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Remote Assessment of Disease and Relapse in Central Nervous System Disorders - Sofia ref.: 115902

Periodic Reporting for period 4 - RADAR-CNS (Remote Assessment of Disease and Relapse in Central Nervous System Disorders)

Reporting period: 2019-04-01 to 2020-03-31

RADAR-CNS will develop and test a transformative platform of remote monitoring of disease state in three CNS diseases: epilepsy, multiple sclerosis (MS) and depression. The development of remote measurement technologies (RMT) is an innovation which could be used to predict and avert negative clinical outcomes by providing real time information on the patient’s current clinical state, as well as providing predictive information indicative of a future deterioration. RMT is a disruptive innovation which requires careful evaluation, with an eye kept on implementation in real world settings. CNS disorders are an excellent test bed for such evaluation because they are chronic diseases whose course is dynamic with multiple relapses that could be measured remotely and passively via unobtrusive on-body biosensors and smartphones.

Our ambition is to transform patient care through remote assessment. We will create a pipeline for developing, testing and implementing RMT for depression, MS and epilepsy. We will build an infrastructure to identify clinically useful RMT-measured biosignatures to assist in the early identification of relapse or deterioration, which can be translated into health services. We will develop a platform to identify these biosignatures from well-characterized patient cohorts and will anticipate potential barriers to translation by initiating a dialogue with stakeholders, including patients.

Our specific objectives are:
1. Building a generic RMT platform for smartphone and wearable devices to generate passive and active measurement data using experience sampling methodology (ESM).
2. Devising clinical observational studies to follow patients, stratified by known prognostic indicators, in order to test the acceptability and determine the added value of RMT.
3. Engaging stakeholders at the outset to maximise real world use of RMT and to produce relevant questions to inform clinical study design.
In the first year, collaborations and leadership where developed, and a successful management structure was set up shared between KCL, JPNV and Lygature. We have established Scientific and Patient Advisory boards and appointed an ethics advisor.

The translational cluster (WP2, 9 and 10) has concluded research determining the acceptability and potential barriers for RMT in people with MS, epilepsy and MDD. A systematic review summarising previous findings on barriers and facilitators to RMT across a breadth of health conditions has been published. Focus groups in the three disorders and three countries (UK, Italy and Spain) have been completed and analysed by WP2, with results now published. There has been strong enthusiasm from patient groups about the potential for RMT and the Patient Advisory Board has been actively engaged. Detailed care pathway mapping and surveys have been completed by WP9 identifying the likely points at which RMT will have greatest clinical utility. WP10 has mapped out the current regulatory climate for the application of RMT in healthcare.

The main technical work packages (WP7 and 8) have delivered RADAR-base, a platform for the ingestion, storage, analysis and feedback of data from RMT, and developing an analytic framework for future studies. The platform has been successfully deployed first in an in-hospital study of WP4 (epilepsy, study 1). Since November 2017 it has been deployed in the first ambulatory community study of depression and subsequently in MS. During the period November 2017-March 2018 we have been able to test the performance of the platform in clinical studies. This testing phase has been critical in identifying and resolving problems with the software and optimising participant acceptability. We have deliberately limited this testing phase to WP6 (depression) in the KCL site, so that any issues in the platform could be readily addressed because of co-location of WP6 and WP7 teams. All clinical sites are now recruiting actively, and RADAR-CNS has accumulated more patient years exposure of sensor data than virtually any similar study internationally.

As part of the preparation for the clinical studies we have conducted an extensive scoping exercise led by WP3 to assist in device selection and to identify signals of greatest value – this involved forming 7 thematic working groups which have coordinated efforts to identify the relevant variables to measure within the main RMT modalities (cognition, mood, physical activity, sleep, speech, social interactions and stress).

The clinical work packages (WP3, 4, 5 & 6) have developed and implemented study protocols. WP3 has developed the overall assessment scheme for the main studies in the 3 clinical work packages. WP4 has a study under way on the use of RMT to detect seizures in hospitalised epilepsy patients undergoing video-telemetry. After delays at the German site due to the ethics committee requiring the use of a CE marked device, we have successfully recruited 234 participants (March 2020). WP5 has recruited all 400 patients in the MS disability study and 99/240 patients in the MS depression study. WP6 has now recruited 569/600 participants with depression across the three sites, with the London site having already over-recruited to compensate for a delayed start date in Amsterdam. Adherence to the study protocols has been high, with >80% of participants completing one year follow up interviews. There is high acceptability of the passive app, however we have experienced some issues regarding adherence to the active app which requires questionnaires to be completed by participants. Following extensive technical testing, this has now been addressed and we have seen a steady improvement in active app data completion.

With the COVID-19 pandemic, we have reviewed current study progress. Site visits and data collection are affected for which mitigation measures are being sought. In all clinical studies currently under way we are measuring COVID-19 symptoms.
A major outcome of RADAR-CNS is the open source software infrastructure ‘RADAR-base’ created for collecting mHealth datasets from devices, phones and apps, consisting of:
• A github organisation to host code repository: http://github.com/RADAR-base
• A website hosted by KCL: https://radar-base.org/
• A confluence-based wiki for the documentation of the software: https://radar-base.org/index.php/documentation/
• Docker hub containers defining the backend components

By offering an end-to-end platform capable of data capture, management, modelling and visualization, we will be able to test the acceptability and clinical utility of multimodal RMT. By supporting cheap and widely available devices and where possible passive monitoring, our platform will be scalable to large populations of patients. It also offers the potential for adding new devices, new target outcomes and new diseases. With early engagement from stakeholders our system will anticipate translational and implementational barriers. The clinical management of depression, epilepsy and MS would be readily translated by this technology, with real-time monitoring and an interactive style of communication between patient and clinician. A point of strength of the RADAR-CNS project therefore refers to its potential to translate research findings into both clinical applications and technological opportunities.
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