lower risk of serious adverse events compared to other RNA antiviral drugs like remdesivir in patients under 65 years old. However, close monitoring of its safety is still necessary for elderly patients aged 65 years and above. Further studies are warranted to continuously assess the safety profile of molnupiravir as its usage increases, especially in high risk populations.Copyright © 2023 Liang, Ma, Wang, Zheng, Su and Lyu.