Medical Design Briefs - October 2021 - 10

FDA's Modernization Plans
making better use of data. This motivated
the agency to create the Data
Modernization Action Plan (DMAP).
Specifically, this data strategy focuses on
the stewardship, security, quality control,
analysis, and use of data in developing
state-of-the-art products and solutions.
At a high level, the DMAP will enable
the agency to align technology and innovation
across multiple industries, en -
hance its data practices, and foster efficient
collaboration across its growing,
diverse workforce.8
Foundational requirements for the
FDA's modernized technology infrastructure
include virtual data storage,
problem-specific software, and solutions
for efficiently exchanging data. This
calls for the robust computing power
and extensive data storage capacity of a
cloud environment. Overall, the plan
will support broader efficiencies in communication
and data sharing.
The Necessity of the Data
Management Strategy
Understanding the potential of what
can be achieved through modernization
and big data is largely the impetus for the
FDA's DMAP strategy. Evolving technologies
are ushering in next-generation
solutions and more precise processes.
Data is highly integral to this progress.
For example, the ability to closely track
and trace medical and food products can
increase responsiveness to emergencies
and unplanned events such as pandemics,
natural disasters, and global supply
chain disruptions. Capturing more
real-world data also boosts the effectiveness
and diversity of clinical trials.
Delivering Measurable Value with
Modernization
Throughout 2020, the FDA labored to
expedite the drug approval process to
find treatments for COVID-19. During
this time, the agency has also been making
notable progress with its technology
modernization action plans. The ability to
use data from many new sources has led
to better understanding how healthcarerelated
solutions are performing. For
example, experts can now better pinpoint
the source of a foodborne illness, which is
an emerging public health threat. AI can
rapidly analyze data and automatically
identify connections and patterns in the
data that people or rules-based screening
systems can easily overlook. The agency
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Intro
Cov
has been leveraging AI to expand its predictive
analytics capabilities in a pilot program
for screening imported foods as part
of its food safety initiative.
The pilot program focuses on imported
seafood due to the high percentage
of the product that is imported versus
that produced domestically. This concentration
allows for targeted learning
and controlled experimentation within
the import screening process. This
approach has real potential to be a tool
that expedites the clearance of lower
risk seafood shipments and identifies
those that are higher risk. The proof of
concept [demonstrates] that AI/ML
could almost triple the likelihood that
we will identify a shipment containing
products of public health concern.9
" AI and ML have
the potential to
transform healthcare
by deriving new and
important insights
from the vast
amount of data
generated during
the delivery of
healthcare. "
Modernization Going Forward
Overall, the TMAP and DMAP have
enabled the FDA to take a more ad -
vanced, proactive approach to pursuing
its regulatory mission of enhancing public
health. The modernization strategies
are a work in progress, but the agency
has identified specific metrics to measure
the success of each strategy. These
include a recognizable reduction in regulatory
cycles, broader data sharing across
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the organization and the life sciences
industry, and the creation of a culture of
empowerment among its workforce. The
agency plans to build on the experience of
its modernization approaches, continue
planning for resource needs, and continue
with launching the individual programs
outlined in both the TMAP and DMAP initiatives.
References
1.
" Number of Original Investigational New
Drug (IND) applications received in the
quarter, " U.S. Food and Drug Administration,
Dec. 31, 2020, https://www.
accessdata.fda.gov/scripts/fdatrack/view/
track.cfm?program=cber&status=
publ ic&id=CBER-Al l - IND-and-IDEs -
received-and-actions&fy=All.
2. " Can Nanotechnology Deliver Big Drug
Benefits? " BioPharm, June 1, 2019, https://
www.biopharminternational.com/view/
can-nanotechnology-deliver-big-drug-benefits.
3. " FDA's Technology Modernization Action
Plan, " U.S. Food and Drug Administration,
Sep. 17, 2019, https://www.fda.gov/
about-fda/reports/fdas-technologymodernization-action-plan.
4.
" FDA's Data Modernization Action Plan:
Putting Data to Work for Public Health, "
Janet Woodcock and Amy Abernethy, U.S.
Food and Drug Administration, Mar. 3,
2021, https://www.fda.gov/news-events/
fda-voices/fdas-data-modernization-actionplan-putting-data-work-public-health.
5.
" Artificial Intelligence and Machine
Learning in Software as a Medical Device, "
Artificial Intelligence and Machine
Learning (AI/ML) Software as a Medical
Device Action Plan, U.S. Food and Drug
Administration (FDA), Jan. 12, 2021,
https://www.fda.gov/medical-devices/
software-medical-device-samd/artificialintelligence-and-machine-learningsoftware-medical-device.
6.
" Artificial Intelligence and Personalized
Medicine, " Nicholas J. Schork, National
Center for Biotechnology Information,
Oct. 22, 2020, https://www.ncbi.nlm.
nih.gov/pmc/articles/PMC7580505/.
7. " AI Device for Detecting Diabetic
Retinopathy Earns Swift FDA Approval, "
Keng Jin Lee, American Academy of
Ophthalmology, April 12, 2018, https://
www.aao.org/headline/first-ai-screendiabetic-retinopathy-approved-by-f.
8.
" Data Modernization Action Plan: A
Framework for FDA's Data Strategy, " U.S.
Food and Drug Administration, Nov. 10,
2020, https://fda.report/media/143627/
DMAP+final.pdf.
9. " Import Screening Pilot Unleashes the
Power of Data and Leverages Artificial
Intelligence, " Stephen M. Hahn, U.S.
Food and Drug Administration, Aug. 31,
2020, https://www.fda.gov/news-events/
fda-voices/import-screening-pilotunleashes-power-data-and-leveragesartificial-intelligence.
This
article was written by Sue Marchant,
Senior Director of Product for Data and AI,
MasterControl, Salt Lake City, UT. For more
information, visit http://info.hotims.com/
79418-341.
Medical Design Briefs, October 2021
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https://www.accessdata.fda.gov/scripts/fdatrack/view/track.cfm?program=cber&status=public&id=CBER-All-IND-and-IDEsreceived-and-actions&fy=All https://www.biopharminternational.com/view/can-nanotechnology-deliver-big-drug-benefits https://www.fda.gov/about-fda/reports/fdas-technology-modernization-action-plan https://www.fda.gov/news-events/fda-voices/fdas-data-modernization-action-plan-putting-data-work-public-health https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-software-medical-device https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7580505/ https://www.aao.org/headline/first-ai-screendiabetic-retinopathy-approved-by-f https://www.fda.report/media/143627/DMAP+final.pdf https://www.fda.gov/news-events/fda-voices/import-screening-pilot-unleashes-power-data-and-leverages-artificial-intelligence http://info.hotims.com/79418-341 http://www.medicaldesignbriefs.com http://info.hotims.com/79418-966

Medical Design Briefs - October 2021

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