Purpose <p>This study aimed to develop a visualization platform for querying and analysing data from the FDA Adverse Event Reporting System (FAERS) to support the efficient collection, review, and analysis of adverse drug reactions (ADRs) for pharmacovigilance.</p> Methods <p>Data acquisition, cleaning, and integration processes were conducted to prepare FAERS data for analysis. The platform was designed with key functionalities, including multi-condition query, drug and ADR query, primary ID query, and interactive visualizations. Usability was demonstrated through a case study investigating the association between sulfonylureas and serious skin ADRs. Additionally, the platform’s accuracy was validated by comparing its outputs with manually retrieved and visualized data using a separate test case involving aspirin and tremor.</p> Results <p>The platform provides an interface with advanced query and visualization features, enabling users to efficiently retrieve, analyse, and visualize ADR data. Usability was illustrated by dynamically exploring FAERS data to identify safety signals for sulfonylureas and serious skin ADRs. The validation process confirmed the platform’s reliability by showing consistent results with manually processed data, demonstrating its potential to streamline PV workflows and improve data interpretation.</p> Conclusion <p>The visualization platform represents a novel and practical tool for pharmacovigilance research. By offering intuitive data query and analysis capabilities, the platform supports drug safety monitoring and promotes the development of pharmacovigilance practices.</p>

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Establishment of a visualization platform for ADR query and analysis: an example of severe skin adverse reactions caused by sulfonylureas

  • Hui-Min Yu,
  • Ya-Min Huang,
  • Jian Xiao,
  • Lu Zhang,
  • Hang-Xing Huang,
  • Ling Huang,
  • Jing-Yang Li,
  • Xin-qiong Huang

摘要

Purpose

This study aimed to develop a visualization platform for querying and analysing data from the FDA Adverse Event Reporting System (FAERS) to support the efficient collection, review, and analysis of adverse drug reactions (ADRs) for pharmacovigilance.

Methods

Data acquisition, cleaning, and integration processes were conducted to prepare FAERS data for analysis. The platform was designed with key functionalities, including multi-condition query, drug and ADR query, primary ID query, and interactive visualizations. Usability was demonstrated through a case study investigating the association between sulfonylureas and serious skin ADRs. Additionally, the platform’s accuracy was validated by comparing its outputs with manually retrieved and visualized data using a separate test case involving aspirin and tremor.

Results

The platform provides an interface with advanced query and visualization features, enabling users to efficiently retrieve, analyse, and visualize ADR data. Usability was illustrated by dynamically exploring FAERS data to identify safety signals for sulfonylureas and serious skin ADRs. The validation process confirmed the platform’s reliability by showing consistent results with manually processed data, demonstrating its potential to streamline PV workflows and improve data interpretation.

Conclusion

The visualization platform represents a novel and practical tool for pharmacovigilance research. By offering intuitive data query and analysis capabilities, the platform supports drug safety monitoring and promotes the development of pharmacovigilance practices.