RADAR-AD
RADAR-AD (Remote Assessment of Disease And Relapse – Alzheimer’s Disease) aimed to transform patient care through remote assessment – using mobile technologies such as smartphones or fitness trackers, and the use of devices such as pads. The project developed technology to identify which clinical or physiological features – digital biomarkers – can be measured remotely to predict deterioration.
To achieve this, we created a pipeline for developing, testing and implementing remote measurement technologies for Alzheimer’s Disease. Patients were involved at each stage of development. The project included a generic data management and modelling infrastructure already in use (in the RADAR-CNS project). This platform developed with the flexibility to be adapted for future technological developments and similar projects.
We anticipated any potential problems with using remote measurement technologies by consulting patients, caregivers, clinicians, payers, regulators and healthcare providers throughout the project duration.
We brought an international consortium of academic and industrial members who are leaders in the field of Alzheimer’s Disease. We delivered clinical expertise and access to patient cohorts in this disease area. All of this is combined with leading technical and methodological expertise in the disciplines required to develop and implement remote measurement technologies.
Methods
RADAR-AD (Remote Assessment of Disease and Relapse – Alzheimer’s Disease) aimed to identify biosignatures indicative of functional decline in early Alzheimer’s Disease (AD) by using remote monitoring techniques. The goal was to do so by exploring how mobile technologies – such as smart phones, wearables and home-based sensors – can measure disability progression associated with AD with greater sensitivity than currently used methods, such as direct observation or caregiver recall.
To reach our goal, we assessed which functional domains are most relevant for people with early AD and can most accurately predict disease progression. This was done via statistical analysis of available longitudinal cohorts, patient focus groups, and literature reviews. The outcome of this assessment was used to identify devices that are well-suited to accurately measure these relevant functional domains. These measurements include physiological state, behavioural and cognitive biomarkers, as well as active or passive assessments.
Device selection was also be based on functionality, patient acceptability and value for money. In addition to standard devices (like smartphones or fitness trackers), we explored novel and complex devices. The combination of using standard devices and novel, complex devices allowed for feasible and low-risk data collection, as well as the maintenance of a highly innovative approach.
The devices were assessed in an exploratory study for their utility in making group comparisons, associations with other cognitive, functional, and biomarker measures, and modelling functional decline.
Data will was captured and modelled by using the RADAR-base platform, which is a generic data management and modelling infrastructure. RADAR-base was initially developed for the RADAR-CNS project and is designed in a flexible way so that it can easily be adapted to accommodate other satellite projects that revolve around remote measurement technologies.
To pave the way for such potentially ground-breaking technologies and approaches, it was critical to proactively identify and address potential barriers to effective implementation. We worked closely together with patients, caregivers and regulators to ensure that adequate regulatory frameworks are developed, that technologies are safe and convenient to use, and that the data and privacy of patients are protected.
Principal Investigator
Director, Centre for Healthy Brain Ageing