Unveiling insights from the Joint FAO/WHO Expert Committee on Food Additives (JECFA) portal

Area of Science:

• Food Safety Science
• Toxicology
• Computational Chemistry

Background:

• The Joint FAO/WHO Expert Committee on Food Additives (JECFA) database contains extensive toxicological information crucial for food safety assessments.
• Manual navigation and data extraction from the JECFA database are time-consuming and inefficient for researchers.
• There is a need for automated tools to enhance the accessibility and usability of JECFA's toxicological data.

Purpose of the Study:

• To develop and present a method for automating the retrieval of key identifiers and links to toxicological data from the JECFA database.
• To enhance the efficiency of accessing and organizing JECFA's extensive reports, monographs, and specifications.
• To facilitate more targeted and efficient toxicological data searches for researchers.

Main Methods:

• Utilized web scraping techniques to extract data from JECFA web pages.
• Developed R programming scripts to identify and retrieve chemical names, identifiers, and evaluation reports.
• Created a comprehensive dataset of 6552 records as of May 2024.
• Validated the dataset through systematic comparison with manually collected data.

Main Results:

• Successfully automated the retrieval of key toxicological data and links from the JECFA database.
• Generated a dataset containing 6552 records, significantly improving data accessibility.
• Validated dataset reliability through comparison with manual data collection.
• Provided openly available R code and the dataset for research reuse.

Conclusions:

• The developed automated method significantly enhances the efficiency of navigating and accessing toxicological data within the JECFA database.
• The open-source code and dataset empower researchers to conduct more targeted and efficient food additive safety analyses.
• This approach facilitates broader research and application of JECFA's critical toxicological findings.