Only 10% of people with motor neuron disease currently enter clinical trials, and many receive care interventions too late to help. Motor neuron disease (MND) is fast and unpredictable, leaving patients and care teams constantly catching up. Good multidisciplinary care prolongs life, but access is inequitable and burdensome. Trial participation is low partly because outcome measures are not patient-centred, adding further burden. This research aims to transform both care delivery and trial design. The researcher will build a personalised prediction model to time care interventions precisely, develop a new patient-reported outcome measure that captures both function and quality of life, and add remote monitoring to an existing telehealth platform. A clinical trial will test the full package. If successful, patients could receive timely, evidence-based care close to home, and many more could join low-burden clinical trials. That would accelerate the search for effective treatments while improving quality of life and survival for people living with MND today.
View original technical description
Research questions: Can highly specialised personalised evidence-based multidisciplinary care for people living with MND be delivered effectively close to home? Can technology and patient centred outcome measures reduce burden and increase participation in clinical trials? Background: Motor neuron disease (MND) is a devastating neurodegenerative disease with high-unmet needs. The pace of change in MND can be fast and unpredictable with patients and care teams constantly playing catch up with the decisions that need to be taken and the provision of care interventions is often too late. Good MDT care prolongs life in MND but access to this is inequitable and burdensome. Only 10% of patients with MND enter clinical trials, in which trial burden can be considerable in part due to non-patient centred outcome measures. Aims and objectives: I aim to transform how care is delivered and how clinical trials are conducted. I will develop and evaluate a low burden evidence-based personalised care pathway for people living with MND to support decision making, the timely delivery of care interventions to improve quality of life and survival, and increased participation in clinical trials. I will develop a care prediction model to predict the optimal timing of care interventions and use this to develop and enhance decision aids for patients. I will develop a new combined function and HRQoL preference-based patient reported outcome measure (PROM). I will define outcomes that are relevant and patient centric and evaluate technologies that enable their low burden remote collection in trials. I will develop further our Telehealth in MND (TiM) platform adding new remote monitoring capabilities and evaluating impact on care. I will develop the evidence for secretion management. Methods: I propose four work packages (WPs) that employ a broad range of qualitative and quantitative methodologies with co-design a consistent thread throughout. NICE Evidence standards framework for digital health technologies and the MRC framework for evaluating complex interventions will be adhered to. Timelines for delivery: WP1: Within 12 months the personalised prediction model will be developed. By the end of year 3 this will be integrated into decision aids. WP2: In 2 years a new PROM will be developed and ready for incorporation into clinical trials. By end of year 3 three remote technologies will be ready to be deployed in low burden clinical trials of MND interventions. By year 5 report performance of PROM and remote technologies in clinical trials. WP3: Within 3 years successful iteration of TiM implemented across the MND network with evaluation of impact completed and reported by end of year 5. WP4: Within year 1 co-design clinical trial and submit application to HTA aiming to start clinical trial in year 3. Anticipated Impact and dissemination: The key impact from this work will be the introduction of timely personalised high-quality care for those living with MND and the opportunity for all to participate in low burden clinical trials, ultimately bringing closer the day when we have an effective treatment for MND. I will disseminate findings through publication, social media, and existing partnerships.
Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.
Is something wrong? Let us know