基于 DNA 超分子水凝胶的保护性 NK 细胞储库用于增强三阴性乳腺癌治疗
Protective NK Cell Reservoir Based on DNA Supramolecular Hydrogel for Enhanced Triple-Negative Breast Cancer Therapy.
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:Initial interactions with the FDA on developing a validation dataset as a medical device development tool.
Initial interactions with the FDA on developing a validation dataset as a medical device development tool.
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在乳腺癌肿瘤中定量评估TIL(肿瘤浸润淋巴细胞)对病理学家而言颇具挑战。全视野成像可将玻片数字化,使计算模型能够辅助病理学家定量TIL。开发此类模型需要投入大量时间、专业知识、共识协调和资源。为减轻开发者负担,研究团队正在准备一套用于模型验证的数据集,并向美国食品药品监督管理局(FDA)器械与放射健康中心的医疗器械开发工具(MDDT)项目提交申请。如果FDA批准该数据集用于提交时指定的使用场景,模型开发者便可在该认证范围内将其用于监管申报,而无需额外文档。该数据集旨在降低TIL密度估算模型开发者的监管负担,并允许多个计算模型在同一数据集上进行直接比较。本文讨论MDDT数据集的准备和申报流程,包括团队与FDA初步沟通时收到的反馈,并提出经认证的MDDT验证数据集可作为开放、公平且一致评估计算模型性能的机制。相关经验有助于业界了解,在MDDT申报早期阶段,FDA认为哪些内容对于验证间质TIL密度估算模型及其他潜在计算模型是相关且适当的。本文版权归作者所有;《Journal of Pathology》由John Wiley & Sons Ltd代表英国和爱尔兰病理学会出版。部分作者为美国政府雇员,其作品在美国属于公共领域。
Quantifying tumor-infiltrating lymphocytes (TILs) in breast cancer tumors is a challenging task for pathologists. With the advent of whole slide imaging that digitizes glass slides, it is possible to apply computational models to quantify TILs for pathologists. Development of computational models requires significant time, expertise, consensus, and investment.
To reduce this burden, we are preparing a dataset for developers to validate their models and a proposal to the Medical Device Development Tool (MDDT) program in the Center for Devices and Radiological Health of the U. S. Food and Drug Administration (FDA). If the FDA qualifies the dataset for its submitted context of use, model developers can use it in a regulatory submission within the qualified context of use without additional documentation.
Our dataset aims at reducing the regulatory burden placed on developers of models that estimate the density of TILs and will allow head-to-head comparison of multiple computational models on the same data. In this paper, we discuss the MDDT preparation and submission process, including the feedback we received from our initial interactions with the FDA and propose how a qualified MDDT validation dataset could be a mechanism for open, fair, and consistent measures of computational model performance.
Our experiences will help the community understand what the FDA considers relevant and appropriate (from the perspective of the submitter), at the early stages of the MDDT submission process, for validating stromal TIL density estimation models and other potential computational models. 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland. This article has been contributed to by U. S. Government employees and their work is in the public domain in the USA.
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