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.

  • 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
  • Use our checklists for device selection and data strategy
Read the whitepaper
Wearables webinar recordings

Wearables webinar recordings

Digital endpoint strategy and validation

The COVID-19 pandemic has heightened interest in mHealth and mobile technology to capture patient insights outside of the traditional clinical setting. The application of COA principles and techniques can be applied to build the evidence package, when considering the evidence required to support digital endpoints for their submission to regulatory bodies and reimbursement stakeholders.

Best practices for implementing a successful digital trial

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.

eCOA - insights into equivalence testing methodology and implications for BYOD

Smartphone sensors to measure novel health outcomes

Activity monitoring, setting standards for clinical research

The value of measuring sleep and activity in Alzheimer

The value of measuring sleep and activity in Alzheimer's disease trials.

Sleep quality and quantity have clinical relevance in Alzheimer's disease. Review the use of wearables in Alzheimer’s disease to provide objective measures of sleep and activity patterns that are not subject to patient recall bias.

Case studies: wearables in clinical trials

Case studies: wearables in clinical trials

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.