Development and evolution of risk assessment for food allergens

• Published in: Food and chemical toxicology 2014-05, Vol.67, p.262-276
• Main Authors: Crevel, René W.R., Baumert, Joseph L., Baka, Athanasia, Houben, Geert F., Knulst, André C., Kruizinga, Astrid G., Luccioli, Stefano, Taylor, Stephen L., Madsen, Charlotte B.
• Format: Article
• Language: English
• Subjects: Allergens - analysis; Allergic diseases; Biological and medical sciences; Digestive allergic diseases; Food allergy; Food Contamination - analysis; Food toxicology; Immunopathology; Medical sciences; Probabilistic modelling; Probability; Public health; Reference dose; Risk Assessment; Thresholds; Toxicology; Uncertainty
• ISSN: 0278-6915; 1873-6351
• DOI: 10.1016/j.fct.2014.01.032

•Dose distribution modelling of individual MEDs provides a means of quantifying the risk of reaction at the population level.•Full quantitative risk assessments can be performed when these are integrated with exposure data.•These modelling outcomes generate quantitative predictions of impact which can be used to manage the risk.•Important data gaps remain around severity as related to dose and patterns of consumption by allergic people.•Application of these models provides valuable insights, leading to further refinements and generating testable hypotheses. The need to assess the risk from food allergens derives directly from the need to manage effectively this food safety hazard. Work spanning the last two decades dispelled the initial thinking that food allergens were so unique that the risk they posed was not amenable to established risk assessment approaches and methodologies. Food allergens possess some unique characteristics, which make a simple safety assessment approach based on the establishment of absolute population thresholds inadequate. Dose distribution modelling of MEDs permitted the quantification of the risk of reaction at the population level and has been readily integrated with consumption and contamination data through probabilistic risk assessment approaches to generate quantitative risk predictions. This paper discusses the strengths and limitations of this approach and identifies important data gaps, which affect the outcomes of these predictions. These include consumption patterns among allergic individuals, analytical techniques and their application, severity-dose relationships, and the impact of extraneous factors which alter an individual’s physiology, such as infection or exercise. Nevertheless, application of these models has provided valuable insights, leading to further refinements and generating testable hypotheses. Their application to estimate the risk posed by the concurrent consumption of two potentially contaminated foods illustrates their power.