Redefining and Validating Digital Biomarkers as Fluid, Dynamic Multi-Dimensional Digital Signal Patterns

Abstract

“Digital biomarker” is a term broadly and indiscriminately applied and often limited in its conceptualization to mimic well-established biomarkers as defined and approved by regulatory agencies such as the United States Food and Drug Administration (FDA). There is a practical urgency to revisit the definition of a digital biomarker and expand it beyond current methods of identification and validation. Restricting the promise of digital technologies within the realm of currently defined biomarkers creates a missed opportunity. A whole new field of prognostic and early diagnostic digital biomarkers driven by data science and artificial intelligence can break the current cycle of high healthcare costs and low health quality that is being driven by today's chronic disease detection and treatment approaches. This new class of digital biomarkers will be dynamic and require developing new FDA approval pathways and next-generation gold standards.

Multidimensional digital biomarker phenotypes for mild cognitive impairment: considerations for early identification, diagnosis and monitoring

“…This broad definition of digital biomarkers that is not limited to only correlated digital versions of traditional biomarkers has been criticized for diverging too far from a measurement taken directly in the body ( 14 ). Others, however, have advocated for collaboration with regulatory bodies to define different types (e.g., actively/passively acquired, point-in-time/continuous) or classes (e.g., direct/indirect, existing/novel) of digital biomarkers that could enable corresponding validation pathways ( 15 ). We prefer the broader definition of digital biomarkers.…”

Short-circuiting biology: Digital phenotypes, digital biomarkers, and shifting gazes in psychiatry

“…Note that some digital phenotypers stretch the biomarker term even further-that is, any kind of digitized data, not only physiological or behavioral data, can become a biomarker (Au et al, 2021). Accordingly, several researchers have used Internet search activity (Birnbaum et al, 2020), social media posts (Adler et al, 2022), geo-location data (Fraccaro et al, 2019), and computer or mobile-device gaming (Johannes Dechant et al, 2021) to derive digital biomarkers of mental health.…”

“…In contrast to the tenuous use of the extended phenotype concept, the use of the term “digital biomarkers” presents a more difficult case to criticize. First, because the use of the parent term “biomarker” has not been very consistent in the literature (Califf, 2018), one might also expect inconsistency in the use of the term “digital biomarker.” Second, discussions of what is meant by digital biomarkers are still ongoing, with some authors advocating more stringent use of the term (Au et al, 2021; Babrak et al, 2019; Montag et al, 2021a). Despite these caveats, what I seek to show is that current definitions and uses of “digital biomarker” involve a significant shift in what “bio” in biomarker is taken to denote—specifically, that “bio” now denotes “marker of biology,” including any digital markers of biology, rather than, as before, “marker derived from biology,” such as a biomolecule.…”

Machine Learning in Clinical Trials: A Primer with Applications to Neurology

“…Given the power of ML systems to detect anomalies in continuous signals [ 111 ], software programs that learn a patient’s unique physiologic patterns from wearable or implantable sensors may lead the way for personalized warning systems during experimental drug trials. Additionally, ML models can learn entirely new patterns from standardly collected data, giving rise to a new generation of digital biomarkers [ 112 , 113 ], to monitor treatment responses. Automated systems may learn to detect these biomarkers from a singular data source (e.g., electrocardiogram) or from combinations of multiple modalities (e.g., pulse oximetry, skin conductance, and blood glucose) to maximize the amount of information used for decision-making.…”