Supermarket Perimeter - September 2020 - 60

Food safety: Bold steps

FOUR-FOLD FOCUS
The blueprint focuses on
four main objectives, or core
elements:
Core Element 1
Tech-enabled Traceability
seeks to advance traceability
to help protect consumers
from contaminated products
by doing rapid tracebacks,
identifying specific
sources and helping to
remove products from the
marketplace as quickly as
possible when necessary.
Ultimately, the goal is
to support end-to-end
traceability throughout the
food safety system. The
FDA will explore ways to
encourage firms to voluntarily
adopt tracing technologies
and ways to harmonize
tracing activities, which will
support interoperability
across a variety of technology
solutions, working toward

outcomes that are achievable
for all sectors.
Core Element 2
Smarter Tools and Approaches
for Prevention and Outbreak
Response seeks to explore the
preventive value of modern
food safety approaches that
generate new data streams
as well as tools for rapidly
analyzing big data. The FDA
is looking to enhance and
strengthen root cause analyses
and predictive analytics.
Findings of root cause analyses
can be an important step in
helping to modify practices to
avoid identified risks and can
provide more robust data for
predictive analytics.
It is also important for the
FDA to work with others in
new and creative ways. These
include the domestic mutual
reliance initiative, in which
the FDA seeks to build on

Smarter tools and approaches for
prevention and outbreak response
One of the most important resources the industry has today is the
ability to unleash the power of data, according to the blueprint. FDA
officials say the agency intends to do everything it can to attain better
quality data, conduct a more meaningful analysis of it, and to transform
streams of data into more meaningful, strategic, and preventionoriented actions.
"The plans embraced by the blueprint include strengthening our
procedures and protocols for conducting the root cause analyses
that can identify how a food became contaminated and inform our
understanding of how to help prevent that from happening again."
The need for greater traceability and predictive analytics can be
seen in the FDA's most recent efforts to improve the safety of romaine
lettuce and other leafy greens, which have too often been implicated in
outbreaks of Shiga-toxin producing E. coli (STEC) infections. The repeat
60 - SEPTEMBER 2020

existing efforts to partner with
states that have comparable
regulatory and public health
systems, leveraging each
other's data and analytics
to ensure optimal use of
resources and maximize its
food safety reach.
Core Element 3
New Business Models and
Retail Food Modernization
is intended to address how
to protect foods from
contamination as new business
models emerge and change to
meet the needs of the modern
consumer. The evolution of
how food gets from farm
to table continues with the
emergence of e-commerce
and new delivery models.
The evolution of how food
gets produced continues
with the emergence of
new business models that
advance innovations in novel

ingredients, new foods, and
new food production systems.
These new models include
online shopping for meals and
groceries, a practice that has
surged during the COVID-19
pandemic. Looking at more
traditional business models,
the FDA is exploring ways to
further modernize and help
ensure the safety of foods sold
at retail and foodservice.
Core Element 4
Food Safety Culture seeks to
foster, support and strengthen
food safety cultures on
farms, in food facilities,
and in homes. Dramatic
improvements in reducing
the burden of foodborne
disease depends on everyone
doing more to influence the
beliefs, attitudes, and, most
importantly, the behaviors
of people and the actions of
organizations.

nature of these outbreaks illustrates the importance of achieving endto-end traceability and of maximizing the effectiveness of root cause
analyses.
Another example of the kinds of new tools the agency is developing
for prevention can be seen in a pilot program the FDA is conducting
that will leverage artificial intelligence (AI) and machine learning to
strengthen the agency's review of imported foods at ports of entry to
help ensure that they meet US food safety standards.
"A proof of concept application of AI and machine learning models
to historical shipment data indicates that we can expect very promising
results from this pilot," according to FDA officials. "Imagine having a
tool that expedites the clearance of legitimate, compliant shipments
and improves by 300% our ability to know which shipping container
to examine because that container is more likely to have violative
products. It would save an immense amount of time, and potentially
lives."

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