Integrating artificial intelligence and advanced biocensors for rapid and sensitive detection of antimicrobial-resistant foodborne pathogens

The existence of foodborne pathogens which carry antimicrobial resistance is not merely scientific issue, but it is a health world crisis. These microorganisms can invisibly exist in food systems but when they do; they result in devastating outbreaks that are difficult to treat through common means, thus making them hard to control in order to perform clinical work as well as regulation of food safety. Culture-based assays, polymerase chain reactions (PCR) and enzyme-linked immunosorbent assays (ELISA) represent the conventional diagnostic methods that can be sensitive and specific but are hampered by long turnaround time, complicated procedures and require well equipped laboratories with trained staff. The latency of these methods can be disastrous to the health of the population. The development of sophisticated biocensors combined with artificial intelligence (AI) is a paradigm shift to integrate fast and sensitive biochemical detection with intelligent signal processing and pattern recognition. The purpose of this integration is to identify minute amounts of resistant pathogens in complex food matrixes faster and more precisely than ever before. In addition to decreasing the time to run an assay, AI-enables biocensing can facilitate real time interpretation of data, decrease false positives and false negatives and, eventually, facilitate the deployment of platforms in the field to perform on site monitoring. The integrated approach of state-of-the-art sensor design combined with machine learning and deep learning analytics has the potential to change the discipline to highly adaptive, robust systems that can be used to address the complex issue of antimicrobial resistance in foodborne pathogens. This paper identifies the motivations, state of the art, challenges and future directions of this interdisciplinary integration, and aims to inform research directions that would take food safety diagnostics to a higher level to provide safer food supply in the world.