Early Evaluation of the Food and Drug Administration (FDA) Adverse Event Monitoring System (AEMS): An Analysis of Over 32 Million Pharmacovigilance Reports

INTRODUCTION: Post-marketing pharmacovigilance systems are essential for detecting adverse drug reactions not identified during pre-marketing clinical trials. The United States Food and Drug Administration (FDA) introduced the Adverse Event Monitoring System (AEMS) public dashboard on March 11, 2026, a new platform that provides near-real-time access to data from the FDA Adverse Event Reporting System (FAERS). This interface allows clinicians and researchers to query pharmacovigilance data through an interactive visualization platform without requiring advanced data processing. To describe the structure, available features, and reporting patterns of the newly released AEMS dashboard, this study provides an exploratory descriptive analysis of FAERS report characteristics. METHODS: A cross-sectional descriptive analysis was conducted using data available through the FDA AEMS public dashboard on the day of its public release. The dashboard modules were explored, and datasets were exported using the built-in data download functionality. Variables examined included total report counts, seriousness of reports, death outcomes, patient sex distribution, reporter type, reporting region, annual reporting trends, and products with the highest total adverse event counts. Descriptive statistics were used to summarize available pharmacovigilance data. RESULTS: At the time of analysis, the AEMS dashboard contained 32,815,201 adverse event reports submitted to FAERS. Among these reports, 17,929,119 reports (54.6%) were classified as serious (excluding death), while 2,899,382 reports (8.8%) involved death outcomes. Female patients accounted for 17,292,788 (52.7%) reports, compared with 11,455,663 (34.9%) reports among male patients, while 4,066,750 (12.4%) reports did not specify sex. Annual report volumes increased substantially after 2014, exceeding two million reports annually during recent years, with 2,359,318 reports recorded in 2022 and 2,211,235 reports recorded in 2023. CONCLUSIONS: This study provides one of the earliest evaluations of the newly released FDA AEMS dashboard and demonstrates its capability to support rapid exploratory pharmacovigilance analysis. The use of publicly accessible data improves transparency and reproducibility of pharmacovigilance research. However, inherent limitations of spontaneous reporting databases, including underreporting, reporting bias, incomplete clinical data, and inability to establish causality, remain important considerations when interpreting findings derived from the system.

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Journal
Cureus
Published
2026-04-01
DOI
https://doi.org/10.7759/cureus.106259
Primary Topic
Pharmacovigilance and Adverse Drug Reactions
Type
article
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article

Early Evaluation of the Food and Drug Administration (FDA) Adverse Event Monitoring System (AEMS): An Analysis of Over 32 Million Pharmacovigilance Reports

Shaheen Emmanuel Lakhan
Cureus
Pharmacovigilance and Adverse Drug Reactions
article

Early Evaluation of the Food and Drug Administration (FDA) Adverse Event Monitoring System (AEMS): An Analysis of Over 32 Million Pharmacovigilance Reports

Shaheen Emmanuel Lakhan
article en

Abstract

INTRODUCTION: Post-marketing pharmacovigilance systems are essential for detecting adverse drug reactions not identified during pre-marketing clinical trials. The United States Food and Drug Administration (FDA) introduced the Adverse Event Monitoring System (AEMS) public dashboard on March 11, 2026, a new platform that provides near-real-time access to data from the FDA Adverse Event Reporting System (FAERS). This interface allows clinicians and researchers to query pharmacovigilance data through an interactive visualization platform without requiring advanced data processing. To describe the structure, available features, and reporting patterns of the newly released AEMS dashboard, this study provides an exploratory descriptive analysis of FAERS report characteristics. METHODS: A cross-sectional descriptive analysis was conducted using data available through the FDA AEMS public dashboard on the day of its public release. The dashboard modules were explored, and datasets were exported using the built-in data download functionality. Variables examined included total report counts, seriousness of reports, death outcomes, patient sex distribution, reporter type, reporting region, annual reporting trends, and products with the highest total adverse event counts. Descriptive statistics were used to summarize available pharmacovigilance data. RESULTS: At the time of analysis, the AEMS dashboard contained 32,815,201 adverse event reports submitted to FAERS. Among these reports, 17,929,119 reports (54.6%) were classified as serious (excluding death), while 2,899,382 reports (8.8%) involved death outcomes. Female patients accounted for 17,292,788 (52.7%) reports, compared with 11,455,663 (34.9%) reports among male patients, while 4,066,750 (12.4%) reports did not specify sex. Annual report volumes increased substantially after 2014, exceeding two million reports annually during recent years, with 2,359,318 reports recorded in 2022 and 2,211,235 reports recorded in 2023. CONCLUSIONS: This study provides one of the earliest evaluations of the newly released FDA AEMS dashboard and demonstrates its capability to support rapid exploratory pharmacovigilance analysis. The use of publicly accessible data improves transparency and reproducibility of pharmacovigilance research. However, inherent limitations of spontaneous reporting databases, including underreporting, reporting bias, incomplete clinical data, and inability to establish causality, remain important considerations when interpreting findings derived from the system.

CureusVol. 18(4)
Bioscience (China) (CN), Global Neuroscience Initiative Foundation (US), A.T. Still University (US), Morehouse School of Medicine (US), Western University of Health Sciences (US)
Openalex Percentile: Top 35%
Pharmacovigilance and Adverse Drug Reactions
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