Fast-track procedures play an important role in the context of conditional registration of medical devices, such as listing processes for digital health applications. They offer the potential for earlier patient access to innovative products and involve two registration steps. The applicants can apply first for conditional registration. A successful conditional registration provides a limited funding or approval period and time to prepare the application for permanent registration (the second registration step). For conditional registration, products have to fulfill only a part of the requirements necessary for permanent registration. There is interest in valid and efficient study designs for fast-track procedures. This will be addressed in this paper. A motivating example is the German fast-track registration process of digital health applications (DiGA) for reimbursement by statutory health insurances. The main focus of the paper is the systematic statistical investigation of the utility of adaptive designs in the context of fast-track registration processes like the DiGA fast-track. We demonstrate that, in most cases, such designs are much more efficient than the current standard of two separate studies. A careful statistical discussion of the registration requirements and their consequences is also included. The results are based on numerical calculations supported by mathematical arguments.

翻译：快速审批程序在医疗器械（如数字健康应用的上架流程）的有条件注册中发挥着重要作用。这些程序为患者更早获得创新产品提供了可能，并包含两个注册步骤。申请人可首先申请有条件注册。成功的有条件注册将提供有限的资助或批准期限，并为准备永久注册（第二注册步骤）申请留出时间。对于有条件注册，产品仅需满足永久注册所需的部分要求。当前业界对快速审批程序中有效且高效的研究设计存在迫切需求，本文正致力于解决该问题。一个具有启发性的案例是德国法定健康保险报销体系中数字健康应用（DiGA）的快速审批流程。本文的核心重点是对自适应设计在DiGA快速审批等快速注册流程中效用的系统性统计研究。我们证明，在大多数情况下，此类设计比当前两个独立研究的标准方案更为高效。文中还包含对注册要求及其影响的细致统计讨论，所有结论均基于数学论证支持的数值计算。