Verification, analytical validation, and clinical validation (V3): the foundation of determining fit-for-purpose for Biometric Monitoring Technologies (BioMeTs)
Abstract Digital medicine is an interdisciplinary field, drawing together stakeholders with expertize in engineering, manufacturing, clinical science, data science, biostatistics, regulatory science, ethics, patient advocacy, and healthcare policy, to name a few. Although this diversity is undoubted...
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doaj-1b5f94c494b5431a8b26ec28113f48ab2021-04-18T11:43:38ZengNature Publishing Groupnpj Digital Medicine2398-63522020-04-013111510.1038/s41746-020-0260-4Verification, analytical validation, and clinical validation (V3): the foundation of determining fit-for-purpose for Biometric Monitoring Technologies (BioMeTs)Jennifer C. Goldsack0Andrea Coravos1Jessie P. Bakker2Brinnae Bent3Ariel V. Dowling4Cheryl Fitzer-Attas5Alan Godfrey6Job G. Godino7Ninad Gujar8Elena Izmailova9Christine Manta10Barry Peterson11Benjamin Vandendriessche12William A. Wood13Ke Will Wang14Jessilyn Dunn15Digital Medicine Society (DiMe)Digital Medicine Society (DiMe)Digital Medicine Society (DiMe)Biomedical Engineering Department, Duke UniversityTakeda PharmaceuticalsClinMed LLCComputer and Information Sciences Department, Northumbria UniversityCenter for Wireless and Population Health Systems, University of CaliforniaSamsung NeurologicaDigital Medicine Society (DiMe)Digital Medicine Society (DiMe)Independent ConsultantBytefliesDepartment of Medicine, University of North Carolina at Chapel Hill; Lineberger Comprehensive Cancer CenterBiomedical Engineering Department, Duke UniversityBiomedical Engineering Department, Duke UniversityAbstract Digital medicine is an interdisciplinary field, drawing together stakeholders with expertize in engineering, manufacturing, clinical science, data science, biostatistics, regulatory science, ethics, patient advocacy, and healthcare policy, to name a few. Although this diversity is undoubtedly valuable, it can lead to confusion regarding terminology and best practices. There are many instances, as we detail in this paper, where a single term is used by different groups to mean different things, as well as cases where multiple terms are used to describe essentially the same concept. Our intent is to clarify core terminology and best practices for the evaluation of Biometric Monitoring Technologies (BioMeTs), without unnecessarily introducing new terms. We focus on the evaluation of BioMeTs as fit-for-purpose for use in clinical trials. However, our intent is for this framework to be instructional to all users of digital measurement tools, regardless of setting or intended use. We propose and describe a three-component framework intended to provide a foundational evaluation framework for BioMeTs. This framework includes (1) verification, (2) analytical validation, and (3) clinical validation. We aim for this common vocabulary to enable more effective communication and collaboration, generate a common and meaningful evidence base for BioMeTs, and improve the accessibility of the digital medicine field.https://doi.org/10.1038/s41746-020-0260-4 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jennifer C. Goldsack Andrea Coravos Jessie P. Bakker Brinnae Bent Ariel V. Dowling Cheryl Fitzer-Attas Alan Godfrey Job G. Godino Ninad Gujar Elena Izmailova Christine Manta Barry Peterson Benjamin Vandendriessche William A. Wood Ke Will Wang Jessilyn Dunn |
spellingShingle |
Jennifer C. Goldsack Andrea Coravos Jessie P. Bakker Brinnae Bent Ariel V. Dowling Cheryl Fitzer-Attas Alan Godfrey Job G. Godino Ninad Gujar Elena Izmailova Christine Manta Barry Peterson Benjamin Vandendriessche William A. Wood Ke Will Wang Jessilyn Dunn Verification, analytical validation, and clinical validation (V3): the foundation of determining fit-for-purpose for Biometric Monitoring Technologies (BioMeTs) npj Digital Medicine |
author_facet |
Jennifer C. Goldsack Andrea Coravos Jessie P. Bakker Brinnae Bent Ariel V. Dowling Cheryl Fitzer-Attas Alan Godfrey Job G. Godino Ninad Gujar Elena Izmailova Christine Manta Barry Peterson Benjamin Vandendriessche William A. Wood Ke Will Wang Jessilyn Dunn |
author_sort |
Jennifer C. Goldsack |
title |
Verification, analytical validation, and clinical validation (V3): the foundation of determining fit-for-purpose for Biometric Monitoring Technologies (BioMeTs) |
title_short |
Verification, analytical validation, and clinical validation (V3): the foundation of determining fit-for-purpose for Biometric Monitoring Technologies (BioMeTs) |
title_full |
Verification, analytical validation, and clinical validation (V3): the foundation of determining fit-for-purpose for Biometric Monitoring Technologies (BioMeTs) |
title_fullStr |
Verification, analytical validation, and clinical validation (V3): the foundation of determining fit-for-purpose for Biometric Monitoring Technologies (BioMeTs) |
title_full_unstemmed |
Verification, analytical validation, and clinical validation (V3): the foundation of determining fit-for-purpose for Biometric Monitoring Technologies (BioMeTs) |
title_sort |
verification, analytical validation, and clinical validation (v3): the foundation of determining fit-for-purpose for biometric monitoring technologies (biomets) |
publisher |
Nature Publishing Group |
series |
npj Digital Medicine |
issn |
2398-6352 |
publishDate |
2020-04-01 |
description |
Abstract Digital medicine is an interdisciplinary field, drawing together stakeholders with expertize in engineering, manufacturing, clinical science, data science, biostatistics, regulatory science, ethics, patient advocacy, and healthcare policy, to name a few. Although this diversity is undoubtedly valuable, it can lead to confusion regarding terminology and best practices. There are many instances, as we detail in this paper, where a single term is used by different groups to mean different things, as well as cases where multiple terms are used to describe essentially the same concept. Our intent is to clarify core terminology and best practices for the evaluation of Biometric Monitoring Technologies (BioMeTs), without unnecessarily introducing new terms. We focus on the evaluation of BioMeTs as fit-for-purpose for use in clinical trials. However, our intent is for this framework to be instructional to all users of digital measurement tools, regardless of setting or intended use. We propose and describe a three-component framework intended to provide a foundational evaluation framework for BioMeTs. This framework includes (1) verification, (2) analytical validation, and (3) clinical validation. We aim for this common vocabulary to enable more effective communication and collaboration, generate a common and meaningful evidence base for BioMeTs, and improve the accessibility of the digital medicine field. |
url |
https://doi.org/10.1038/s41746-020-0260-4 |
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