The project objective is to leverage AI-assisted dynamic risk management concepts from Stochastic Finance to initiate disruptive transformation of the currently used classical (and often static) microbial risk analysis framework to meet the challenges of future food systems as part of a circular economy. Using the B. cereus group as a model, the project will develop dynamic data-driven risk assessment and management concepts and an overarching risk analysis scheme enabling food business operators, policy makers and risk managers to jointly promote the SDGs by minimizing food waste while protecting human health, biodiversity, and ecosystems.
- Transferring risk management concepts from Stochastic Finance to the microbial risk analysis context and harnessing existing data, models and concepts for microbial risk assessment and management
- Generating new data on B. cereus group hazard characterization and hazard exposure that can feed into AIbased risk assessment and management concepts
- Development of AI-assisted risk assessment and management concepts by building upon established tools from game theory and decision making and implementation in a food production facility
- Proposing an overarching microbial risk assessment and management scheme for multi-criteria decision support that integrates the novel AI-assisted concepts in a modular design
- Engaging stakeholders and assuring sustainable effects of the project by involvement of a sounding board of stakeholders, establishment of an interoperable database, and creation of training materials
Switzerland has been a driving force in shaping the UN’s Sustainable Development Goals (SDGs) and has committed to the ambitious 2030 Agenda to end hunger and assure health while protecting ecosystems. A key cornerstone in reaching these goals is the Farm to Fork Strategy of the European Green Deal that aims to promote healthy foods and preserve biodiversity. By 2030 food waste per capita and chemical pesticides shall be reduced by 50%, while at the same time organic farming shall increase to 25% of total farmland. These efforts started a disruptive transformation process towards fair, healthy, and environmentally friendly food systems that needs to be urgently complemented by innovative microbial risk assessment and management approaches, which are not only balancing food security and food safety but also consider health/environmental costs and minimize food waste. Current taxonomy-driven microbial food safety concepts have limited capability to cope with natural complexity and uncertainties. Furthermore, the tremendous progress made in whole genome sequencing over the last decade resulted in a disruptive paradigm shift in bacterial identification, questioning classical taxonomical concepts. A striking example for the limits of traditional risk assessment is the Bacillus cereus group. Toxicity within this group is highly variable and ranges from strains used as biopesticides and plant growth promoters to strains causing human fatalities. As species differentiation within the B. cereus group is difficult, usually species are not distinguished but subsumed under B. cereus s. l. and the risk related to a specific strain is not considered in routine diagnostics and outbreak investigations. However, to meet the SGDs and make food systems sustainable and resilient, a new path towards innovative food safety concepts must move from taxonomy to risk, considering strain specific risks, and must integrate costs to human health and the environment. The MicRisk2030 project transfers knowledge from the most developed fields of risk management within finance and economics to a microbial context, using the B. cereus group as a model, to bridge the growing gap between currently used traditional food safety concepts and the demands of modern food systems. In this project, we leverage artificial intelligence (AI)-assisted dynamic risk assessment concepts from Stochastic Finance to create new opportunities for the implementation of integrated risk assessment and management in biological systems embedded in an economic framework. Using the B. cereus group as a model, we will develop a novel risk assessment and management framework supplied with data from comprehensive field, wet lab and in silico experiments allowing to integrate risks to humans, animals, and the environment. The novel concept will be implemented and validated in a food production setting. This radically new approach has the potential to transform current paradigms in microbial risk assessment and management practices beyond the B. cereus group, promote circular food systems and inform policy makers, thus contributing to the 2030 Agenda. The results of MicRISK2030 could transform current paradigms in microbial risk assessment and pave the way for holistic and dynamic food safety concepts as integral parts of circular food systems.
Project start: 01.08.2022
Project duration: 4 years
Project duration: 4 years