TY - JOUR
T1 - Remote monitoring technologies in Alzheimer's disease: design of the RADAR-AD study
AU - Muurling, Marijn
AU - de Boer, Casper
AU - Kozak, Rouba
AU - Religa, Dorota
AU - Koychev, Ivan
AU - Verheij, Herman
AU - Nies, Vera J. M.
AU - Duyndam, Alexander
AU - Sood, Meemansa
AU - Fröhlich, Holger
AU - Hannesdottir, Kristin
AU - Erdemli, Gul
AU - Lucivero, Federica
AU - Lancaster, Claire
AU - Hinds, Chris
AU - Stravopoulos, Thanos G.
AU - Nikolopoulos, Spiros
AU - Kompatsiaris, Ioannis
AU - Manyakov, Nikolay V.
AU - Owens, Andrew P.
AU - Narayan, Vaibhav A.
AU - Aarsland, Dag
AU - RADAR-AD Consortium
AU - Visser, Pieter Jelle
N1 - Funding Information: This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 806999. This joint undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA. See www.imi.europa.eu for more details. This paper represents independent research partly funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. The views expressed are those of the author and not necessarily those of the NHS, the NIHR, or the Department of Health and Social Care. Funding Information: We would like to acknowledge and thank members of the RADAR-AD Patient Advisory Board for their input to the protocol. The following consortium members contributed to the design of the RADAR-AD study (sorted by affiliated partner and alphabetically): Maximilian Buegler1, Richard Fischer1, Robbert Harms1, Irene B Meier1, Ioannis Tarnanas1, Ana Diaz2, Jean Georges2, Dianne Gove2, Casper de Boer3, Marijn Muurling3, Pieter Jelle Visser3, Ioannis Kompatsiaris4, Ioulietta Lazarou4, Lampros Mpaltadoros4, Spiros Nikolopoulos4, Asterios Papastergiou4, Thanos Stavropoulos4, Dimitris Strantsalis4, Holger Froehlich5, Martin Hoffman-Apitius5, Meemansa Sood5, Nikolay Manyakov6, Vaibhav A Narayan6, Jerry G Novak6, Dorota Religa7, Emilia Schwertner7, Juraj Secnik7, Bengt Winblad7, Dag Aarsland8, Pauline Conde8, Amos Folarin8, Grace Lavelle8, Andrew P Owens8, Andrew McCarthy9, Aidan Nickerson9, Janneke Boere10, Bruna Consiglio10, Yoanna Daskalova10, Alexander Duyndam10, Irene Kanter-Schlifke10, Vera J M Nies10, Pieter Stolk10, Herman Verheij10, Neva Coello11, Jelena Curcic11, Gul Erdemli11, Tilo Hache11, Kristin Hannesdottir11, Alex Sverdlov11, Vanessa Vallejo11, Eric Yang11, Ariel Dowling12, Rouba Kozak12, Melissa Naylor12, Rodrigo Palma dos Reis12, Gene Shin12, Joris Borgdorff13, Elisa Cirillo13, Keyvan Hedayati13, Nivethika Mahasivam13, Aidan Doherty14, Chris Hinds14, Ivan Koychev14, Claire Lancaster14, Sebastien Libert14, Federica Lucivero14, Yuhao Wu14, Andre Durudas15.1Altoida Inc., Houston, USA;2Alzheimer Europe, Luxembourg, Luxembourg;3Amsterdam UMC, Amsterdam, The Netherlands;4Centre for Research and Technology Hellas, Thessaloniki, Greece;5Fraunhofer Institute for Algorithms and Scientific Computing, Bonn, Germany;6Janssen Pharmaceutica NV, Beerse, Belgium;7Karolinska Institutet, Stockholm, Sweden;8Kings College London, London, UK;9Eli Lilly and Company, Indianapolis, USA;10Lygature, Utrecht, The Netherlands;11Novartis Institutes for Biomedical Research, Cambridge, Massachusetts, USA;12Takeda Pharmaceuticals International, Cambridge, Massachusetts;13The Hyve, Utrecht, The Netherlands;14University of Oxford, Oxford, UK;15Modis, Temse, Belgium (funded by Janssen Pharmaceutica NV). Research of Alzheimer Center Amsterdam is part of the neurodegeneration research program of Amsterdam Neuroscience. Alzheimer Center Amsterdam is supported by Stichting Alzheimer Nederland and Stichting VUmc fonds. Dag Aarsland is a Royal Society Wolfson Research Merit Award Holder and would like to thank the Wolfson Foundation and the Royal Society for their support. Federica Lucivero acknowledges the Welcome Centre for Ethics and Humanities, grant number 203132. Funding Information: Altoida Inc., Houston, USA; Alzheimer Europe, Luxembourg, Luxembourg; Amsterdam UMC, Amsterdam, The Netherlands; Centre for Research and Technology Hellas, Thessaloniki, Greece; Fraunhofer Institute for Algorithms and Scientific Computing, Bonn, Germany; Janssen Pharmaceutica NV, Beerse, Belgium; Karolinska Institutet, Stockholm, Sweden; Kings College London, London, UK; Eli Lilly and Company, Indianapolis, USA; Lygature, Utrecht, The Netherlands; Novartis Institutes for Biomedical Research, Cambridge, Massachusetts, USA; Takeda Pharmaceuticals International, Cambridge, Massachusetts; The Hyve, Utrecht, The Netherlands; University of Oxford, Oxford, UK; Modis, Temse, Belgium (funded by Janssen Pharmaceutica NV). 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Funding Information: Research of Alzheimer Center Amsterdam is part of the neurodegeneration research program of Amsterdam Neuroscience. Alzheimer Center Amsterdam is supported by Stichting Alzheimer Nederland and Stichting VUmc fonds. Dag Aarsland is a Royal Society Wolfson Research Merit Award Holder and would like to thank the Wolfson Foundation and the Royal Society for their support. Federica Lucivero acknowledges the Welcome Centre for Ethics and Humanities, grant number 203132. Publisher Copyright: © 2021, The Author(s). Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/12
Y1 - 2021/12
