Predicting and characterising asthma exacerbations using a contactless respiratory night monitor
Lead supervisor: Professor Nayia Petousi
Co-supervisor: Professor Ian Pavord
Commercial partner: BreatheOx Limited (trading as Albus Health)
The project is a translational multi-disciplinary academic-industry collaboration. It utilizes objective symptom data passively collected from patients, enabled through advances in contactless sensor technology and Artificial Intelligence (AI), to predict life-threatening asthma attacks several days in advance – one of the most pressing needs in respiratory medicine. The student will lead cross-sectional and longitudinal studies, incorporating training in whole-human physiology and airway biology, clinical research with patients, data science, and medical innovation within healthcare systems.
Asthma affects ~300 million people worldwide, with many experiencing significant daytime and night-time respiratory symptoms. Symptom changes can go undetected, which can result in exacerbations (flare-ups or “attacks”) leading to hospitalizations and, in some cases, deaths. Identifying at-risk patients, understanding the nature of attacks and predicting their onset to trigger early interventions remain key challenges in respiratory medicine.
Albus Health has developed a small contactless multi-sensor device, Albus Home, that automatically monitors vital signs, cough, sleep and a range of respiratory physiological parameters from the patient’s bedside, without patients needing to do or wear anything. Early published studies show strong monitoring accuracy in adults and suggest an ability to detect deterioration several days before asthma attacks in children.
This project will evaluate Albus Home in adults with severe asthma through:
Cross-Sectional Study: Patients will be thoroughly phenotyped using clinical (symptom scores), biological (type-2 biomarkers: FeNO, eosinophils) and physiological (spirometry, oscillometry) assessments, and compared to healthy controls. All participants will use the Albus Home Monitor over several nights. Albus Home’s ability to distinguish asthma versus healthy, and variations of physiological patterns across asthma biological subtypes (eg. Type-2 high versus low) will be assessed.
Longitudinal Study: A cohort of patients prone to frequent exacerbations will use Albus Home nightly for up to 12 months. When they experience a flare-up, they will undergo detailed phenotyping (clinical, biological, physiological) prior to treatment. We will investigate whether and how early Albus Home can predict attacks, and variations of those predictions with attack type (inflammatory vs. infective) and severity. Patients will also be studied before and after treatment, including advanced biologic therapies.
The collaboration between Oxford’s Respiratory Medicine Unit (RMU) in the Nuffield Department of Medicine (Experimental Medicine) and Albus Health, an Oxford spinout company, provides the ideal foundation for an enriching doctoral project. The student will work with world-leading respiratory researchers on urgent clinical needs with access to well-characterised patients, innovative technology, and full spectrum of clinical innovation – from patient assessment and data collection to modelling and multistakeholder analysis for clinical adoption. This collaboration enables RMU to advance its core research area: predicting and preventing respiratory disease and exacerbations; and supports the objectives of Albus Health to further validate the technology in asthma patients and generate evidence for clinical adoption.
The project strongly aligns with MRC’s remit by: building capacity in precision medicine, data and diagnostics; training on cross-level approaches to research; deploying advances in AI and sensor data at the human health and biology interface; fostering inter-disciplinary skills, thus enabling researcher mobility across research sectors and innovation ecosystems.
Apply using course: DPhil in Clinical Medicine
