The fundamental principles of ANSES’s vigilance | Handles

2024-03-27 08:36:00

Could you explain to us the main fundamental principles of these vigilances that you have just published in a specific document?

Each vigilance is monitored by a dedicated scientific team. A vigilance coordination committee ensures the implementation of general fundamental principles. These principles guarantee the same level of quality in the analysis of reports and consistency between methods for characterizing a signal and a health alert, monitoring reports and communicating our analyses. In application of these principles, we ensure the development of robust accountability methods, tested and scientifically validated. These methods make it possible to estimate the strength of the link between exposure, to a product for example, and an adverse effect that has been reported.

We also strive to ensure monitoring of alerts transmitted to the authorities and the actions that were taken in response. This is a results indicator for our vigilance missions. In order to raise awareness among the most concerned audiences, health professionals in particular, and promote the usefulness of reports, we have created a dedicated publication, the Vigil’Anses bulletin, which offers articles that are quick to read and understandable for those not specialists.

What are the prospects for the years to come?

Since January 2024, we have been responsible for two new areas of vigilance: cosmetic products and tattoo products, which were previously managed by the ANSM, the National Agency for the Safety of Medicines and Health Products. We are deploying the necessary resources to carry out these two missions with, very concretely, recruitment to increase our skills in these highly regulated areas and be able to analyze a greater number of declarations.

Another challenge of vigilance is to develop identifying weak signals. We are discussing with Public Health France and the ANSM on automated detection models that would make it possible to identify new phenomena, or unusual events, in large data sets including discussion forums.

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