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Leveraging Technology to Develop New Trial Endpoints

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Page 1 of 3 APPLIED CLINICAL TRIALS 29 December 2018 mHE ALTH develop new objective measures of movement and mobility. Each approach shows promise in leveraging existing technology solutions in novel ways to deliver health outcomes measures that ei- ther provide a richer picture of health status due to the ability to mea- sure remotely, or provide a potentially superior approach to develop- ment of sensitive, objective measures compared to current practice. Use cases Use Case 1: Leveraging wearable sensors to measure pain Wearable devices that measure EEG brain activity have been used to enable interaction with gaming systems, develop applications to facilitate activity and communication in impaired patients, and to provide brain training applications in personal health and wellness. 1 Examples of the latter two include the "Mind Speller" application that enables textual and verbal communication using EEG brain signals from patients with reduced motor functioning; 2 and brain training applications to assist the management of anxiety and concentration by providing insight into types of brain activity using neurofeedback. 1 Por table EEG headbands provide a means to collect this data remotely or without specialist equipment during clinic visits. These are typically worn on the forehead and collect signals using a series of dry electrodes to generate a continuous EEG trace, although some discrete cochlear devices are in development. 3 Examples include MUSE (InteraXon Inc., Toronto, Canada), Emotiv EPOC (Emotiv Inc.) and ZenZone (NeuroSky Inc.). While we discuss later in this article the additional work needed to ensure the reliability, accuracy, and precision of data collected in this way, if the potential use in clinical trials is to be realized, PainQx have conducted significant work on the validation of outcome measures derived from EEG signal data to provide objective measures of pain. In his presentation, Zamorano provided an insightful review of their scientific work to date. 4 Foundational to this work is the property that chronic pain ap- pears to be associated with increased alpha and theta EEG signals during spontaneous EEG recording, and low amplitudes of event- related potential (ERP) when the patient is presented with various stimuli. 5 PainQx have developed algorithms to interpret EEG traces to describe the patient's pain state by mapping quantitative measures of electrical activity in different regions of the brain responsible for the sensation and perception of pain. By filtering out components not related to pain sensation or perception, this "Pain Matrix" pro- vides an objective outcome measure to describe pain incidence and severity. Pertinent areas of EEG activity are isolated, identified, cor- related, and weighted to produce an objective score describing the patient's pain state. This approach has been seen to correlate well with subjective measures of pain and to distinguish between high and low pain in chronic pain conditions. 1 While self-perception of pain nature and severit y is a critical element to assess pharmaceutical inter vention effects, generally recorded using patient-reported outcome measures (PROMs), this objective measure derived from brain activity monitoring may be useful alongside these traditional PROMs. In particular, in addition to providing additional supportive data to PROM endpoints, EEG- derived outcome measures may provide additional supporting data, may enhance study qualification/screening activity, and may provide a convenient mechanism to evaluate the real-time effects and dose optimization of analgesic and narcotic drugs during treatment. Measurement using portable EEG headsets opens the door to remote measurement, and convenient measurement in clinic. How- ever, their use relies upon satisfactory reliability, accuracy, and pre- cision of data collected in this way. Some factors for consideration include the reduced number of electrodes, the fact that electrodes connect to the skin in a dry state, that measurements using head- bands predominantly represent activity from the frontal cortex, and that device firmware must be relied upon to adequately filter and in- terpret the signals received. Some of this data is becoming available for appraisal in the scientific literature, and some additional work is needed to assess the scientific acceptability of the approach. Use Case 2: Leveraging smartphone sensors to enable fre- quent outcome assessment in remote settings As described above, the sensors within smartphone handsets are al- ready being used in the wellness industry to provide health and fitness applications. Smartphones are already used in clinical trials to collect electronic patient-reported outcomes (ePRO) data, and leveraging their sensors to collect other data through active performance tests is a novel approach to accumulating additional objective data remotely and conveniently. Christian Gossens, PhD, global head of digital biomark- ers at Roche, also presented in the "Future of Endpoints" session and described new work underway in the development and validation of performance outcomes (PerfOs) aimed at studying multiple sclerosis (MS) patients and conducted by leveraging smartphone components and sensors. This work is presented within the Floodlight Open study, currently recruiting online. 6 The study aims to measure a participant's ability to perform simple tasks using their smartphone with the aim of understanding the effects of MS on cognition, dexterity, and mobility. For example, the assess- ment of pinching action between thumb and finger is commonly as- sessed subjectively using clinician-reported outcomes such as within the Unified Parkinson's Disease Rating Scale (UPDRS). This assessment measures aspects of dexterity, muscle weakness, and control. The Floodlight app has gamified this test and presented it as a task where subjects use the same pinching action on the touchscreen to "squash" tomatoes between thumb and finger as they appear on screen. In ad- dition, a drawing test where users are requested to draw along the outline of a figure of eight shapes is included to measure other aspects of dexterity, hand-eye coordination, and muscle control. In addition to enabling objective measures of constructs that have previously been measured subjectively by the clinician, one key advantage of this approach is the ability to study health out- comes more frequently than can be achieved through regular clinic appointments. This has been illustrated previously by Gossens and colleagues in their work on smartphone-delivered tests in Parkin- son's disease (PD). Detecting tremor, for example, using a simple test where the smartphone is balanced on the palm of the hand for 30 seconds and tremor-related movements are detected using the ac- For personal, non-commercial use

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