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F61 Digital, high-frequency, long-term monitoring of motor and non-motor symptoms in huntington’s disease (hd) patients

Authors :
Edward J. Wild
Michael Lindemann
Scott Schobel
Florian Lipsmeier
Anne Smith
Yan-Ping Zhang
Christian Gossens
Wei-Yi Cheng
Detlef Wolf
Christian Czech
Atieh Bamdadian
Timothy Kilchenmann
Source :
Clinical studies.
Publication Year :
2018
Publisher :
BMJ Publishing Group Ltd, 2018.

Abstract

Background Smartphones, wearables and other consumer technology have high-quality sensors that enable the objective, remote, continuous and longitudinal measurement of disease symptoms. This approach has the potential to be used in future drug development and clinical practice. Aim In this study, we are exploring the feasibility of using smartphone and wrist-worn wearables for high-frequency monitoring of motor and non-motor Huntington’s disease (HD) symptoms. Method Patients with HD in the ongoing ISIS 443139-CS2 clinical study (planned enrollment, n=46) receive a smartphone and wrist-worn wearable during screening. Using these tools, patients are asked to complete daily ‘Active’ tests at home that have been designed to measure a range of motor and non-motor symptoms. Motor symptoms that are being tested include chorea and gait problems; non-motor symptoms that are in focus include cognitive processing speed. In addition, patients are asked to carry the devices with them as they go about their daily activities (i.e., ‘Passive Monitoring’). The sensor data is then securely transferred via WIFI in real-time to Roche, where it is processed and analyzed for adherence and clinically meaningful sensor data features. Results Preliminary data that has been uploaded during the first 8-week observational period in the study show that adherence is good: approximately 85% of subjects completed the entire ‘Active’ test suite on 3 or more days each week. Conclusion It is feasible to measure motor and non-motor function in patients with HD using smartphone-based assessments performed at home. This technology, including real-time data transfer and advanced analytics, provides an innovative way to learn more about patients’ daily symptoms in the clinical trial setting. Data collection in additional patient cohorts will be an important next step to broaden experience with this approach. Funded by Ionis Pharmaceuticals Inc and F. Hoffmann-La Roche.

Details

Database :
OpenAIRE
Journal :
Clinical studies
Accession number :
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