Fit-for-Purpose Biometric Monitoring Technologies (BioMeT): Leveraging the Laboratory Biomarker Experience

Godfrey, Alan, Vandendriessche, Benjamin, Bakker, Jessie, Fitzer-Attas, Cheryl, Gujar, Ninad, Hobbs, Matthew, Liu, Qi, Northcott, Carrie, Parks, Virginia, Wood, William, Zipunnikov, Vadim, Wagner, John and Izmailova, Elena (2020) Fit-for-Purpose Biometric Monitoring Technologies (BioMeT): Leveraging the Laboratory Biomarker Experience. Clinical and Translational Science. ISSN 1752-8054 (In Press)

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Official URL: https://doi.org/10.1111/cts.12865

Abstract

Biometric Monitoring Technologies (BioMeTs) are becoming increasingly common to aid data collection in clinical trials and practice. The state of BioMeTs, and associated digitally measured biomarkers, is highly reminiscent of the field of laboratory biomarkers two decades ago. In this review, we have summarized and leveraged historical perspectives, and lessons learned from laboratory biomarkers as they apply to BioMeTs. Both categories share common features, including goals and roles in biomedical research, definitions, and many elements of the biomarker qualification framework. They can also be classified based on the underlying technology, each with distinct features and performance characteristics, which require bench and human experimentation testing phases. In contrast to laboratory biomarkers, digitally measured biomarkers require prospective data collection for purposes of analytical validation in human subjects, lack well-established and widely accepted performance characteristics, require human factor testing and, for many applications, access to raw (sample-level) data. Novel methods to handle large volumes of data, as well as security and data rights requirements add to the complexity of this emerging field. Our review highlights the need for a common framework with appropriate vocabulary and standardized approaches to evaluate digitally measured biomarkers, including defining performance characteristics and acceptance criteria. Additionally, the need for human factor testing drives early patient engagement during technology development. Finally, the use of BioMeTs requires a relatively high degree of technology literacy among both study participants and healthcare professionals. Transparency of data generation and the need for novel analytical and statistical tools creates opportunities for precompetitive collaborations.

Item Type: Article
Subjects: G400 Computer Science
G500 Information Systems
G900 Others in Mathematical and Computing Sciences
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Rachel Branson
Date Deposited: 28 Jul 2020 14:07
Last Modified: 13 Aug 2020 12:30
URI: http://nrl.northumbria.ac.uk/id/eprint/43908

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