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Verification, analytical validation, and clinical validation (V3): the foundation of determining fit-for-purpose for Biometric Monitoring Technologies (BioMeTs)

Jennifer C. GoldsackDigital Medicine Society (DiMe), Boston, MA USAAndrea Coravos3Harvard-MIT Center for Regulatory Science, Boston, MA USAJessie P. Bakker4Philips, Monroeville, PA USABrinnae Bent5Biomedical Engineering Department, Duke University, Durham, NC USAAriel V. DowlingTakeda Pharmaceuticals, Cambridge, MA USACheryl Fitzer‐AttasClinMed LLC, Dayton, NJ USAAlan Godfrey8Computer and Information Sciences Department, Northumbria University, Newcastle-upon-Tyne, UKJob Godino9Center for Wireless and Population Health Systems, University of California, San Diego, CA USANinad GujarCuris Advisors, Cambridge, MA USAElena S. IzmailovaDigital Medicine Society (DiMe), Boston, MA USAChristine MantaDigital Medicine Society (DiMe), Boston, MA USABarry W. PetersonIndependent Consultant, Charlotte, NC USABenjamin Vandendriessche15Department of Electrical, Computer and Systems Engineering, Case Western Reserve University, Cleveland, OH USAWilliam A. Wood16Department of Medicine, University of North Carolina at Chapel Hill; Lineberger Comprehensive Cancer Center, Chapel Hill, NC USAKe Will Wang5Biomedical Engineering Department, Duke University, Durham, NC USAJessilyn Dunn17Department of Biostatistics & Bioinformatics, Duke University, Durham, NC USA

2020en

ABI

Annotatsiya

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.

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DOI: 10.1038/s41746-020-0260-4

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