HHS · no agency ID · record R0819

Renamed: FAR-based Facility Signal Detection Tool Previously: Post-market Surveillance Reports Signal Detection and Cluster Analysis.

Department of Health and Human Services · HHS/FDA/CDER

Overview

Development stage: DeployedSource: c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not reported
Start date: 2024-06 (month precision)Source: Jun-24
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Health and Medical
Operational functions: Risk scoring and triage Derived by keyword rules; see methodology

Problem the AI is intended to solve

Need for proactive detection of quality signals in post-market surveillance reports using statistical process control and topic modeling to identify potential drug quality hazards and mitigate the associated risks.

Expected benefits

Identifies proactive quality signals and their associated problem clusters in an objective manner for triage and human review, helping prioritize resources on the higher risk issues and more complex problems.

System outputs

Identifies problem clusters for the flagged signals in an objective manner for triage/review.

Technology

AI classification: Natural language processingSource: Natural Language Processing: AI that processes, interprets, and shares information in human language.
System name(s): CDEROne Analytics: FISMA-high environment
Custom-developed code: Yes
Public source code: Not reported

Sourcing

How it was built: Contract and in-houseSource: c) Developed with both contracting and in-house resources
Vendor (as reported): In-house (CDER staff)
Vendors (standardized): None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII: No
Privacy Impact Assessment: Not reported
Authorization to Operate: Yes
Demographic features: k) None of the above
Training and evaluation data: Internal Field Alert Reports data from LSMV (FAERS tool)
Federal Data Catalog: Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported