FDA’s data science experts include a diverse group of statisticians, mathematicians, computer scientists, engineers, bioinformaticists, and others who conduct applied research and provide pivotal support for the agency’s human foods program by applying traditional and emerging methodologies involving statistics, bioinformatics, and artificial intelligence.

Their endeavors include all aspects of statistical and analytical support related to ensuring the microbial and chemical safety of foods, cosmetics, and dietary supplements. Some examples of this support include: providing experimental design and analyses for laboratory and regulatory studies; designing and analyzing sampling surveys; conducting adverse event report analyses and developing signal detection tools; and collaborating on the preparation of risk assessments, microbial growth models, and estimations of relative risk.

Their bioinformatics work involves the development of analytical tools for application to biological data critical to research, compliance, and foodborne illness outbreak response activities related to FDA regulated products. Such biological data analyses can require complex computer modeling in areas such as toxicology, genetics, whole genome sequencing, metagenomics, and more.

Our data scientists are also leveraging artificial intelligence and machine learning technologies to enhance food safety. One example is the use of machine learning to strengthen the screening of imported seafood. By utilizing machine learning, we can identify connections and patterns beyond those that people or FDA’s traditional screening systems would normally detect. With this information we can better determine the likelihood that a seafood shipment offered for import is potentially harmful or otherwise not compliant with FDA regulations. Another example is using artificial intelligence to analyze broad sources of data to improve our ability to predict and detect new chemical hazards. FDA can then use this information to estimate exposure levels and toxicity levels for the potential hazard. This in turn allows us to better prioritize the public health risks associated with the potential hazard and to develop appropriate mitigation strategies to keep consumers safe.