HHS · no agency ID · record R0816

Renamed: 356H Machine Learning (ML) Facility Supply Chain Role Classification Previously: 356H ML Facility Supply Chain Role Classification

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: 2023-05 (month precision)Source: May-23
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Health and Medical
Operational functions: No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

Manual classification of facility supply chain roles from FDA industry submissions (356h forms) is time-consuming and inefficient

Expected benefits

Improve the efficiency of evaluating 356H forms to assess a facility's supply chain role, thereby decreasing the time required for the processing of submissions and enabling faster oversight of drug manufacturing facilities.

System outputs

Extracts a facility's supply chain role from industry submissions and displays identified roles on a data-stewards screen for human verification and final determination.

Technology

AI classification: Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…
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): Deloitte
Vendors (standardized): Deloitte

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: Applicant submissions
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