U.S – The U.S. Food and Drug Administration (FDA) has commenced the third phase of the Artificial Intelligence (AI) Imported Seafood Pilot program, which leverages AI and machine learning (ML) to reinforce import screening and to ensure that foods entering the U.S are safe.
The FDA has in the recent past battled with food safety concerns for various imported seafood products along different points in the supply chain, hence the focus on imported seafood which makes up more than 90 percent of the U.S. seafood supply.
This pilot builds upon the two previous phases of the pilot under the New Era of Smarter Food Safety Blueprint, a program that seeks to reduce the number of foodborne illnesses by leveraging technology to create a safer, more digital, traceable food system.
FDA launched the first phase of the pilot, an analytical proof of concept, in 2019. Two years later they carried out the second phase at all 328 U.S. ports of entry from February 2021 through July 2021.
The second phase integrated ML into existing import data systems to inform decisions about sampling by entry reviewers while providing agency staff with more experience with the ML model.
“The third phase, begun on August 15, 2022, will help to determine the feasibility of deploying in-house AI/ML models using the intelligence that FDA extracts from the data we collect reviewing millions of import entries per year,” says the FDA
ML is a type of AI that can help identify connections and patterns that people, or the FDA’s screening system, cannot see. These patterns are applied to incoming supply chains to help predict the likelihood that an import shipment is potentially harmful and not compliant with FDA regulations.
The ability of ML to analyze data, already generated and used by the agency, makes it well suited for addressing complex public health challenges and helping the agency to ensure the safety of imported foods.
The third phase is designed to accelerate the detection of contaminated imported seafood products with hazards such as pathogens, decomposition, unapproved antibiotic residues, among others.
The ability of ML to analyze data, already generated and used by the agency, makes it well suited for addressing complex public health challenges and helping the agency to ensure the safety of imported foods.
From the pilot, the FDA will be able to put the knowledge acquired in the ML screening of other FDA-regulated products. It will also inform future risk-based surveillance in products that present the greatest risk to consumers.
The ultimate goal is to better protect consumers from unsafe foods by advancing the FDA’s ability to identify potential hazards, according to the agency.
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