Completed Lungs & Breathing Public Health & Healthcare

Design and usability test of age-stratified afloPaediatric apps connected to the aflo asthma management device and platform

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AI plain-English summary

Only 13% of children arriving at A&E with an asthma attack use their inhaler correctly. This project will co-design and test three age-specific smartphone apps, called afloPaediatrics, that connect to a sensor-equipped inhaler device to train children in proper technique and allow clinicians to monitor their use remotely. The problem is stark. Inhaler technique errors drive poor symptom control, yet the NHS cannot provide the annual in-person reviews that NICE guidelines recommend. Children from poorer backgrounds are 70% more likely to develop asthma, and the UK has the worst death rate from asthma in Europe for those aged 10–24. Existing adult-focused solutions do not meet children’s needs. If successful, the apps could embed correct inhaler technique from childhood, reducing attacks, hospitalisations, and reliance on high-carbon rescue inhalers. The data-driven platform would support a hybrid care pathway—part remote monitoring, part clinic visits—that is achievable within current NHS capacity. This directly addresses the Life Sciences Vision’s goal to cut asthma deaths and develop better monitoring technologies for children and young adults.

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**Globally asthma is the most common non-communicable disease in children,** with about 10-15% having asthma symptoms in the last year. Inhaled medication is the mainstay of treatment but **inhaler technique errors amongst all users and all devices are highly prevalent**. Evidence shows **high asthma prevalence in children in the UK with 1.1 million children on active asthma treatment**. Being born into poor circumstances increases the risk of developing asthma by 70% (NIHR). The **UK has the worst death rate for asthma in children and young people aged between 10 and 24 in Europe (Asthma+LungUK)**_._ The **Life Sciences Vision Respiratory Mission priorities describe the global need 'to significantly reduce the number of attacks, hospitalisations and deaths_',_ to develop 'better monitoring technologies_'_ and for '_more effective treatment options for asthma, particularly children and young adults_'.** Kennedy (2022) showed that **only 13% of children with asthma presenting at ED/ admitted had correct inhaler technique**. Poor adherence and **incorrect inhaler technique are significant drivers of poor symptom control** (McCrossan et al 2022). NICE guidelines **(NG80) recommend inhaler technique should be trained and reviewed annually to optimise medication and improve symptom control**. This is **unachievable** in the current pathway for capacity and technology reasons. Over the last 3 years, with the support of previous IUK awards **this project team has successfully co-designed, built, patented and clinically tested the functionality of a deep tech respiratory platform, aflo, for adult inhaler users**, to medical device standards. It was **co-designed with users to automate all steps of the UK Inhaler Group recommended inhaler technique**, to **improve outcomes, allow remote monitoring, reduce healthcare utilisation**. Our trial data shows that a **paediatric specific platform is needed to optimise medication**. Post Covid capacity issues have resulted in limited access to in-person primary care support for inhaler technique training and patient review. The **primary goal of this research proposal is to address the well recognised challenge of establishing persistent correct inhaler technique for children with asthma**. Through this R&D we will **co-design with children, carers and clinicians, and test 3 personalised, age-stratified apps - afloPaediatrics - integrated with the latest sensor technology in the aflo device, delivering a data driven approach to inhaler technique training and clinical monitoring**. This will embed correct inhaler technique and **support a new data driven, hybrid asthma care pathway for children**, which supports the NHS Net Zero target, reducing high carbon Short Acting Beta Agonist over-reliance.

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Related Research

Grants with similar aims, by meaning.

Clinical study of an inhalation training and feedback device, user app, clinician portal and cloud based data analytics tool for self management and remote monitoring of respiratory conditions
AI driven inhalation technique and adherence support device with data aggregation platform for remote monitoring of asthma
Breathing REtraining for Asthma Trial of Home Exercises for Teenagers (BREATHE4T); repurposing, refining and feasibility
Development of a non-bluetooth smart inhaler.
Reducing the environmental impact of Metered Dose Inhalers with aflo, the automated inhaler technique platform

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Collaborative R&D

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