mHealth & Wearables
Remote monitoring and leveraging wearable devices and sensors in clinical trials
Advancing digital endpoints
Navigating the shift from traditional trial models to agile, patient-centric processes driven by digital health technologies.
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
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
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
Media articles on wearables, sensors and remote monitoring
Wearables in clinical trials
Wearables are improving the clinical trial experience for patients and satisfying the need to collect data for real-world use studies.
Adopting mHealth technologies in cardiovascular trials
Developing a protocol that incorporates data collection via mHealth technologies requires a comprehensive solution that has a strong patient engagement element and a robust digital framework.
The digital trial: How technology is changing trial design, start-up and close-out
To understand these large datasets, AI and machine learning are necessary to automate analyses.
The potential of activity trackers to bias study results
Wearables are purpose-built to engage users, with optimized interfaces, easy-to-use screens, appealing companion apps and easy-to-interpret dashboards.
The promise of IoMT
New ways to collect data and transforming clinical operations.
A new horizon
Maximising AI’s involvement in pharma development is to utilise its ability to draw distinctions and correlations, which would otherwise elude human observation.
How a focus on the patient drives stronger healthcare partnerships?
The foundation of healthcare is shifting from a provider-based to a patient-centric, or value-based, model.
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.
- Using objective measures of activity and standardisation of endpoints to clarify the value and impact of exercise in patients with Alzheimer’s disease
- The Journal of Prevention of Alzheimer’s Disease - The case for using actigraphy generated sleep and activity endpoints in Alzheimer’s disease clinical trials
- Can actigraphy outcome measures from existing clinical trials provide a framework for future?
Case studies on wearables, sensors and remote monitoring
Wearables and remote monitoring case study
ICON’s wearables and patient outcomes teams were able to objectively measure cough using patient-centric, novel technologies.
Remote patient monitoring for respiratory measures
Generating respiratory disease specific biomarkers using advanced analytics.
Developing and validating endpoints derived from wearables data
ICON uses AI machine learning algorithms to develop new digital biomarkers from raw accelerometer data.
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.
Leveraging BYOD, wearables and shareables in Real World Evidence studies
Approaches to leveraging mobile, wearable and shareable technology in observational research
- Webinar: What's Next in eCOA? - New insights into equivalence testing methodology and implications for BYOD
- Podcast: How Bring-Your-Own-Device (BYOD) is changing clinical research
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Article: Scrip Bring Your Own Device ePRO: Hold the relish, or no holds barred?
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Article: The use of digital technologies to collect patient data in outcomes research
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White paper: On a technology-enabled collision course - clinical research meets clinical practice through Real World Evidence
mHealth and wearables blogs
Wearables across phases
How to best incorporate digital endpoints at every stage of clinical research?
Post pandemic clinical trial strategies
How COVID-19 altered clinical trials forever and what’s next?
Wearables and digital endpoint generation
An end-to-end approach to managing wearable devices through clinical development.
Key considerations for achieving digital trial success
An end-to-end solution is required to run a successful digital trial.
A study to examine the feasibility of running a clinical trial
The REACHES study considered how assessments that are traditionally conducted at a clinic visit.
Real-time monitoring of the digital patient
Direct to patient strategies and crafting patient centric trials are of increasing interest in drug development trials.
Applications for wearables and apps in precision medicine
Patients increasingly act like consumers, expecting to control decisions about their care and to receive individualised products and services
Developing digital biomarkers from raw accelerometer data
Accelerometers can capture significant quantities of raw data, potentially containing patterns
which, could quantify specific motor movements.Leveraging motion-based gaming platforms to measure health outcomes
ICON’s Innovation lab have begun to develop prototype solutions that could be used in clinic to make objective assessments of movement and mobility.
Objective measurement of sedentary behaviour using accelerometers
Measuring treatment-related changes in sedentary behaviour using wearable technology.
Measuring Activity in COPD and Other Less Active Populations
While activity monitors have been used in clinical trials, some researchers consider a number of perceived barriers limiting their use.
Dirty data: How to manage data from wearables in clinical trials
How to manage data from wearables in clinical trials — from overcoming regulatory issues to handling challenges associated with dirty data.
The impact of digital technology on patient engagement in clinical trials
The more that can be done to encourage patients to participate in clinical trials, the faster new medicines and devices become available.