User Guide for VisDrugs

This webpage integrates adverse reaction data in ASCII format from the FAERS database spanning 2014Q3 to 2024Q3. It specifically filters reports submitted by four types of healthcare professionals: HP (Health Professional), MD (Physician), OT (Other Health Professional), and PH (Pharmacist). VisDrugs has filtered over 2,700,000 independent reports from the FAERS database, with each report involving only one drug, thus avoiding the interference of adverse reactions caused by multiple drugs. This dataset covers approximately 4,000 drug active ingredients and provides over 6,000,000 adverse reaction entries, helping users to analyze drug safety with precision. In the interactive interface, users simply need to enter the active ingredient of a drug to analyze and compare the potential adverse reactions it may cause.

It is important to note that the adverse reactions mentioned in this article refer to the Preferred Term (PT) provided by the FAERS database, a medical term used to describe events according to the Medical Dictionary for Regulatory Activities (MedDRA). When reporting data to FAERS, relevant personnel typically report adverse reactions caused by diseases, those related to the drug's indications, as well as those triggered by the drug itself. Therefore, if the focus of analysis is on drug-induced adverse reactions, special care must be taken to exclude the interference of adverse reactions related to the indications in order to ensure the accuracy of the analysis results. In practical analysis, if the top 15 adverse reactions in a drug’s pie chart are all related to its indications, the raw data of the pie chart can be downloaded to identify the most frequent adverse reactions that are unrelated to the indications. These can then be analyzed in the “Reaction Comparison Between Drugs” mode for specific adverse reactions.

Most Potential Reactions of Target Drugs Mode:

Analyzes the adverse reactions most likely caused by the target drug.

In this mode, the user needs to input the name of the drug's active ingredient in the designated field. As the user types a few letters, the server will automatically search the database and display matching active ingredient names. The user can then select the relevant active ingredient(s) from the suggestions (ensure you enter active ingredient names, not brand names; multiple selections are allowed). If a drug has multiple active ingredients or comes in various formulations, the user should decide which combinations or formulations to include in the analysis based on their research objectives.

Once the user has selected the target drug(s), they can assign a name to the drug group in the second input field and click the "Submit" button. The server will generate and display the analysis results below.

To learn how to interpret the forest plot, please skip directly to the end of the document.

Reaction Comparison Between Drugs Mode:

Compares the adverse reactions between two groups of drugs

This mode allows flexible comparison of adverse reactions between two groups of drugs. It also supports subgroup analysis of target drugs based on research needs, currently offering subgrouping by age or gender.

What information does the forest plot display?

Forest plots are commonly used to analyze and compare the adverse reactions of drugs. A detailed explanation of the results can be found in the diagram below. In simple terms, the larger the odds ratio (OR) value (further to the right of the red line), the more likely the drug is associated with the specific adverse reaction. Conversely, the smaller the OR value (further to the left of the red line), the less likely the drug is to cause the adverse reaction.

Please cite the following paper when publishing using this webpage:

1. Renjun Yang, Nuoya Yin, Ying Zhao, Dandan Li, Xuanling Zhang, Xingang Li, Yang Zhang, Francesco Faiola. Adverse Events During Pregnancy Associated With Entecavir and Adefovir: New Insights From a Real-World Analysis of Cases Reported to FDA Adverse Event Reporting System. Front Pharmacol. 2022 Jan. 3:12:772768. DOI: 10.3389/fphar.2021.772768.