A risk-based approach to the monitoring of undesired substances in food products assumes the number of tests conducted for a given contaminant to be proportional to its potential health hazard and to the frequency of detections above the maximum level. One variant of the risk-oriented approach involves the use of dedicated algorithms whose core element is the ranking of individual compounds or groups of substances by their priority for inclusion in monitoring. This ranking is performed by assigning scores based on the criteria mentioned above, as well as additional criteria, followed by calculating and comparing overall scores. The details of national monitoring systems are generally not publicly disclosed, and therefore only a few such algorithms are described in open access.

The article presents a comparative analysis of the algorithms developed by the Food Safety Authority of Ireland (FSAI), the U.S. Department of Agriculture (USDA) and the Food and Drug Administration (FDA), Abbott Nutrition (USA), the Norwegian Scientific Committee for Food and Environment (VKM), the Federal Agency for the Safety of the Food Chain of Belgium (AFSCA), as well as the algorithm developed by the Russian State Center for Animal Feed and Drug Standardization and Quality.

The reviewed algorithms cover residues of veterinary medicinal products and contaminants (both individual substances and contaminant groups) in raw materials, finished products, and food ingredients. Some algorithms assign scores based on a general “health hazard” criterion, while others rely on specific values such as the acceptable daily intake (ADI) and other health-based guidance values (HBGVs). Certain schemes additionally incorporate criteria related to population exposure to contaminants through food.

The main advantage of these algorithms lies in providing a clear scientific rationale for monitoring plans, whereas their drawbacks include the subjectivity of scoring and, in some cases, methodological complexity requiring the consideration of large volumes of data. The degree to which such algorithms have been practically implemented remains unknown; however, this approach undoubtedly serves the primary goal of national monitoring – protecting public health.