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

点击翻译按钮获取中文摘要

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.