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

项目摘要 本研究旨在改进识别和分析用户的方法 界面（UI）设计差异可能影响参考列出药物的可替代性 (RLD)正在寻求FDA批准的仿制药-器械组合产品（DDCP） 通过简化新药申请（ANDA）途径。这项研究将 通过以下方式促进监管审查以及通用DDCP的设计和开发 开发一种基于使用相关风险的分析方法，可以提高患者的可及性 他们需要的药物。拟议的目标包括： 目标1.建立一个关于主要利益攸关方观点和现有战略的知识体系， 评估用户界面设计。 目标2.开发一个视觉分类系统来分析组合产品UI设计 属性，并便于识别次要和其他设计差异，因为它们 可能导致伤害或损害医疗的潜在使用错误。 目标3。制定一种方法，对拟议的通用DDCP及其 RLD基于评估与引入使用潜力相关的UI设计差异 可能导致伤害或医疗护理受损的关键任务错误。 本研究将通过以下方式影响DDCP可接受性评估的人为因素方法： 提供可能导致潜在使用错误的UI设计差异的清晰度 伤害或危及医疗。使用可视化分类法对UI进行分类 DDCP类型的设计属性是一种新方法，将符合当前FDA指南， 国际标准，并支持FDA审查ANDA提交资料中的人为因素数据。 所提出的方法将使用相关风险分析（乌拉）与 通过FDA ANDA寻求上市前许可的DDCP的特定UI设计属性 通路最终目标是提出一种改善HF质量的人为因素方法 ANDA提交中的数据，促进FDA更有效地审查ANDA提交，以及 提高业界对拟议方法的接受程度。

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.