Fibrotic Interstitial Lung DiseaseAIRMILDNCT07844915
Artificial Intelligence Enhanced Remote Monitoring in Interstitial Lung Disease
A study testing AIRM v1.0 AI-Enhanced Remote Monitoring in people with Fibrotic Interstitial Lung Disease, run by King's College London at 1 site in United Kingdom.
Trial summary
The goal of this clinical trial is to learn whether artificial intelligence AI-enhanced remote monitoring (AIRM) is feasible, safe and acceptable for adults with fibrotic interstitial lung disease (fILD). Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Fibrotic Interstitial Lung Disease
- What is being tested?
- AIRM v1.0 AI-Enhanced Remote Monitoring
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 120 participants
- Where
- 1 siteUnited Kingdom
- Study dates
- 1 Dec 2026to 1 Jun 2028
- Phase
- Interventional
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Aged 18 years or older.
- Diagnosis of fibrotic interstitial lung disease (fILD) confirmed through multidisciplinary team review at a tertiary ILD centre, based on high-resolution computed tomography (HRCT) and standard clinical assessment.
- Forced vital capacity (FVC) >45% predicted.
- Able to perform spirometry and use a home spirometer safely and reliably.
- Availability of baseline pulmonary function tests (PFTs), preferably within the preceding 6 months as part of routine clinical care.
- Access to a compatible smart device with internet connectivity.
- Able to understand study procedures, communicate with the research team, and complete study questionnaires and remote monitoring tasks.
- Has capacity to provide informed consent.
Who cannot join
- Previous participation in the REMILD study.
- Estimated life expectancy of less than 6 months, as judged by the treating clinician.
- Contraindication to spirometry in accordance with Association for Respiratory Technology and Physiology (ARTP) guidelines.
- Current or recent acute exacerbation of ILD, confirmed clinically and/or radiologically, within the previous 4 weeks.
- Active or life-limiting malignancy that, in the opinion of the treating clinician, is likely to affect participation, adherence to study procedures, or interpretation of study outcomes.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
United Kingdom1 site
King's College London
London
Marium Naqvi, 4402071880599, marium.1.naqvi@kcl.ac.uk
About this study
Official title: A Mixed-Methods Feasibility Study Evaluating Artificial Intelligence Enhanced Remote Monitoring in Interstitial Lung Disease
The goal of this clinical trial is to learn whether artificial intelligence AI-enhanced remote monitoring (AIRM) is feasible, safe and acceptable for adults with fibrotic interstitial lung disease (fILD). The artificial intelligence (AI) system uses information collected through home monitoring to identify patterns that may suggest a person's lung condition is getting worse. The AI does not make treatment decisions. Its outputs are reviewed by healthcare professionals.
The main questions this study aims to answer are:
Read more
Is AIRM feasible and acceptable for people with fILD and their healthcare professionals? Can it be used safely to help identify possible worsening of fILD? How well does the AI system identify clinical deterioration?
Participants will take part for about 12 months. They will:
Measure their lung function and oxygen levels at home each week using connected monitoring devices.
Report their breathlessness and cough symptoms each week using the patientMpower app.
Complete questionnaires about their health and their experience of remote monitoring at the start of the study and every 3 months.
Continue to receive their usual clinical care.
Some participants will also be invited to an interview or focus group to discuss their experience of AI-enhanced remote monitoring. Healthcare professionals involved in the study may also be invited to discuss their experience of using the system.
The AI system is investigational and is being evaluated as part of this study. Healthcare professionals will review relevant AI-generated alerts before taking any clinical action. The AI will support, rather than replace, clinical judgement.
Read the detailed description
AIRMILD is a prospective, single-arm, mixed-methods feasibility study evaluating artificial intelligence-enhanced remote monitoring (AIRM) in people with fibrotic interstitial lung disease (fILD). Approximately 120 participants will be recruited from the interstitial lung disease (ILD) service at Guy's and St Thomas' NHS Foundation Trust (GSTT).
The study will evaluate AIRM version 1.0, an investigational artificial intelligence (AI) algorithm integrated within the patientMpower remote monitoring platform. AIRM analyses longitudinal multimodal remote monitoring data, including home spirometry, pulse oximetry, symptom scores and patient-reported measures, to identify patterns associated with potential clinical deterioration.
AIRM is intended to support clinical review rather than replace clinical assessment or clinical decision-making. It will not make autonomous diagnoses or treatment decisions. AIRM-generated outputs that may contribute to clinical management will be reviewed by an appropriately qualified clinician before clinical action is taken. Clinicians will retain independent clinical oversight and responsibility for clinical decisions. Participants will continue to receive usual clinical care throughout the study.
AIRM version 1.0 is investigational and is not UKCA or CE marked. The prediction algorithm will be fixed before prospective evaluation and will not be retrained or modified during participant follow-up. This will allow the performance of the predefined model to be evaluated prospectively against clinically identified deterioration.
