Introduction to the Monte Carlo project and the approach to the validation of probabilistic models of dietary exposure to selected food chemicals

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Abstract
The Monte Carlo project was established to allow an international collaborative effort to define conceptual models for food chemical and nutrient exposure, to define and validate the software code to govern these models, to provide new or reconstructed databases for validation studies, and to use the new software code to complete validation modelling. Models were considered valid when they provided exposure estimates (ea) that could be shown not to underestimate the true exposure (eb), but at the same time are more realistic than the currently used conservative estimates (ec). Thus, validation required eb⩽eac. In the case of pesticides, validation involved the collection of duplicate diets from 500 infants for pesticide analysis. In the case of intense sweeteners, a new consumption dataset was created among prescreened high consumers of intense sweeteners by recording, at brand level, all foods and beverages ingested over 12 days. In the case of nutrients and additives, existing databases were modified to minimize uncertainty over the model parameters. In most instances, it was possible to generate probabilistic models that fulfilled the validation criteria.