TY - JOUR
T1 - Verification, Analytical Validation, and Clinical Validation (V3): The Foundation of Determining Fit-for-Purpose for Biometric Monitoring Technologies (BioMeTs)
AU - Goldsack, Jennifer
AU - Coravos, Andrea
AU - Bakker, Jessie
AU - Bent, Brinnae
AU - Dowling, Ariel
AU - Fitzer-Attas, Cheryl
AU - Godfrey, Alan
AU - Godino, Job
AU - Gujar, Ninad
AU - Ismailova, Elena
AU - Manta, Christine
AU - Peterson, Barry
AU - Vandendriessche, Benjamin
AU - Wood, William
AU - Wang, Ke
PY - 2020/12
Y1 - 2020/12
N2 - Digital medicine is an interdisciplinary field, drawing together stakeholders with expertise in engineering, manufacturing, clinical science, data science, biostatistics, regulatory science, ethics, patient advocacy, and healthcare policy, to name a few. While 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.
AB - Digital medicine is an interdisciplinary field, drawing together stakeholders with expertise in engineering, manufacturing, clinical science, data science, biostatistics, regulatory science, ethics, patient advocacy, and healthcare policy, to name a few. While 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.
KW - SAW
KW - CEA
KW - SAM
KW - Piezoelectricity
KW - Label free
KW - Biosensing
U2 - 10.1038/s41746-020-0260-4
DO - 10.1038/s41746-020-0260-4
M3 - Article
SN - 2398-6352
VL - 3
JO - npj Digital Medicine
JF - npj Digital Medicine
IS - 1
M1 - 55
ER -