The study will assess the feasibility of delivering an AIRM pathway in clinical practice, including participant engagement with remote monitoring and the practical integration of AI-generated information into clinical review. Safety evaluation will include assessment of situations in which AIRM generates an alert without subsequent clinical deterioration and situations in which clinical deterioration occurs without a preceding AIRM alert. The study will also evaluate the performance of AIRM in identifying potential clinical deterioration.
A mixed-methods evaluation will explore the acceptability, usability and perceived clinical value of AIRM. A purposive sample of participants will be invited to take part in qualitative interviews or focus groups following their period of remote monitoring. Healthcare professionals involved in the pathway will also be invited to participate. Qualitative data will be analysed thematically to explore experiences of remote monitoring, interaction with the AI-enhanced pathway, perceived benefits and concerns, and factors that may affect future implementation.
Findings from the quantitative and qualitative components will be considered together to assess the feasibility, safety and acceptability of the pathway and to inform the design of future evaluation of AIRM in fILD.
- Conditions
- Fibrotic Interstitial Lung Disease
- Being tested
- AIRM v1.0 AI-Enhanced Remote Monitoring
- Keywords
- Artificial intelligence, Remote monitoring, Interstitial lung disease
- Medical subject headings
- Lung Diseases, Interstitial
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AIRM v1.0 AI-Enhanced Remote MonitoringDevice
Also called AIRM
AI-enhanced remote monitoring (AIRM) delivered through the patientMpower platform for 12 months. Participants will use connected home spirometry and pulse oximetry devices and report symptoms and patient-reported measures. AIRM version 1.0 is an investigational artificial intelligence (AI) algorithm that analyses longitudinal multimodal remote monitoring data to identify patterns associated with potential clinical deterioration in fibrotic interstitial lung disease (fILD). AIRM-generated outputs that may contribute to clinical management will be reviewed by an appropriately qualified clinician before any clinical action is taken. The algorithm will remain fixed during the prospective study and will not be retrained or modified during participant follow-up. AIRM supports, rather than replaces, clinical judgement and usual clinical care.
| Study group | Role | What they receive |
|---|---|---|
| AI-enhanced remote monitoring pathway | Experimental | Participants will receive AI-enhanced remote monitoring (AIRM) for 12 months using the patientMpower platform. Participants will undertake home spirometry and pulse oximetry, report symptoms, and complete patient-reported measures. AIRM version 1.0, an investigational artificial intelligence (AI) algorithm, will analyse longitudinal remote monitoring data to identify patterns associated with potential clinical deterioration. AIRM-generated outputs that may contribute to clinical management will be reviewed by an appropriately qualified clinician before any clinical action is taken. AIRM will support, rather than replace, clinical judgement, and participants will continue to receive usual clinical care. Receives: Device: AIRM v1.0 AI-Enhanced Remote Monitoring |
What is being measured
The primary outcome is the main question the study is designed to answer.
Recruitment Rate of Eligible Participants
Recruitment rate will be calculated as the number of eligible individuals who provide informed consent and enrol in the study divided by the total number of eligible individuals approached for participation, multiplied by 100. The outcome will be reported as a percentage.
Measured: Up to 24 weeks
Percentage of Enrolled Participants Retained at 12 Months
Retention rate will be calculated as the number of enrolled participants who remain enrolled in the study through to the end of the 12-month active remote monitoring period divided by the total number of participants enrolled, multiplied by 100. The outcome will be reported as a percentage.
Measured: Up to 12 months
Percentage of Weekly Home Spirometry Measurements Completed
Calculated as the number of scheduled weekly home spirometry measurements completed by participants divided by the total number of scheduled home spirometry measurements, multiplied by 100.
Measured: Up to 52 weeks
Percentage of Scheduled Pulse Oximetry Measurements Completed
Calculated as the number of scheduled weekly pulse oximetry measurements completed by participants divided by the total number of scheduled pulse oximetry measurements, multiplied by 100.
Measured: Up to 52 weeks
Percentage of Scheduled Weekly Cough Assessments Completed (Cough Visual Analogue Scale)
Calculated as the number of scheduled weekly Cough Visual Analogue Scale assessments completed by participants divided by the total number of scheduled Cough Visual Analogue Scale assessments, multiplied by 100. The Cough Visual Analogue Scale assesses cough severity during the past week on a scale from 0 to 100, with higher scores indicating greater cough severity.
Measured: Up to 52 weeks
Percentage of Scheduled Weekly Breathlessness Assessments Completed (Breathlessness Visual Analogue Scale)
Calculated as the number of scheduled weekly Breathlessness Visual Analogue Scale assessments completed by participants divided by the total number of scheduled Breathlessness Visual Analogue Scale assessments, multiplied by 100. The Breathlessness Visual Analogue Scale assesses breathlessness severity during the past week on a scale from 0 to 100, with higher scores indicating greater breathlessness severity.
