NSF-FDA: Generating trustworthy computational evidence to support FDA’s regulatory evaluation of medical devices, via transparency and reproducibility

美国食品和药物管理局(FDA)已将提高医疗器械非临床评估的预测价值确定为研究重点。在许多与FDA批准的医疗器械相关的情况下，计算建模可以补充或取代实验室研究、动物试验或临床试验。它的潜力尚未完全实现，因为在开发或评估医疗设备时，不存在使用计算模型的标准化或行业接受的工作流程或评估指标。该项目的目标是将计算建模和模拟从科学研究工具提升到高质量的监管工具。增加计算证据的作用将加快医疗器械的创新和监管决策。该项目还将增加关于可重复计算的知识库，并提高审查员处理计算证据的舒适度。将这一知识传达给行业将提高设备提交的质量。从长远来看，监管级别计算建模的透明度和重复性标准可以导致文化的变化，在这个领域建立对计算证据的更多信任。这个为期一年的项目是一个概念验证工作流程和试点研究，旨在为医疗器械安全性和有效性的监管非临床评估生成可靠的计算证据。该项目的概念验证应用是电子药物输送系统(EDDS)原型，即基于电子烟设备的电子吸入器。这项在监管科学背景下的研究建立、适应和扩展了可再生性的框架，现在正在元研究中确立。在这个过程中，这项研究支持监管机构和行业了解EDDS原型的严格和可信的计算证据，借鉴计算流体力学模型和数字证据的最佳实践。所有研究人工制品和经验结果的出处将被严格捕获、记录和管理，例如，包括数据、代码、参数、计算环境和计算工作流程。这项初步研究对监管科学、计算机科学、网络物理系统和医疗器械方面的文献做出了贡献。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The Food and Drug Administration (FDA) has identified as a research priority the need to improve the predictive value of non-clinical evaluation of medical devices. Computational modeling can complement or replace laboratory studies, animal trials, or clinical trials in many situations relating to FDA approval of medical devices. Its potential has yet to be fully realized because no standardized or industry accepted workflow or appraisal metrics exist for using computational models in developing or assessing medical devices. The goal for this project is to elevate computational modeling and simulation from scientific research tools to high-quality regulatory tools. Increasing the role of computational evidence will accelerate innovation and regulatory decision-making of medical devices. The project will also increase the knowledge base about reproducible computations, and increase the level of comfort for reviewers handling computational evidence. Communicating this knowledge to industry will increase the quality of device submissions. Longer term, transparency and reproducibility standards in regulatory grade computational modeling can lead to a change in culture, building more trust in computational evidence in this sphere.This one-year project is a proof-of-concept workflow and pilot study for generating trustworthy computational evidence for regulatory non-clinical evaluation of medical device safety and efficacy. The proof-of-concept application for this project is an electronic drug delivery system (EDDS) prototype, an electronic inhaler based on e-cigarette devices. This study in the context of regulatory science builds on, adapts, and expands a framework of reproducibility, now becoming established in meta-research. In the process, this study supports regulators and industry in understanding rigorous and trustworthy computational evidence for the EDDS prototype, drawing upon computational fluid dynamics models and best practices for digital evidence. The provenance of all the research artifacts and empirical results will be rigorously captured, recorded, and curated including, for example, data, code, parameters, computational environment, and computational workflow. This pilot study contributes to the literature in regulatory science, computer science, cyber-physical systems, and medical devices.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.