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

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 2 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, 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.

Figure 1

Timeline comparing a number of major technology developments (bottom) underlying laboratory biomarker assays and present‐day biometric monitoring technologies (BioMeTs) and examples of major biomedical applications based on those technology developments (top). ECG, echocardiogram; IHC, immunohistochemistry; IVD, in vitro diagnostics; NGS, next‐generation sequencing; NIH, National Institutes of Health; PCR, polymerase chain reaction; PPG, postprandial glucose.

Figure 2

The V3 framework as applied to digital (left) and laboratory (right) biomarkers. Laboratory biomarkers go through an analytical and clinical validation step as defined in the Biomarkers, Endpoints, and other Tools framework. ⁹⁵ Digitally measured biomarkers are derived from sensor technology (BioMeT) that needs to undergo verification, before the physiological or behavioral measures of interest can be analytically and clinically validated. ⁷ Whereas laboratory biomarkers can go through the process based on bench testing, digitally measured biomarkers are highly reliant on human subject testing. Figure adapted from ref. 7 with permission.