Living my life for over 20 years in academia, then quickly pivoting to a government role overseeing the workings of the industry, has given me a unique perspective on the abundant amount of data that exists in the world of food safety. Considering academia, government and industry, there is one common element: They all have excellent scientists. When I was at FSIS, we had experts in just about every area of food safety, from the purist microbiologist to the epidemiologists. In academia, I was an expert in building academic teams across multiple universities, USDA's Agricultural Research Service and industry. And finally, while working at the agency I was exposed to innovative problem-solving from the industry scientists who would present great ideas that are indeed leading edge.

Despite the common thread of having excellent scientists, there are some key differences in the scientific approach in each of these areas that I’ll describe below:

Academia: Generally focused on discovery and basic research. There is some problem-solving and motivation to implement ideas, but generally the scientists are driven to devise an idea, get funding and publish for promotion and tenure. There is little “credit” given by university administrators when projects are done to help the industry.

Government (regulatory): Generally focused on collecting data to inform policy or rulemaking. They have access to samples across the entire industry to describe the status of the industry as a whole. They are accountable to Congress in spending of taxpayer dollars and thus must be very careful not to overstep. Data are sometimes published and/or available to the public in other formats (for example, through the Freedom of Information Act). Note: Government research agencies (for this group, USDA-ARS) would be similar to academia and aren’t included in this description.

Industry: The problem-solvers. They are motivated to solve problems, meet the everyday challenges faced in the industry and to make decisions to improve safety and meet regulatory requirements while keeping the company profitable. Usually, data are not available to the public and are not published as they inform proprietary decisions of the company.

All three of these entities and the data they generate are of critical importance. The place we have dropped the ball is at the scientific intersection. That is, we don’t share nearly enough information with one other. If we did, we could make significant strides in moving the bar forward for safety

For example, meat and poultry companies have been the most innovative in adopting quantitative pathogen standards for their operations. It was the companies that brought the ideas to the agency to open the door to strategically address Salmonella. Testing companies have followed the trend and have moved forward for Association of Official Agricultural Chemists (AOAC) or other approvals for their rapid quantification methods. These methods not only facilitate Salmonella control by the industry, but now that we have AOAC-approved methods, they are opening the doors for academia to do innovative research that has never been done by collecting and publishing data on quantification as opposed to simple detection. Quantification tells a very different story and detection alone is not giving enough information.

Now that methods are approved and adopted by industry and academia, it’s the government’s turn to evaluate these quantification methods, as regulators will be left behind each day that passes as everyone else adopts these approaches. I personally know this was a priority in the "Salmonella Roadmap" that FSIS rolled out last fall and I look forward to seeing action on this one by the agency.

This is just one example. If we had a way to anonymously collect and share all of the data generated by the industry we could use these data to rapidly inform policies such as performance standards without taking the enormous amount of time it takes to generate data by the agency. Academia could use the data as well, for publication and discovery to pinpoint the weakest links in the supply chain. Academia could share ideas with government and industry before the research is done to design discovery work that has the potential to be implemented one day.

I realize this is a paradigm shift, but I do think it is achievable through the right communication channels and opportunities to share ideas. Data Intersections should always be in our minds as we push the bar forward to do better and improve food safety. It is one of the key next steps to protecting public health!

Scientific intersections

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