mHealth & Wearables

Remote monitoring and leveraging wearable devices and sensors in clinical trials

Wearable devices and sensors offer great potential in the collection of richer data and insights to enhance our understanding of the effects of treatment. They enable the collection of objective measures of intervention effects both in-clinic and in remote free-living settings. However, implementing wearables and sensors brings new challenges to clinical trial conduct, data management, including digital endpoint validation, and interpretation.

Our ICON Insights will help you to understand and successfully address the complexities of implementation of wearable devices in trial design, execution and reporting.

Whitepaper: Wearables and digital endpoint strategy and validation

Whitepaper: Wearables and digital endpoint strategy and validation

Although mHealth devices and sensors are continuing to evolve, and it is now possible to capture a vast array of physiological data, the operationalization of digital trial is not without challenges. Published in mid-June, pre-register to receive our Digital Endpoints whitepaper:

  • Develop a strategy to identify devices that are "fit for purpose"
  • The ICON framework for Digital Endpoint selection and validation to ensure the outcome measurement is robust, reliable, and interpretable
  • Address the key considerations that arise when using digital technology to support endpoint generation in clinical studies such as Device Selection, Endpoint Reliability and Sensitivity, Meaningful Change Thresholds, and Analysis Strategy and Interpretation

Watch related webinar recording

Pre-register for whitepaper
The path to a successful digital trial

The path to a successful digital trial

mHealth device technology has evolved to the point where it is now possible to collect a vast array of physiological data, sleep and activity data, and using advanced analytics to monitor patients in their own home outside of the hospital environment.

In a jointly authored article, ICON and Intel explore industry concerns about implementation of this technology in a clinical trial, including Patient Acceptance, Device Suitability, Data Complexity and Insight Generation, Operationalisation, Privacy and Security Issues, and Regulatory Acceptance.

Key considerations for achieving digital trial success 

Webinar: Best practices for implementing a successful digital trial

Case studies

Case studies

Management wearables and data in a global trials
ICON’s eCOA team and wearables consultants design, implement and manage a technology solution for a global trial across nine countries amongst patients suffering from a neurological disorder

Developing and validating endpoints derived from wearables data
ICON uses AI machine learning algorithms to develop new digital biomarkers from raw accelerometer data.

Leveraging technology to conduct a study in a decentralised care setting
ICON uses Apple Research Kit to deliver an electronic patient reported outcomes instrument using an iPad and a wrist wearable, amongst elderly patients.

Standards for measuring activity in COPD and other less active populations

Standards for measuring activity in COPD and other less active populations

Recommendations on standard approaches for wearable selection, implementation, and derived endpoints to measure changes in activity.

Sedentary behaviour is an important risk factor for a number of chronic diseases

Sedentary behaviour is an important risk factor for a number of chronic diseases

Learn how to measure treatment related changes in sedentary behaviour using wearable technology.