Remote monitoring and leveraging wearable devices and sensors in clinical trials
Navigating the shift from traditional trial models to agile, patient-centric processes driven by digital health technologies.
Incorporating digital health technologies into clinical trial designs has the potential to address many clinical trial challenges, including patient retention and engagement.
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.
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.
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.
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.
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.
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.
Approaches to leveraging mobile, wearable and shareable technology in observational research