Measured: Up to 52 weeks
Percentage of Scheduled Patient-Reported Measures Completed
Completion of scheduled patient-reported measures will be assessed across the Idiopathic Pulmonary Fibrosis Patient Reported Outcome Measure (IPF-PROM), Idiopathic Pulmonary Fibrosis Patient Reported Experience Measure (IPF-PREM), EQ-5D-5L, SpiroQ Home Spirometry Satisfaction Questionnaire, Patient Health Questionnaire-9 (PHQ-9), Generalised Anxiety Disorder-7 (GAD-7), and Porter-Novelli 10-item Patient Engagement Scale. The outcome will be calculated as the number of scheduled patient-reported measures completed divided by the total number of patient-reported measures scheduled for completion, multiplied by 100, and reported as a percentage.
Measured: Baseline, 3 months, 6 months, 9 months and 12 months
Percentage of Clinician-Confirmed Clinical Deterioration Events Without a Preceding AIRM Alert
Calculated as the number of clinician-confirmed clinical deterioration events occurring without a preceding AIRM alert within the previous 4 weeks divided by the total number of clinician-confirmed clinical deterioration events, multiplied by 100. The outcome will be reported as a percentage.
Measured: Up to 52 weeks
Number of Device-Related Adverse Events
Number of adverse events related to the remote monitoring devices or monitoring platform during the 12-month active remote monitoring period.
Measured: Up to 52 weeks
Percentage of Participants Reporting Remote Monitoring as Easy or Very Easy
Participant acceptability will be assessed using the SpiroQ Satisfaction Questionnaire. Participants rate the ease of remote monitoring using response categories ranging from "very easy" to "very difficult", with an additional "I don't know/not applicable" option. The outcome will be reported as the percentage of participants selecting "easy" or "very easy."
Measured: Baseline, 3 months, 6 months, 9 months and 12 months
Clinician Perspectives on the Acceptability of AIRM
Clinician acceptability will be explored through focus groups with clinicians involved in the AIRM remote monitoring pathway. Qualitative data will be analysed thematically to identify themes relating to the acceptability of using AIRM within clinical practice.
Measured: Up to 15 months
Secondary outcomes (7)
Percentage of AIRM Alerts That Are False-Positive Alerts
Calculated as the number of AIRM alerts not associated with a clinician-confirmed clinical deterioration event divided by the total number of AIRM alerts, multiplied by 100.
Measured: Up to 52 weeks
Sensitivity of AIRM for Identifying Clinically Significant Deterioration Events
Calculated as the number of clinician-confirmed clinical deterioration events identified by AIRM divided by the total number of clinician-confirmed clinical deterioration events, multiplied by 100.
Measured: Up to 52 weeks
Percentage of AIRM Alerts Leading to Clinical Review
Calculated as the number of AIRM-generated alerts that result in clinical review by a clinician divided by the total number of AIRM-generated alerts, multiplied by 100. The outcome will be reported as a percentage.
Measured: Up to 52 weeks
Percentage of AIRM Alerts Leading to Clinical Intervention
Calculated as the number of AIRM-generated alerts that result in clinical intervention divided by the total number of AIRM-generated alerts, multiplied by 100. The outcome will be reported as a percentage.
Measured: Up to 52 weeks
Number of Emergency Hospital Admissions
The total number of emergency hospital admissions occurring during the 12-month study period will be recorded for each participant and summarised across the study population.
Measured: Up to 12 months
Number of Outpatient Attendances
The total number of outpatient attendances occurring during the 12-month study period will be recorded for each participant and summarised across the study population.
Measured: Up to 12 months
Number of Other Clinically Relevant Healthcare Contacts
The total number of other clinically relevant healthcare contacts, e.g. helpline, occurring during the 12-month study period will be recorded for each participant and summarised across the study population.
Measured: Up to 12 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted28 Sep 2026
- Study start1 Dec 2026 (estimated)
- Primary completion1 Mar 2028 (estimated)
- Study completion1 Jun 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Fibrotic Interstitial Lung DiseaseStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Other
- Allocation
- Not applicable
- Intervention model
- Single group
- Model description
- Single-arm feasibility study in which all participants receive the same AI-enhanced remote monitoring intervention for 12 months. There is no comparator or control group.
- Masking
- None (open label)
- Enrolment
- 120 participants (estimated)
Sponsor and investigators
- Lead sponsor
- King's College London
- Sponsor type
- University, hospital or other
- Collaborators
- patientMpower Ltd.
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07844915
- Sponsor's protocol ID
- 353066
- Acronym
- AIRMILD
- Status last verified
- Sep 2026
- First submitted
- 16 Sep 2026
- Last updated
- 28 Sep 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No