NOVEL TOOLS FOR FOOD SAFETY MANAGEMENT BASED ON QMRA WITH A ROBUST MODELLING OF UNNOVEL TOOLS FOR FOOD SAFETY MANAGEMENT APPLYING QMRA WITH ROBUST MODELLING OF UNCERTAINTY AND VARIABILITY: FANTASTICAL

Food safety remains a main concern for consumers, society, health agencies and food industry. Despite the efforts made during the last years, the number of outbreaks and food borne diseases is still high. Recent outbreaks within the European Union (e.g. L. monocytogenes in frozen vegetables) show that efforts are needed to coordinate scientific advances into decision making in order to implement new measures to increase consumer protection.
Quantitative Microbial Risk Analysis (QMRA) can be applied to support food safety management. QMRA is based on a mathematical description of the microbial response during the farm-to-fork chain of the product. Its application requires an accurate characterization of uncertainty and variability, inherent to any biological process. Because of these, QMRA must follow a probabilistic approach, considering the variance of the response variables. Consequently, decisions must be made with an acceptable level of risk given the knowledge gaps. A deeper knowledge of both uncertainty and variability is a top priority in the EU, since it would allow a better application of QMRA, leading to a better safety standards for policy makers and industry.
FANTASTICAL aims to develop novel approaches and tools for QMRA that can be implemented by all the stakeholders, i.e. agencies related to consumer protection (EFSA, ECDC) and industry. It will link a database of microbial responses with robust statistical functions for variance analysis and stochastic simulation in a user friendly software. This project will reach out to the potential users and provide them with hands-on, open access tools to better understand microbial variability and uncertainty, resulting in more realistic QMRA. Thus, it will lead to an improvement in consumer protection and safer products. It will also complement Dr Garre’s curriculum and provide him with soft skills required to take the next step of his scientific career towards becoming an R3 – Experienced Researcher.