Detecting

Digital biomarkers in non-communicable diseases

Autoren

Louis Agha-Mir-Salima, Elias Grünewalda, Felix Balzera and Katarina Braune

Journal

BIOMARKERS

Abstract

Digital biomarkers—objective, quantifiable physiological and behavioral measures collected through digital tools—enable continuous health assessment and hold promise for precision medicine. With non-communicable diseases (NCDs) being the leading cause of morbidity and mortality worldwide, digital biomarkers can provide early detection, continuous monitoring, and individualized care. This review examines advances in digital biomarkers across NCD domains, including endocrinology, cardiology, respiratory medicine, neurology, and mental health, with a focus on wearable technologies that continuously capture real-world behavior and physiology. Continuous glucose monitoring in diabetes exemplifies successful clinical translation, while digital biomarkers in cardiology, respiratory medicine, and neurology are at varying stages of validation and adoption. Most digital biomarkers across internal medicine, neurology, and mental health remain in early validation stages. Critical barriers to implementation include limited validation in diverse populations, lack of interoperability, insufficient integration with electronic health records, challenges in multimodal data synthesis, and underdeveloped regulatory pathways. Equity concerns persist as infrastructure, affordability, and capacity-building needs vary globally.Bridging the gap between consumer self-tracking and clinically validated, guideline-compatible digital biomarkers requires rigorous multicenter validation, standardized interfaces, open data models, secure and ethical data infrastructures, and equitable design. Coordinated efforts addressing these challenges are essential to enable digital biomarkers to improve prevention, diagnosis, and management of NCDs.

Zur Publikation

Unterstützendes Material

Autoren aus dem TRR 418

Projekte aus dem TRR 418

C01

Detecting

Targeting

Individualisierte datengesteuerte Lichtintervention bei Patienten auf der Intensivstation

Bei kritisch kranken Patienten sind circadiane Rhythmen häufig gestört, was den Krankheitsverlauf verschlechtert. Nicht-invasive Methoden zur Erfassung und Normalisierung der inneren Uhr auf der Intensivstation sind bisher nicht etabliert. Dieses Projekt kombiniert hochauflösende Patientendaten mit dynamischer Lichttherapie, um circadiane Rhythmen wiederherzustellen.

Individualisierte datengesteuerte Lichtintervention bei Patienten auf der Intensivstation

Bei kritisch kranken Patienten sind circadiane Rhythmen häufig gestört, was den Krankheitsverlauf verschlechtert. Nicht-invasive Methoden zur Erfassung und Normalisierung der inneren Uhr auf der Intensivstation sind bisher nicht etabliert. Dieses Projekt kombiniert hochauflösende Patientendaten mit dynamischer Lichttherapie, um circadiane Rhythmen wiederherzustellen.