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Respiratory

The Respiratory theme focuses on developing and evaluating HealthTech solutions to improve the diagnosis and management of common respiratory illnesses in community settings. Our work aims to reduce the burden on patients and healthcare services by enabling better care outside of hospitals.

Key areas of focus:


  • Early detection and diagnosis
    Identifying novel diagnostic modalities for early detection of chronic lung disease in at-risk populations

  • Remote monitoring and management
    Assessing HealthTech's potential to predict clinical worsening of chronic respiratory conditions prior to symptom onset, meaning earlier treatment and prevention of unplanned hospital admissions

  • Disease management and engagement with treatment
    Identifying and evaluating digital technologies to support self-management and engagement with treatment regimes

  • Patient-centered Innovation
    Fostering innovation that aligns with the needs and priorities of people living with chronic respiratory conditions through patient and public involvement

Current projects

  • Asthma-Dx-Pc
    This project is piloting a platform study design for asthma diagnosis in primary care, evaluating multiple novel diagnostics simultaneously.
  • HERON
    This 'Priority Setting Partnership' gathers perspectives from patients, carers, clinicians and stakeholders to guide HealthTech solutions for chronic respiratory diseases.
  • CORMORANT:
    This project evaluates the accuracy, cost-effectiveness, and acceptability of the N-Tidal Diagnose  AI-powered COPD diagnostic versus current care pathways, to inform primary care use.
  • Eupnoos acoustic biomarker technology:
    This qualitative project interviews the public and clinicians about airways disease diagnosis and monitoring, exploring how a smartphone app using breath sounds could improve current care pathways. Details here.
  • ACCESS
    This project develops precise respiratory gas analysis technology, combined with computational models, to detect early signs of lung disease in community settings – enabling earlier diagnosis and treatment for those at risk.

Impact:

Our research in respiratory HealthTech aims to:

  • Reduce hospital admissions for respiratory conditions
  • Improve quality of life for patients with chronic respiratory diseases
  • Enhance the efficiency of community-based respiratory care
  • Reduce inequalities in access to respiratory care and treatment outcomes across diverse patient populations

Collaborations:

We work closely with charities, industry partners, NHS trusts and patient groups. Our current collaborations include: Asthma+Lung UK, LifeArc, Primary Care Respiratory Society (PCRS), and the Centre for Applied Respiratory Research Innovation and Impact (CARRii).

Get involved

Partner with us:
We welcome collaboration with industry and academia to drive impactful innovation in respiratory HealthTech. For partnership inquiries, contact us at hrc@phc.ox.ac.uk

Join our Patient and Public Involvement (PPI) advisory group:

We are currently establishing a PPI advisory group consisting of individuals living with and at high risk of chronic respiratory diseases. This group will help shape our research and ensure it addresses real-world needs of people with lung disease.

Click here for further details of involvement and how to sign up.

Upcoming events

Promotional graphic for the Diagnostic Evidence Workshops, three one-day courses in Oxford on 5–7 October 2026, from £175 per day, 20 places per day, run by the NIHR HealthTech Research Centre in Community Healthcare.
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Diagnostic Evidence Workshops 2026

Monday, 05 October 2026 to Wednesday, 07 October 2026 @ Nash Suite, Worcester College, Walton Street, Oxford, OX1 2HB

Three one-day Oxford workshops on evaluating diagnostic tests: basic approaches to diagnostic evidence generation and synthesis, statistical methods for test evaluation, and cost-effectiveness of diagnostics for NHS adoption. For diagnostics companies, researchers, funders and regulators. From £175 per day.

Theme lead

Co-Lead/Deputy: