Resource Library

Discover how the V3 framework determines whether biometric monitoring technologies (BioMeTs) are fit-for-purpose to generate reliable digital biomarkers and endpoints in clinical trials.

Explore how Merck and Koneksa Health tested whether mobile health-derived heart rate and blood pressure data can match traditional clinic measures, and detect real pharmacological effects, in an 18-subject Phase I trial.

Learn how a wearable biosensor accurately detected activity-induced heart rate changes following amphetamine administration in a Phase I trial (Bland-Altman confirmed), while respiratory rate data fell short, reinforcing that wearable validation must happen parameter by parameter, not device by device.

Learn how CTTI’s recommendations tackle the real barriers to mobile technology adoption in clinical trials, from technology selection and data management to FDA submission readiness, without changing the scientific principles that trials have always relied on.

Explore how smartphones, already carried by over 2.5 billion people worldwide, are poised to reshape oncology care through continuous patient-generated health data, digital biomarkers, and more personalized clinical decision-making, even as data integration, patient engagement, and privacy remain real barriers to scale.

Discover how a systematic review of 275 feasibility studies covering sensor performance, algorithm development, and operational fit is helping sponsors choose the right mobile technology for their clinical trial endpoints, rather than defaulting to whatever device is most familiar.

Discover why heart rate data from a wearable biosensor patch correlated strongly with in-clinic measures (r = 0.71) in a Phase I trial, while respiratory rate and skin temperature readings fell short, underscoring the need for fit-for-purpose validation before any wearable device is deployed in drug development.

A foundational review of how wearable devices in clinical trials move from raw sensor data to validated, regulatory-grade endpoints through analytical and clinical validation.

Learn how objective wearable data challenges assumptions about radiation-related fatigue in breast cancer patients.