Non-device software functions are not subject to
FDA device regulation and are not within the
scope of this paper. In addition, as detailed in
section 502(o) of the FD&C Act, software
functions intended (1) for administrative support
of a health care facility, (2) for maintaining or
encouraging a healthy lifestyle, (3) to serve as
electronic patient records, (4) for transferring,
storing, converting formats, or displaying data,
or (5) to provide certain, limited clinical decision
support are not medical devices and are not
subject to FDA regulation.
modifications guidance
8
, and the organization-based TPLC approach as envisioned in the Digital Health
Software Precertification (Pre-Cert) Program.
9
It also leverages practices from our current premarket
programs, including the 510(k), De Novo, and PMA pathways.
This discussion paper describes an innovative approach that may require additional statutory authority
to implement fully. The proposed framework is being issued for discussion purposes only and is not a
draft guidance. This document is not intended to communicate FDA's proposed (or final) regulatory
expectations but is instead meant to seek early input from groups and individuals outside the Agency
prior to development of a draft guidance.
This proposed TPLC approach allows FDA’s regulatory oversight to embrace the iterative improvement
power of AI/ML SaMD while assuring that patient safety is maintained. It also assures that ongoing
algorithm changes are implemented according to pre-specified performance objectives, follow defined
algorithm change protocols, utilize a validation process that is committed to improving the performance,
safety, and effectiveness of AI/ML software, and include real-world monitoring of performance. This
proposed TPLC regulatory framework aims to promote a mechanism for manufacturers to be continually
vigilant in maintaining the safety and effectiveness of their SaMD, that ultimately, supports both FDA
and manufacturers in providing increased benefits to patients and providers.
II.
Background:
A
I
/
M
L
-
Based
Software
as
a
Medical
Device
In this paper, we use John McCarthy’s definition of AI as the science and engineering of making
intelligent machines, especially intelligent computer programs.
10
AI can use different techniques, such as
ML, to produce intelligent behavior, including models based on statistical analysis of data, and expert
systems that primarily rely on if-then statements. In this paper, we refer to an ML system as a system
that has the capacity to learn based on training
on a specific task by tracking performance
measure(s). AI, and specifically ML, are
techniques used to design and train software
algorithms to learn from and act on data. These
AI/ML-based software, when intended to treat,
diagnose, cure, mitigate, or prevent disease or
other conditions, are medical devices under the
FD&C Act, and called “Software as a Medical
Device” (SaMD) by FDA and IMDRF. The
intended use of AI/ML-based SaMD, similar to
other SaMDs, may exist on a spectrum of
impact to patients as categorized by IMDRF
SaMD risk categorization framework.
11
8
Deciding When to Submit a 510(k) for a Software Change to an Existing Device:
https://www.fda.gov/downloads/medicaldevices/deviceregulationandguidance/guidancedocuments/ucm514737.pdf.
9
Developing a Software Precertification Program: A Working Model; v1.0 – January 2019:
https://www.fda.gov/downloads/MedicalDevices/DigitalHealth/DigitalHealthPreCertProgram/UCM629276.pdf.
10
http://jmc.stanford.edu/articles/whatisai/whatisai.pdf.
11
Software as a Medical Device (SaMD): Possible Framework for Risk Categorization and Corresponding Considerations:
http://www.imdrf.org/docs/imdrf/final/technical/imdrf-tech-140918-samd-framework-risk-categorization-141013.pdf.
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