The focus of the research, development and innovation activities is to participate in national and international projects aiming at the safety of the food chain, and thus, due to the profile of the Institute, it mainly targets the following research areas related to food chain safety:

  • Data analytics research (data mining, text mining, network mining, artificial intelligence applications)
  • Forecasting (identifying emerging risks, epidemiological modelling)
  • Decision-making methodological research (cost-benefit, risk-benefit analyses, risk assessment)


Research topic ideas, search for international and national partners

Since its establishment, the Institute has been actively seeking opportunities for collaboration both within and outside the University. Working relationships have been established with several universities (e.g. University of Debrecen, Hungarian University of Agriculture and Life Sciences) and for-profit organisations, businesses. The exploration of research topic ideas and the search for national and international partners is ongoing.


Digitalization project proposals identified by DFI 

  • A system for early warning of food chain safety hazards and identification of emerging risks to support food business operators 
  • Systems for food chain safety health technology assessment, cost-benefit and risk-benefit analyses 
  • Food chain safety, quality management decision support systems for food chain managers
  • A secure, credible, blockchain-based traceability pilot system for one or two product lines 
  • Meat inspection digitalization 
  • Developing digital food chain monitoring subsystems for the authority, in cooperation with the authority 
  • Assessing food safety and nutritional impacts on consumers at the molecular level using data-driven, AI-assisted methods.

Research projects in progress

The National Laboratory project includes a number of research directions related to animal health and veterinary public health. The project is a collaboration between the University of Veterinary Medicine Budapest, the Veterinary Medical Research Institute and Széchenyi University. Separate sub-projects will address questions related to infection biology and antimicrobial resistance (AMR), while the third sub-project is entitled "Veterinary Public Health Process and Data Analysis". DFI is involved in this work through the following tasks:

  • Élelmiszerlánc folyamat– és driver-elemzési keret és tudásgráf létrehozása 
    Folyamatfelméréskockázatértékelési és driverelemzési keretrendszer kialakítása
  • Creating a food chain data collection network and repository - Development and populating of data infrastructure (data lake)
  • Pathways identified through food chain microbiome research for selected microbes - Identification of risk points and process drivers in the selected food chain process, risk assessment and identification of possible interventions


The project started in June 2022 and will be completed in 2026.

The project is a consortium of the University of Veterinary Medicine Budapest, PRIM-A-VET and E-Group, supported by the National Research, Development and Innovation Office (NKFIH), and will be implemented over the next 3 years. On the part of the University, the Department of Pharmacology and Toxicology and DFI are participating in the project.

The aim of the project is to build a veterinary public health data lake at the University of Veterinary Medicine Budapest, modelled on the human medical data lake at the University of Pécs. The data lake will allow the storage and preparation for analysis of structured and unstructured data from different sources. It is a novel data storage method that can reveal previously unexplored correlations through AI-enabled data mining and analysis.

If data from animal health, veterinary public health, food safety, human health and other sources can be analysed together, the resulting veterinary public health data repository could serve as a model for other countries and for the common European food chain safety profession. Possible applications of the dataset include drug repositioning and AMR control. The project was launched in October 2021.

A joint project with the Department of Pathology, the Department of Pharmacology and Toxicology and TETRABBIT Animal Breeding and Trade Ltd. The aim is to improve rabbit meat as a food product and the production process. The main tool is a big data analytical system fed by an automated data collection system, which can provide information from the barn to the table, covering the whole vertical of rabbit meat production. In addition, the system to be developed will be able to provide information or forecasts to all steps and actors in the supply chain. The project was launched in January 2021.

A NetPoulSafe egy Európai Uniós Horizon 2020 projekt, melynek célja, hogy támogassa az érdekelt feleket a biológiai biztonsági gyakorlatok hatékony megvalósítában. A 2020-ban indult projekt célkitűzése, hogy javítsa hét nagy baromfitenyésztő országban a biológiai biztonsági előírásoknak való megfelelést a baromfitenyésztésben a már bevezetett vagy bevezetés előtt álló eljárások adatainak összegyűjtésével, értékelésével és megosztásával.

Supporting measures to improve disease control are gathered from the consortium's network of experts, relevant disciplines and literature. The results will be analysed by the consortium, validated on pilot farms and made directly available to breeders, operators and advisors (including veterinarians). The national actors will be brought together by the Institute and the Department of Animal Hygiene, Herd Health and Mobile Clinic.

More information is available on the project page:

Completed research projects

DEMETER project

Researchers, governments, agencies, food producers and the civil society are increasingly concerned about ‘emerging food risks’. It is recognised that the successful identification of emerging risks is at the heart of protecting public health and the environment, and that this requires worldwide cooperation between all parties involved in the food supply chain.

The objectives and research proposed in the DEMETER project (Determination and Metrics of Emerging Risks) are designed to support current (and future) EFSA procedures for emerging issue and risks identification, providing a community resource that will allow EFSA and EU Member State authorities to share data, data mining knowledge and methods in a rapid and effective manner. A prototype technical Platform called the Emerging Risks Knowledge Exchange Platform (ERKEP) was developed by DEMETER.

The colleagues at the Institute contributed to the project with developing automated data analysis workflows, which identify emerging technological innovations and risks by network analysis of news sources and patent databases.

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