Most fungi are able to produce several mycotoxins simultaneously and, consequently, to contaminate a wide variety of foodstuffs. Therefore, the risk of human co-exposure to multiple mycotoxins is real, raising a growing concern about their potential impact on human health. Besides, government and industry regulations are usually based on individual toxicities, and do not take into account the complex dynamics associated with interactions between co-occurring groups of mycotoxins. The present work assembles, for the first time, the challenges posed by the likelihood of human co-exposure to these toxins and the possibility of interactive effects occurring after absorption, towards knowledge generation to support a more accurate human risk assessment. Regarding hazard assessment, a physiologically-based framework is proposed in order to infer the health effects from exposure to multiple mycotoxins in food, including knowledge on the bioaccessibility, toxicokinetics and toxicodynamics of single and combined toxins. The prioritisation of the most relevant mixtures to be tested under experimental conditions that attempt to mimic human exposure and the use of adequate mathematical approaches to evaluate interactions, particularly concerning the combined genotoxicity, were identified as the main challenges for hazard assessment. Regarding exposure assessment, the need of harmonised food consumption data, availability of multianalyte methods for mycotoxin quantification, management of left-censored data, use of probabilistic models and multibiomarker approaches are highlighted, in order to develop a more precise and realistic exposure assessment. To conclude, further studies on hazard and exposure assessment of multiple mycotoxins, using harmonised methodologies, are crucial towards an improvement of data quality and a more reliable and robust risk characterisation, which is central for risk management and, consequently, to prevent mycotoxins-associated adverse effects. A deep understanding of the nature of interactions between multiple mycotoxins will contribute to draw real conclusions on the health impact of human exposure to mycotoxin mixtures.
Fast nonlinear risk assessment for autonomous vehicles using learned conditional probabilistic models of agent futures
