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Leveraging Technology to Develop New Trial Endpoints

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28 APPLIED CLINICAL TRIALS December 2018 mHE ALTH mHEALTH Leveraging Technology to Develop New Trial Endpoints Bill Byrom, PhD A merican physicist and mathematician Freeman Dyson said that the year 2000 was essentially the point at which it became cheaper to collect in- formation than to understand it. This observation, made almost 20 years ago, still rings true today as we consider the growing number of devices that we interact with on a daily basis and that collect all kinds of digital data. This is par ticularly the case with our smar tphones and the sensors cont ained in many ever yday appli- ances that connect and deliver data through the internet of things (IoT ). Modern smar tphones contain sensors that were originally in place to enable certain handset functionality, but the data they generate are now being leveraged in other novel ways to add value to the user. For example, most of them contain an accelerometer sensor. This is used to understand the 3D spatial posi- tioning of the device and to detect when the device is rotated to enable the screen display to switch between portrait and landscape modes. However, this is the same sensor used in many activity monitoring devices, such as Fitbit or Garmin wearable health trackers—and the same 3D accelerations generated and stored by the sensor to determine screen orientation can also be translated into activity parameters such as the number of steps taken by the user while carrying their smartphone. Most devices now contain health and wellness apps to exploit this capability and provide additional value to the user. This interpretation of existing data for new purposes is an exciting area of innovation that we are seeing increas- ingly in the area of personal health and wellness, and it has huge potential to transform the way in which we cap- ture measurements from patients in clinical trials. Simply put, technology like this is enabling us to provide richer in- sights and potentially measure new meaningful constructs that we have been unable to assess robustly in the past. Perhaps most importantly, technolog y gives us the ability to think originally. The ways in which we are able to leverage existing technologies developed for other purposes, in new and novel ways, to collect insightful health status data from patients in clinical trials is an exciting area of current innovation. At the 2018 Drug Information Association (DIA) Annual Meeting in Boston, there were a number of presentations exploring this precise topic, which generated meaningful and enthu- siastic conversation throughout the meeting. Ahead, I provide a brief review of the session that I chaired, entitled "Future of Endpoints," which discussed three di- verse examples at different stages of maturity in terms of their potential application within clinical trials. I fur- ther discuss future directions for these approaches, and the kinds of activities needed to enable their ultimate use to support pharmaceutical and regulatory decision- making. The aim of using technolog y in clinical trials is to simplify processes, make participation easier, improve quality, facilitate decision-making, and collect reliable, honest data. When collecting health outcomes, it is im- portant to employ approaches that enable the optimal assessment of the study concepts of interest. In some cases, this may involve the use of a technology solution. Three approaches that were presented in the DIA ses- sion are considered in this article. The first, presented by Alejandro Zamorano (PainQx) explored the use of modern brain-sensor headbands to measure electroen- cephalogram (EEG) signals and develop objective mea- sures of pain. The second, presented by Christian Gos- sens (Roche) examined the development of new health outcome measures in Alzheimer's disease using smart- phone sensors. The third, presented by myself, explored the use of motion-based gaming technology platforms to Outlining the potential of three mHealth technology approaches in enabling novel and more robust clinical outcomes measurements. For personal, non-commercial use

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