# Development of a Combination Product Taxonomy and Comparative Human Factors Testing Method for Drug-Device Combination Products Submitted in an ANDA

> **NIH FDA U01** · UNIVERSITY OF DETROIT MERCY · 2021 · $195,897

## Abstract

PROJECT SUMMARY
This research seeks to improve methods for the identification and analysis of user
interface (UI) design differences that may impact substitutability of reference listed drug
(RLD) products with generic drug-device combination products (DDCP) that are seeking FDA
clearance through the Abbreviated New Drug Application (ANDA) pathway. This research will
facilitate regulatory review as well as design and development of generic DDCPs by
developing a use-related-risk-based analysis method that can enhance patient access
to the medications they need. The proposed aims include:
Aim 1. Develop a body of knowledge of key stakeholder perspectives and existing strategies for
assessing user interface designs.
Aim 2. Develop a visual taxonomy to systematically analyze combination product UI design
attributes and facilitate the identification of minor and other design differences as they relate
to potential use errors that could cause harm or compromise medical treatment.
Aim 3. Develop a method for the comparative analysis of a proposed generic DDCP and its
RLD that is based on evaluating UI design differences related to the potential for introducing use
errors on critical tasks that could result in harm or compromised medical care.
This research will impact human factors methods for assessment of DDCP interchangeability by
providing clarity in UI design differences that could lead to potential use errors that could result
in harm or compromise medical treatment. The use of a visual taxonomy for classifying UI
design attributes of DDCP types is a novel approach that will match current FDA guidance and
international standards and support FDA review of human factors data in ANDA submissions.
The proposed method will link the use-related risk analysis (URRA) to differences in the
UI design attributes specific to DDCPs seeking pre-market clearance through an FDA ANDA
pathway. The end goal is a proposed human factors methodology to improve the quality of HF
data in ANDA submissions, facilitate more efficient FDA reviews of ANDA submissions, and
improve industry acceptance of the proposed methodology.

## Key facts

- **NIH application ID:** 10378381
- **Project number:** 1U01FD007360-01
- **Recipient organization:** UNIVERSITY OF DETROIT MERCY
- **Principal Investigator:** Megan O'Meara Conrad
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** FDA
- **Fiscal year:** 2021
- **Award amount:** $195,897
- **Award type:** 1
- **Project period:** 2021-08-01 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10378381

## Citation

> US National Institutes of Health, RePORTER application 10378381, Development of a Combination Product Taxonomy and Comparative Human Factors Testing Method for Drug-Device Combination Products Submitted in an ANDA (1U01FD007360-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10378381. Licensed CC0.

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