N2 - BACKGROUND: Functional decline in Alzheimer's disease (AD) is typically measured using single-time point subjective rating scales, which rely on direct observation or (caregiver) recall. Remote monitoring technologies (RMTs), such as smartphone applications, wearables, and home-based sensors, can change these periodic subjective assessments to more frequent, or even continuous, objective monitoring. The aim of the RADAR-AD study is to assess the accuracy and validity of RMTs in measuring functional decline in a real-world environment across preclinical-to-moderate stages of AD compared to standard clinical rating scales. METHODS: This study includes three tiers. For the main study, we will include participants (n = 220) with preclinical AD, prodromal AD, mild-to-moderate AD, and healthy controls, classified by MMSE and CDR score, from clinical sites equally distributed over 13 European countries. Participants will undergo extensive neuropsychological testing and physical examination. The RMT assessments, performed over an 8-week period, include walk tests, financial management tasks, an augmented reality game, two activity trackers, and two smartphone applications installed on the participants' phone. In the first sub-study, fixed sensors will be installed in the homes of a representative sub-sample of 40 participants. In the second sub-study, 10 participants will stay in a smart home for 1 week. The primary outcome of this study is the difference in functional domain profiles assessed using RMTs between the four study groups. The four participant groups will be compared for each RMT outcome measure separately. Each RMT outcome will be compared to a standard clinical test which measures the same functional or cognitive domain. Finally, multivariate prediction models will be developed. Data collection and privacy are important aspects of the project, which will be managed using the RADAR-base data platform running on specifically designed biomedical research computing infrastructure. RESULTS: First results are expected to be disseminated in 2022. CONCLUSION: Our study is well placed to evaluate the clinical utility of RMT assessments. Leveraging modern-day technology may deliver new and improved methods for accurately monitoring functional decline in all stages of AD. It is greatly anticipated that these methods could lead to objective and real-life functional endpoints with increased sensitivity to pharmacological agent signal detection.
AB - BACKGROUND: Functional decline in Alzheimer's disease (AD) is typically measured using single-time point subjective rating scales, which rely on direct observation or (caregiver) recall. Remote monitoring technologies (RMTs), such as smartphone applications, wearables, and home-based sensors, can change these periodic subjective assessments to more frequent, or even continuous, objective monitoring. The aim of the RADAR-AD study is to assess the accuracy and validity of RMTs in measuring functional decline in a real-world environment across preclinical-to-moderate stages of AD compared to standard clinical rating scales. METHODS: This study includes three tiers. For the main study, we will include participants (n = 220) with preclinical AD, prodromal AD, mild-to-moderate AD, and healthy controls, classified by MMSE and CDR score, from clinical sites equally distributed over 13 European countries. Participants will undergo extensive neuropsychological testing and physical examination. The RMT assessments, performed over an 8-week period, include walk tests, financial management tasks, an augmented reality game, two activity trackers, and two smartphone applications installed on the participants' phone. In the first sub-study, fixed sensors will be installed in the homes of a representative sub-sample of 40 participants. In the second sub-study, 10 participants will stay in a smart home for 1 week. The primary outcome of this study is the difference in functional domain profiles assessed using RMTs between the four study groups. The four participant groups will be compared for each RMT outcome measure separately. Each RMT outcome will be compared to a standard clinical test which measures the same functional or cognitive domain. Finally, multivariate prediction models will be developed. Data collection and privacy are important aspects of the project, which will be managed using the RADAR-base data platform running on specifically designed biomedical research computing infrastructure. RESULTS: First results are expected to be disseminated in 2022. CONCLUSION: Our study is well placed to evaluate the clinical utility of RMT assessments. Leveraging modern-day technology may deliver new and improved methods for accurately monitoring functional decline in all stages of AD. It is greatly anticipated that these methods could lead to objective and real-life functional endpoints with increased sensitivity to pharmacological agent signal detection.
KW - Alzheimer’s disease
KW - Remote monitoring technologies
KW - Wearable technologies
UR - http://www.scopus.com/inward/record.url?scp=85105760857&partnerID=8YFLogxK
U2 - https://doi.org/10.1186/s13195-021-00825-4
DO - https://doi.org/10.1186/s13195-021-00825-4
M3 - Article
C2 - 33892789
SN - 1758-9193
VL - 13
SP - 89
JO - Alzheimer's Research & Therapy
JF - Alzheimer's Research & Therapy
IS - 1
M1 - 89
ER -