HHS · no agency ID · record R0832

Resource Capacity Planning

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: 2020-08 (month precision)Source: Aug-20
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Other
Operational functions: Forecasting and prediction Derived by keyword rules; see methodology

Problem the AI is intended to solve

FDA needs to accurately predict the volume and complexity of incoming drug application submissions to ensure appropriate staffing and resources are available for timely reviews under the user fee program

Expected benefits

Forecasting human drug review program submissions and corresponding FDA workload to support better resource planning and ensure timely review of drug applications that benefit public health.

System outputs

Forecasts workload submissions across major user fee programs to help support fee setting for the human drug review programs

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): 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: FDA systems including DARRTS and Panorama
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