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. Measure what is measurable and make measurable what is not so. Galileo Galilei (1564-1642).

Implementing Health Apps for Digital Public Health – An Implementation Science Approach Adopting the Consolidated Framework for Implementation Research

“…Additionally, technical aspects for clinical validation also should be considered. Such aspects might be drawn from frameworks for biometric monitoring technologies (21,22) which highlight the need for appropriate vocabulary and standardized approaches to evaluate digitally measured biomarkers, including defining performance characteristics and acceptance criteria. Furthermore, the adaptation of the CFIR for health apps might also supplement existing guidelines when focusing on implementation of apps the comply with guidelines (e.g., Xcertia Guidelines) (23).…”

Free-living Turning Rather Than Gait Differentiates People with Chronic Mild Traumatic Brain Injury from Controls

“…The primary strength of this study was the use of a single IMU to objectively measure free-living gait and turning in chronic mTBI patients and controls, as the use of a single device and assessment within usual daily life means that subjects had low research burden. However, the outcome measures presented are primarily research-orientated, requiring a great deal of time-consuming post-processing and checking, which is based on prior experience of inertial data [57,58]. Therefore, there needs to be re nement and deployment of software that clinicians and patients can easily navigate, which would allow more widespread uptake and use by health professionals [58].…”

“…However, the outcome measures presented are primarily research-orientated, requiring a great deal of time-consuming post-processing and checking, which is based on prior experience of inertial data [57,58]. Therefore, there needs to be re nement and deployment of software that clinicians and patients can easily navigate, which would allow more widespread uptake and use by health professionals [58]. Participants were assessed for ~7 days using a single IMU attached to a waist belt.…”

Piecing Together the Puzzle of Adherence in Sleep Medicine

“…Piecing Together the Puzzle of Adherence in Sleep Medicine medicine, however, has led to substantial technological advancements in digital monitoring tools across other therapeutic areas. 8,9 Until recently, monitoring adherence to pharmaceutical treatments has been limited to assaying biomarkers, which is impractical in most settings, or surrogate measurements, such as refill rates, pill counts, and Bluetooth-enabled pill bottles, which record the times at which the device is used, but not whether the drug was actually taken. 10 It is now possible to measure objective adherence to pharmaceuticals with devices such as digital pills, which are capsules containing a digital radiofrequency emitter alongside the medication, 11 or smart inhalers, which allow for audio analysis of inhalation, breath-hold, and exhalation.…”