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Hart S, Garcia V, Dudgeon SN, Hanna MG, Li X, Blenman KRM, Elfer K, Ly A, Salgado R, Saltz J, Gupta R, Hytopoulos E, Larsimont D, Lennerz J, Gallas BD. Initial interactions with the FDA on developing a validation dataset as a medical device development tool. J Pathol 2023; 261:378-384. [PMID: 37794720 PMCID: PMC10841854 DOI: 10.1002/path.6208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 07/14/2023] [Accepted: 08/24/2023] [Indexed: 10/06/2023]
Abstract
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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Affiliation(s)
- Steven Hart
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester MN, USA
| | - Victor Garcia
- Division of Imaging, Diagnostics, and Software Reliability, Office Science and Engineering Laboratories, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, USA
| | - Sarah N. Dudgeon
- Computational Biology and Bioinformatics Program, Yale University, New Haven, CT, USA
| | | | - Xiaoxian Li
- Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA, USA
| | - Kim RM Blenman
- Department of Internal Medicine, Section of Medical Oncology, School of Medicine, Yale University, New Haven, CT, USA
- Department of Computer Science, School of Engineering and Applied Science, Yale University, New Haven, CT, USA
| | - Katherine Elfer
- Division of Imaging, Diagnostics, and Software Reliability, Office Science and Engineering Laboratories, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, USA
| | - Amy Ly
- Department of Pathology, Massachusetts General Hospital, MA, USA
| | - Roberto Salgado
- Department of Pathology, GZA-ZNA Hospitals, Antwerp, Belgium
- Division of Research, Peter Mac Callum Cancer Centre, Melbourne, Australia
| | - Joel Saltz
- Department of Biomedical Informatics, Stony Brook School of Medicine, Stony Brook NY, USA
| | - Rajarsi Gupta
- Department of Biomedical Informatics, Stony Brook School of Medicine, Stony Brook NY, USA
| | | | - Denis Larsimont
- Department of Pathology, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - Jochen Lennerz
- Massachusetts General Hospital/Massachusetts General Hospital, Center for Integrated Diagnostics, Boston, MA, USA
| | - Brandon D. Gallas
- Division of Imaging, Diagnostics, and Software Reliability, Office Science and Engineering Laboratories, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, USA
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Teng Y, Sheng H, Liu Y. [Introduction and Reflection on Novel Medical Device Regulatory Science Tool MDDT]. Zhongguo Yi Liao Qi Xie Za Zhi 2023; 47:674-679. [PMID: 38086727 DOI: 10.3969/j.issn.1671-7104.2023.06.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
In recent years, emerging technology medical devices have developed rapidly. How to more scientifically and more efficiently regulate these novel medical devices so as to improve access to advanced medical technology while ensuring safety and effectiveness is a new challenge faced by regulatory authorities, and is also the core topic of regulatory science. New tools, new standards and new methods are important means to achieve regulatory science. "Medical Device Development Tool" proposed by the U.S. FDA is a novel medical device regulatory science tool, which can help medical device developers to predict and evaluate product performance more efficiently. It is also helpful for regulatory authorities to make regulatory decisions more efficiently. This study introduces the concept, qualification process, role of MDDT in medical device regulation and MDDT examples, and makes some discussion on the device evaluation from the perspective of reliability and validity. MDDT can facilitate the developing of novel medical device.
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Affiliation(s)
- Yingying Teng
- Center for Medical Device Evaluation, NMPA, Beijing, 100081
- School of Public Health, Peking University, Beijing, 100191
| | - Hengsong Sheng
- Center for Medical Device Evaluation, NMPA, Beijing, 100081
| | - Yinghui Liu
- Center for Medical Device Evaluation, NMPA, Beijing, 100081
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Machal ML. Framework for creating a qualified medical device development tool of autoinjectors. Front Med Technol 2023; 5:1281403. [PMID: 38130421 PMCID: PMC10733859 DOI: 10.3389/fmedt.2023.1281403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 10/31/2023] [Indexed: 12/23/2023] Open
Abstract
Objectives Autoinjectors are pivotal for precise self-administration of medications across a wide range of medical conditions. Nevertheless, the absence of a dedicated Medical Device Development Tool (MDDT) for autoinjectors represents a gap that may result in variations in the quality and regulatory compliance of autoinjectors as components of combination products. This research aim is to utilize the recently introduced Primary Functions outlined in ISO 11608-1:2022 with the title "Needle-based injection systems for medical use. Requirements and test methods. Part 1: Needle-based injection systems" to create a comprehensive MDDT framework tailored specifically for autoinjectors. Methods To support the creation of the framework, the analysis of the FDA MDDTs that were already approved, FDA's design controls regulations, FDA's guidance related to autoinjectors, and the Primary functions outlined in ISO 11608-1:2022 were utilized. Results The research identifies the Primary Functions in autoinjector to be Holding Force, Cap Removal Force, Activation Force, Extended Needle Length, Injection Time, Dose Accuracy and Needle Guard Lockout. Leveraging these Primary Functions and the FDA's MDDT approach, the research aims to bridge the gap by proposing a structured framework for the development of a specific MDDT tailored to autoinjectors. Conclusion This study presents a MDDT framework tailored to the development of autoinjectors for drug delivery. This framework provides a structured methodology to support predictability and effectiveness of the autoinjector development and support regulatory review process, thereby expediting FDA approval for autoinjectors as part of combination product.
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Affiliation(s)
- Marlon Luca Machal
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
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