Award Title: Prediction and prevention of Asthma attacks in Children
Funder: Department of Health and Social Care

Abstract: Background  Asthma attacks are costing lives and draining healthcare budgets. Attacks are preventable, but continue to occur with failures to identify early warning signs. Patients, carers and clinicians require reliable data to guide proactive care. However, existing solutions (peak-flows, symptom-diaries) provide incomplete assessments and limited by technique, subjectivity and adherence.     Our monitoring device and predictive analytics addresses these needs, providing comprehensive assessments of asthma risk. It continuously, objectively and passively monitors known markers of asthma risk (respiratory rate, nocturnal cough, wheeze) and key environmental triggers.     Aims   The current solution is developed for adults and CE-marked for research-use. Thus, key aims are to:   a) gather clinical data to develop the solution for specific needs of children and parents.  b) develop technical back-end infrastructure for interoperability and scalability within existing NHS infrastructure.  c) regulatory validation study to collect evidence on clinical efficacy, safety and usability  d) enable clinical adoption (incl. CE-marking as medical device, health-economic analysis, commercial, IP, and adoption strategy).     Project plan comprises work-packages across clinical, technical, commercial, IP and regulatory aspects. Two clinical studies are planned, first an observational data gathering study to enable development of paediatric-specific solution; second, regulatory validation via Clinical Investigation of Medical Device study. These are accompanied by technical development work-packages on the device, analytics and data system. Finally, we will plan and implement requirements through clinical-adoption and commercial work-packages.     Timelines for delivery  Project is 36months in total (increased accounting for anticipated COVID-19 impact).   Preparations for Study1 (3months)  Study1 (15m)  Study1 analysis and Preparations for Study 2 (3m)  Study2 (12m)  Study2 analysis and final preparations for regulatory submission (3m)     Anticipated impact and dissemination  An automated monitoring and predictive solution has potential to prevent personally devastating and systemically costly asthma attacks. The clinical findings will be disseminated through peer-reviewed publications, whilst clinical adoption will occur via AHSNs.

Lay Abstract: Asthma is the commonest chronic childhood condition, affecting 1in11 children, characterised by difficulty in breathing and wheezing. Acute asthma attacks remain a leading cause of unplanned hospital admissions, emergency visits and missed school-days. This causes significant disruption in their lives, severe anxiety to parents and a mounting economic burden to the NHS. Moreover, asthma attacks can be fatal: the UK has one of the highest asthma-related death rates in the developed world (1400 annually). Early recognition and management of deteriorations in asthma control can prevent attacks and emergencies. While in most cases symptoms appear before an attack, current tools (e.g. peak-flows and symptom-diaries) are unsuitable for long-term use by children as they (a) require daily active adherence (b) are subjective and dependent on child s technique and (c) do not provide detailed information on various factors associated with attacks. By the time children or parents perceive the decline, it is often too late, requiring them to rush to hospital. The challenge underpinning this unmet need is the inability to detect the signs of deterioration objectively and early at home.       BreatheOx, through two InnovateUK awards and other funding, have invented a small non-contact table-top device and associated AI algorithms that automatically monitor a range of physiological and environmental metrics without requiring patients to do or wear anything. Using motion sensors (similar to automated lights), the device captures small movements in the body when someone breathes and the algorithms estimate breathing rates. Acoustic sensors capture other clinical symptoms (e.g. coughing and wheezing), and environmental sensors monitor living conditions (e.g. temperature, humidity and volatile organic compounds) and other environmental triggers (e.g. pollen, air quality, weather). This way, the device collects objective, continuous and long-term data on a range of physiological symptoms, living conditions and outer environment. This has been tested in a clinical study involving adults and CE-marked for research.     In this project, we propose implementing this innovative monitoring and prediction technology for children. The aim is to further develop algorithms and clinical decision-support tools for early detection of asthma attacks in children by capturing early warning signs before patients perceive them through continuous long-term monitoring, enabling early treatment to stop attacks at home. Our objectives include demonstrating value in NHS care pathways by deploying the system within existing NHS infrastructure and generating real-world evidence of clinical and economic value.  To ensure efficient planning, management and delivery, project team includes BreatheOx (Oxford University med-tech spinout company, for technical, regulatory and commercial input), Birmingham Women s and Children s Hospital NHS Trust (one of the busiest UK paediatric asthma centres), Imperial College London (largest UK paediatric severe asthma translational research programme), AsthmaUK (leading Asthma charity, representing patient and public opinion) and OxfordAHSN (experts in market-access and NHS-adoption).

Research Activity Codes: 7.3 MANAGEMENT AND DECISION MAKING;4.2 EVALUATION OF MARKERS AND TECHNOLOGIES
Health Categories: RESPIRATORY