Sym’Previus enables you to respond to regulatory quality constraints by simplifying the use of predictive microbiology. As such, since 2003, Sym’Previus users enjoy a web interface and state-of-the-art mathematical models to help in their activity.
Tailored to all food matrices, the software can predict the evolution of microbial contamination considering specific inherent variability of the product, of the processes and of microorganisms as indicated in the CE 2073-2005 regulation. It also allows for the optimisation of the information available to the Food Business Operators, like challenge-tests and auto-control data.

Sym’Previus is available online. The results and parameters are saved in your user account which ensures the confidentiality of your data. To benefit from all its features and contents you will need to take out a subscription (130€/year).

Sym’Previus includes :

4 fitting modules Free Premium

  • Estimating the initial concentration, the lag time, the growth rate (or generation time) and the maximal concentration (Rosso et al., 1996).

  • Deducing the cardinal temperature values, of pH or aw (min, opt and max) from a sequence of growth rates obtained under different conditions.

  • Estimating the heat resistance characterized by the decimal reduction time D-value (or δ-value) from a challenge-test data set using a Weibull heat inactivation model (Mafart et al., 2002).

  • Deducing temperature, pH or aw sensitivity parameters from a fitted heat inactivation kinetic.

4 simulation modules

  • Determine if a process consists of high-risk steps and for which microorganism. It enables you to determine which step of the process will have an impact on microbial growth or inactivation and the impact of a recontamination.

  • Helps to optimise the formulation by determining the microorganism development risks and factors (pH, acid, aw) which have the most influence.
    Determine if a product’s characteristics could enable the growth of Listeria.

  • Growth simulation: Determine the growth rate of microorganisms, and when the regulatory threshold will be reached.
    Determine the impact of a formulation change on microbial growth.
    Allow better knowledge of the life-cycle of a product (microorganism development, impact of the different steps of the process etc.)

  • Estimate the impact of the heat treatment and optimise its effectiveness.
    Test different time/temperature couples on 6 pathogen strains and 2 spoilage strains or on customised strains.

A database composed of 26 species for growth and 36 for inactivation
Possibility of adding your own customised strains