Latest developments in foodborne pathogens modeling

• Predictive modeling software, assisting food safety decision-making, has been developed.
• Stochastic models allow the description of strain and single-cell variability.
• Development of models at the molecular level is a future research challenge.

Predicting survival, growth or inactivation of pathogens in foods has been one of the most productive activities within Food Microbiology research the last two decades. Aiming at the wider applicability of predictive models, software development has become an active area in foodborne pathogens modeling, with numerous applications for data storage, analysis, visualization and retrieval. At the same time, the need for describing variability in microbial models used in risk assessment motivated the development of stochastic models, i.e. models with a probabilistic structure that take into account the variability of factors affecting microbial behavior. Current and future advances in systems biology and metabolic network modeling are expected to allow for the joined utilization in predictive models of both phenotypic and molecular data, for the purpose of unraveling the underlying mechanisms of microbial behavior.