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Are Wearables and Sensors the Key to Disruptive Innovation in Clinical Trials-or Merely an Overhyped Distraction?
Marie McCarthy, Director, Product Innovation, ICON plc
Making trials more accessible and attractive to patients; reducing the need to travel to the sites, and developing assessments with the potential to be more responsive to change is an industry obsession. Although activity trackers have been used by the research community since the 1970s, the launch of Bluetooth enabled fitness trackers and digital platforms in the early 2000s helped drive the digital revolution. These devices have caused considerable excitement in the industry and they are seen as having truly transformative potential. If one considers that a typical trial of 12-18 months has the potential to generate 9000 hours of data, but in a traditional trial only 50 hours of in-clinic assessments are captured. There are significant possibilities of identifying clinically responsive signals and unique biometric signatures in these real world continuous data streams generated by these devices.
But 10 years on what is the reality of the situation. The adoption of the accelerometer based fitness devices in drug development industry sponsored studies is still low with only 90 studies in Clinical Trials.gov detailing the use of these devices.
In the early adoption phase, the mHealth technology was almost a distraction, and was the focus of the study rather than the clinical value, or patients themselves. There was a view among some in the industry that one could purchase a number of smartwatches, hand them out to subjects, and generate data that could be used to support a clinical endpoint.
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The use of wearables and sensors is moving towards patient-centric trials and the earlier availability of new therapies improving the lives of patients
As we move beyond the initial hype into the maximising value of the data we face new challenges. With the increasing availability of connected devices, we have the ability to create composite endpoints by combining data from multiple devices with subjective insights from ePRO. As we transition from a snapshot in clinic data capture to real-time continuous data capture, data storage and management needs increase exponentially. The data storage requirements for a traditional 200 patient study is estimated to be in the megabytes range compared to terabytes for a study that captures sub-second accelerometer data. Beyond the storage requirements, data needs to be readily accessed and analysed, ensuring data privacy and security compliance are in line with local legal requirements such as EU General Data Protection Regulation (GDPR). This presents new challenges and opportunities for those involved in global studies using mHealth technologies. Digital platforms such as Validic, Intel, and The Hyve facilitate the scaling of data capture and aggregation from multiple sensors. Similarly, cloud based platforms such as the Amazon Web Services (AWS) and Microsoft Azure are refining their services so that in addition to the storage and database options they are now offering machine learning and analytics tools.
It is clear that wearables and sensors are seen as key components in facilitating new trial design. This approach is gaining momentum in clinical trials design. However, the true value of wearables and sensors will emerge in the coming decade as their use is moving beyond mere hype to creating patient-centric trials and the earlier availability of new therapies improving the lives of patients.