Implementing technology for clinical assessment: opportunities and challenges Gemma Stringer Manchester Dementia Clinical Research Group Division of Neuroscience and Experimental Psychology

Manchester Dementia Clinical Research Group Clinical Research Portfolio Finding the problems…. And treating them… SENSE-Cog Trial INVEST GREAT ATTILA iCST Dementia Matters Toolkit (NOWGEN) Memory drop in events (NIHR) Disease modification in prodromal Alzheimer Mild-moderate AD (MADE) Behaviour (SYMBADD) Deep & Frequent Phenotyping CYGNUS SENSE-Cog MODEM SAMS Detection and monitoring Phase llb/III medication trials Psychosocial interventions Public engagement Interventions

Manchester Dementia Clinical Research Group Clinical Research Portfolio Finding the problems…. And treating them… SENSE-Cog Trial INVEST GREAT ATTILA iCST Dementia Matters Toolkit (NOWGEN) Memory drop in events (NIHR) Disease modification in prodromal Alzheimer Mild-moderate AD (MADE) Behaviour (SYMBADD) Deep & Frequent Phenotyping CYGNUS SENSE-Cog MODEM SAMS Detection and monitoring Phase llb/III medication trials Psychosocial interventions Public engagement Interventions

Deep and Frequent Phenotyping Study Collaborators – UoM, Cambridge, Oxford, Edinburgh, Newcastle, KCL Funding: NIHR and MRC Dementias Platform UK 250 participants (some at risk of developing AD) over 12 months The tests will involve: Movement and walking (gait) assessments using wearable devices Ophthalmological assessments Magnetic Resonance Imaging (MRI) Magnetoencephalography (MEG) and electroencephalogram (EEG) Positron emission tomography (PET) Thinking and memory (cognitive) assessments Clinical assessments including blood and urine samples and cerebrospinal fluid. Development of a multi-modal marker set for measurement of change and its prevention or modification in AD. http://www.dementiasplatform.uk/the-deep-and-frequent-phenotyping-study/

Multidisciplinary collaborative project Funding: EPSRC Objective: To investigate the potential of measuring computer use as a marker of change in cognitive and functional ability

Methodology Study 1 Study 2 Study 3 Expert Reference Group Which computer-use behaviours are indicative of cognitive decline? Which cognitive domains are implicated? Study 2 Cross –sectional How do computer use behaviours relate to cognitive and functional ability? Sample: MCI/mild AD (n=19) and healthy controls (n=24) Study 3 Longitudinal Can the SAMS software detect subtle changes in computer-use behaviours over time? Does this relate to a change in cognitive functioning over time? Sample: 33 (SCI and MCI)

Results A number of computer use behaviours (keystrokes, mouse clicks, pixel count etc) were shown to be different between MCI/mild AD and HCs Computer use behaviours were related to scores on cognitive tests and measures of functional capacity NB. Hierarchical regression models showed that participants age and number of years of computer use could not account for these effects.

Results Combined computer-use behaviours (pauses, keystrokes, mouse clicks) predict functional abilities High sensitivity and specificity for cognitive impairment e.g. ‘Text’ keystrokes per min 91% correct classification of cognitive impairment (90% sensitivity and 78% specificity) ROC analysis for pauses (per min), ‘Text’ keystrokes (per min) and total mouse clicks.

Next steps for SAMS Complete the longitudinal data analysis Apply for further funding to develop the software and validate in a large sample Opportunities: Implement SAMS in other clinical trials Henry Brodaty - Centre for Healthy Brain Aging, Sydney Deep and Frequent Phenotyping

Challenges (Valley of Death) Ensuring that the academic aspirations of all collaborative teams are translated into the research objectives Clinical motivation = positive outcomes for patients How to develop a proof of concept software for routine clinical practice/the home Finding funding for implementation Bridging the gap between proof of concept and implementation with patient group Finding an industry partner to develop a proof of concept

Possible solutions Create solutions to problems that are patient-led rather than tech-led Think about the next steps (next grant) at the earliest stage Consider the academic priorities of all collaborators and integrate this into the objectives Design software that can be developed after proof of concept Involve industrial partners who want an active role in proof of concept studies Maintain communication between collaborators to keep momentum after the end of the project Utilise the CeHRes Roadmap (or new NeuroD roadmap) when designing the study

CeHRes Roadmap Contextual Inquiry: understanding prospective users and their context, analyze strong and weak points of current provision of care. Value Specification: determine which values the different stakeholders deem important and translate into user requirements. Design: develop prototype technology based on requirements, cooperative design with prospective users and stakeholders. Operationalization: launch technology, marketing plans, organizational working procedures. Summative Evaluation: evaluation: how is it being used? what is its effect on patients and healthcare? http://www.ehealthresearchcenter.org/wiki/index.php/Main_Page