RAKIP a new Risk Assessment Modelling and Knowledge Integration Platform

Transcription

1 RAKIP a new Risk Assessment Modelling and Knowledge Integration Platform Leticia Haberbeck and Maarten Nauta

2 Collaborative project between three partner institutes Developed in a long term project planning Phases I to III Started January 2017 (Phase I: Jan 2017 Jan 2018) Main focus (so far) on microbiology Predictive microbial modelling Microbiological risk assessment (QMRA)

3 Problem statement: Current situation in the food safety community Scientific knowledge Software tools and databases Belgium ICRA Spain France UK Dairy ProductSafety Predictor France USA UK and Japan GroPIN 3 Greece Tools function independently, cannot be linked

4 Objectives Main objective: To establish resources facilitating knowledge share and exchange. knowledge = models and data in food safety risk assessment (QMRA) Specific objectives: 1- To create and maintain a knowledge exchange format. 2- To create and maintain a web-based food safety knowledge repository. 3- To develop new open source software libraries and converter tools. 4- To engage with the global food safety risk assessment community.

5 Achievements Phase I (January 2017 January 2018)

6 1- To create and maintain knowledge exchange format Called: Food Safety Knowledge Markup Language (FSK-ML). Capable of describing risk assessment data and models in a harmonized way. Achievements: - White paper defining terms and concepts within QMRA. - Map the metadata and controlled vocabularies to describe knowledge. - Define mandatory metadata as foundation for the FSK-ML format. - Guidelines to FSK-ML development by the community. Future tasks: - Evaluation, adaption and improvement of FSK-ML (Phase II). - Broaden the knowledge base in the RAKIP repository (CRA, antimicrobial resistance, source attribution, burden of disease ) (Phase II and III)

7 2- To create and maintain a web-based open web-based food safety knowledge repository For organization, storage, retrieval, exchange of risk assessment models and data. Achievements: - Online RAKIP Web Portal: - Populate RAKIP Web Portal with models from QMRA domain (Phase I - ongoing). Future tasks: - Population of RAKIP with QMRA and chemical RA models (Phase II and III).

8 3- To develop new open source software libraries and converter tools To directly support the enhancement of existing software and databases facilitating the adoption of the proposed FSK-ML format. Achievements: - Development of FSK-Lab software tool that support FSK-ML information exchange. Future tasks: - Development of resources to convert knowledge contained in food safety software and data bases to the FSK-ML language (Phase II).

9 4- To engage with the global food safety risk assessment community To disseminate and to create broad support for the initiative. Achievements: - Internal survey in the three institutions - Workshop with experts/partners in Berlin - ICPMF-10 workshop (International Conference of Predictive Modelling in Food) - ICPMF-10 oral presentation - Paper submitted to the Food Safety issue of Current Opinion in Food Science journal - Paper invitation for ICPMF special issue on Microbial Risk Analysis journal - BfR 15 th anniversary workshop oral presentation and poster What we plan to do: - Continue disseminating RAKIP results (Phase II and III). - Create basis for establishment of a RAKIP initiative foundation with extended partnership (more than the three institutes) (Phase III). 9

10 RAKIP end users

11 RAKIP and EFSA Knowledge Junction The QMRA and predictive microbial models described in EFSA Knowledge Junction platform will be available in RAKIP Web Portal (Phase II). A convertor tool between EFSA Knowledge Junction and FSK-ML language will be developed (Phase II).

12 RAKIP Team ANSES Virginie Desvignes Laurent Guillier Moez Sanaa BfR Carolina Plaza-Rodriguez Miguel de Alba Aparicio Matthias Filter DTU Food Leticia Haberbeck Paw Dalgaard Maarten Nauta