Paul L. Briant, J. Bischoff, M. Dharia, Franck Le Navéaux, Xuemei Li, Sanjeev M. Kulkarni, Danny Levine, David Ramos, Payman Afshari
{"title":"使用真实世界的数据来提高模型可信度:在医疗设备开发中的应用","authors":"Paul L. Briant, J. Bischoff, M. Dharia, Franck Le Navéaux, Xuemei Li, Sanjeev M. Kulkarni, Danny Levine, David Ramos, Payman Afshari","doi":"10.1115/1.4053888","DOIUrl":null,"url":null,"abstract":"\n Evaluating the credibility of computational models used in medical device development is increasingly important as medical devices become more complex and modeling takes on a more critical role in the device development process. While bench-testing based comparisons are common for assessing model credibility and have many advantages, such as control over test specimens and the ability to quantify outputs, the credibility assessments performed with bench tests often do not evaluate the clinical relevance of key aspects of model form (such as boundary conditions, constitutive models/properties, and geometries) selected when simulating in vivo conditions.\n Real-world data (outcomes data generated through clinical use of a device) offer an opportunity to assess the applicability and clinical relevance of a computational model. Although real-world data are frequently less controlled and more qualitative than benchtop data, real-world data are often a direct assessment of a particular clinical complication and therefore of high clinical relevance. Further, real-world data have the potential to reveal failure modes not previously identified in pre-clinical failure modes analysis, thereby motivating testing advancements. To review the use of clinical data in medical device modeling, this paper presents a series of examples related to tibial tray fracture that incorporate varying levels of benchtop data and real world data when evaluating model credibility. The merits and drawbacks of the credibility assessment for each example are discussed in order to provide practical and actionable guidance on the use of real world data for establishing and demonstrating model credibility.","PeriodicalId":49305,"journal":{"name":"Journal of Medical Devices-Transactions of the Asme","volume":null,"pages":null},"PeriodicalIF":0.8000,"publicationDate":"2022-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Use of Real-World Data for Enhancing Model Credibility: Applications to Medical Device Development\",\"authors\":\"Paul L. Briant, J. Bischoff, M. Dharia, Franck Le Navéaux, Xuemei Li, Sanjeev M. Kulkarni, Danny Levine, David Ramos, Payman Afshari\",\"doi\":\"10.1115/1.4053888\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Evaluating the credibility of computational models used in medical device development is increasingly important as medical devices become more complex and modeling takes on a more critical role in the device development process. While bench-testing based comparisons are common for assessing model credibility and have many advantages, such as control over test specimens and the ability to quantify outputs, the credibility assessments performed with bench tests often do not evaluate the clinical relevance of key aspects of model form (such as boundary conditions, constitutive models/properties, and geometries) selected when simulating in vivo conditions.\\n Real-world data (outcomes data generated through clinical use of a device) offer an opportunity to assess the applicability and clinical relevance of a computational model. 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Use of Real-World Data for Enhancing Model Credibility: Applications to Medical Device Development
Evaluating the credibility of computational models used in medical device development is increasingly important as medical devices become more complex and modeling takes on a more critical role in the device development process. While bench-testing based comparisons are common for assessing model credibility and have many advantages, such as control over test specimens and the ability to quantify outputs, the credibility assessments performed with bench tests often do not evaluate the clinical relevance of key aspects of model form (such as boundary conditions, constitutive models/properties, and geometries) selected when simulating in vivo conditions.
Real-world data (outcomes data generated through clinical use of a device) offer an opportunity to assess the applicability and clinical relevance of a computational model. Although real-world data are frequently less controlled and more qualitative than benchtop data, real-world data are often a direct assessment of a particular clinical complication and therefore of high clinical relevance. Further, real-world data have the potential to reveal failure modes not previously identified in pre-clinical failure modes analysis, thereby motivating testing advancements. To review the use of clinical data in medical device modeling, this paper presents a series of examples related to tibial tray fracture that incorporate varying levels of benchtop data and real world data when evaluating model credibility. The merits and drawbacks of the credibility assessment for each example are discussed in order to provide practical and actionable guidance on the use of real world data for establishing and demonstrating model credibility.
期刊介绍:
The Journal of Medical Devices presents papers on medical devices that improve diagnostic, interventional and therapeutic treatments focusing on applied research and the development of new medical devices or instrumentation. It provides special coverage of novel devices that allow new surgical strategies, new methods of drug delivery, or possible reductions in the complexity, cost, or adverse results of health care. The Design Innovation category features papers focusing on novel devices, including papers with limited clinical or engineering results. The Medical Device News section provides coverage of advances, trends, and events.