Current Global Trends in Food Safety and Risk Prediction

The study substantiates the shift from traditional reactive control methods to a proactive model of intelligent risk management. Particular emphasis is placed on the "One Health" concept, which integrates human, animal, and ecosystem health within a unified monitoring system; special attention is also given to the destabilizing impact of climate change on food quality and safety—specifically through the spread of mycotoxins and alterations to the planet's microbial landscape. The study provides a detailed analysis of the potential of next-generation sequencing (NGS) for the metagenomic profiling of facilities, the role of nanotechnology in developing precision sensors and active packaging, and the application of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas systems for rapid pathogen diagnostics. Digital architectures for ensuring food safety are examined, with artificial intelligence (AI) and big data analytics presented as key tools for predictive modeling. The data presented address emerging threats such as micro- and nanoplastic contamination, antimicrobial resistance (AMR), and the safety of alternative protein sources. The study demonstrates that systemic contaminants necessitate new approaches to toxicological assessment due to their cumulative effects. It highlights that, by 2026, corporate legal liability will be inextricably linked to digital transparency and the ethics of AI algorithm usage. The study concludes that food safety in 2026 will increasingly depend on the integration of advanced technologies, environmental responsibility, and global digital cooperation.