World food safety is often oversimplified to preventing cross-contamination in kitchens or maintaining intact cold chains. In reality, this field of science often goes unnoticed because its most serious outcomes are wrongly dismissed as nothing more than an upset stomach. In truth, the global food industry can significantly undermine sustainable global health.
This past World Food Safety Day (7 June), Biophys has been reflecting on how food safety is far more than a hygiene rating in the window of your local curry house; it is an entire case study in biological resilience.
An estimated 67% of global antibiotic use occurs in livestock. This enormous level of exposure creates a biological “pressure cooker” that rapidly accelerates the emergence of multidrug‑resistant bacteria in treated animals. These bacteria, in turn, drive antimicrobial resistance (AMR) in meat-borne pathogens, which can cause drug-resistant infections in the people who consume them.
Pathogens such as Salmonella, E. coli and methicillin‑resistant Staphylococcus aureus (MRSA) are now routinely detected in meat products, meaning consumers may already be exposed to dangerous microbes before food even reaches the kitchen. Although AMR rates vary by region, resistant infections have been documented worldwide; antibiotic-resistant Salmonella causes more severe illness, is more likely to lead to hospitalisation, and now accounts for around 13% of reported cases in the United States. Meanwhile, in Europe, MRSA contamination is detected in roughly 5% of raw meat samples, raising serious concerns about zoonotic transmission of resistant bacteria from animals to humans.
Reducing meat consumption is one obvious part of the solution. However, in an increasingly globalised world, trade and dietary shifts mean that as of 2018, around 1.8 billion people consume at least 100 g of meat every day. Addressing this threat demands innovative approaches—and this is where artificial intelligence can help us act at scale.
AI models can rapidly integrate and analyse diverse datasets, from antibiotic usage records and microbiological data to whole-genome sequencing and clinical records. By doing so, they can identify potentially drug‑modifying enzyme patterns and detect, or even predict, the likelihood of AMR contamination in meat much earlier in the supply chain.
AI‑driven surveillance has already highlighted the scale of AMR in meat production, and biotechnology is now offering promising solutions. One such contender is phage therapy. Bacteriophages are viruses that specifically infect and destroy bacterial cells, and their mode of action allows them to do so without increasing resistance pressure. They can be added to animal feed or directly to meat products to target AMR‑resistant strains. AI can further enhance this approach through precision veterinary phage therapy, designing highly specific phages that are directly effective against newly emerging resistant strains in their animal hosts.
This is a powerful example of how computational intelligence can optimise biology. AI can improve the speed and efficiency of established workflows while extracting more insight from existing datasets. In practice, this means we can learn much more, much earlier in the food production process, allowing us to intervene before problems escalate and reach consumers.
This World Food Safety Day, we are championing the integration of emerging biotechnologies with advanced computational tools. By doing so, we can move beyond reliance on antibiotics in livestock and address food security with intelligent, adaptable and user‑focused solutions.