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Realising the Potential of Digital Biomarkers in Respiratory Care

   

March 15th, 2024

As healthcare progresses into the digital age, digital biomarkers offer tremendous potential for transforming and improving outcomes in respiratory care, particularly for conditions such as COPD and asthma [1]. The term “digital biomarker” refers to objective and quantifiable physiological and behavioural measurement which have been collected using digital devices such as wearables, mobile apps, and sensors [2].


Within the respiratory setting, digital biomarkers offer several potential benefits including improved patient monitoring, early exacerbation detection and treatment personalisation. However, while the promise of digital biomarkers in respiratory care is enormous, effectively utilising them remains complex and numerous hurdles must be overcome for their potential to be fully realised [3].


This article will describe in more detail how digital biomarkers can transform respiratory care and digital biomarkers which are already showing promise. We will also discuss existing challenges surrounding the use of digital biomarkers and suggest some potential ways in which we can overcome these challenges.


Transformative Value of Digital Biomarkers in Respiratory Care

Digital biomarkers have the ability to transform respiratory care as they enable remote and continuous collection of clinical data, and thereby can provide clinicians with a more complete picture of a patient's respiratory health. Respiratory diseases are often characterised by intermittent symptoms which may be missed during routine appointments.


Digital biomarkers can also aid in the detection of impending respiratory exacerbations, enabling clinicians to be more proactive in their approach to treatment. Respiratory exacerbations are a significant cause of hospitalisation, healthcare utilisation and mortality amongst both asthma and COPD sufferers [4,5].


Additionally, digital biomarkers can provide clinicians with objective information on medication adherence, treatment responses and adverse events enabling more personalised treatment. These same insights can help pharmaceutical companies better understand the real world performance of therapies which can help guide product development and commercialisation [6].

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Promising Digital Biomarkers in Respiratory Care

Several different digital biomarkers are already showing promise in respiratory care including:

  • Portable spirometers paired with smartphone apps can enable patients to easily perform lung function testing at home. In COPD patients home monitoring has been shown to have a positive effect in reducing respiratory exacerbations, hospitalisations and improving quality of life [7].

  • Unobtrusive wrist wearables can enable the continuous monitoring of vital signs including heart rate, respiratory rate, and blood oxygen levels. Vital signs changes can indicate worsening respiratory symptoms or the onset of respiratory exacerbations [8].

  • Pedometer or accelerometer tracking of physical activity can serve as an indicator of respiratory status. Lower levels of physical activity have been associated with a higher risk of exacerbations, and exacerbation-related hospitalizations in patients with COPD [9,10].

  • Sleep monitoring using consumer wearables can enable the evaluation of sleep quality and the detection of sleep disorders like obstructive sleep apnoea which are highly prevalent in COPD/asthma [11,12]. Individuals suffering from obstructive sleep apnoea and COPD are at a higher risk of death and exacerbations when left untreated [13].

  • Symptom journals enable patients to log daily symptoms such as cough, wheezing, and chest tightness using structured apps. Longitudinal logs can provide personalised insights including the identification of exacerbation triggers through the tracking of symptom trends.

Unlocking the True Value of Respiratory Digital Biomarkers

Digital biomarkers offer enormous potential, however to unlock their full value in respiratory care several challenges need to be overcome. These challenges include appropriate biomarker selection, validation and their successful integration into clinical workflows. Other challenges relate more to the digital tools used for data collection and include adoption issues, regulatory requirements, and privacy risks.


To extract genuine value from digital biomarkers, it is important that respiratory health stakeholders:

  • Base biomarker selection and analytics on tangible clinical outcomes like reduced exacerbation rates and hospitalizations while avoiding placing too much emphasis on proxy endpoints.

  • Focus data collection around hypotheses and questions that address real issues of patient need while avoiding the accumulation of unnecessary data.

  • Take a patient-centric view by identifying digital measures that are most likely to improve patient outcomes, quality of life, and care experience.

  • Validate digital biomarkers against clinical gold standards and real-world evidence and ensure results are robust enough to be applied across diverse populations and settings.

  • Consider patient burdens and monitor digital tool adoption rates as well as potential reasons for discontinuation.

  • Utilise digital biomarkers for high-value use cases first, like flagging impending asthma and COPD exacerbations which can enable early intervention.

  • Combine multidimensional data into composite scores and visualisations to simplify clinical decision-making.

  • Ensure data integration into electronic health records and clinical workflow to maximise impact and automate the identification of actionable insights.

The Future of Respiratory Digital Biomarkers

Looking ahead, we are likely to see the further evolution of digital biomarkers in respiratory care with:

  • Increasing use of multidimensional data from diverse inputs combined with the use of AI/ML techniques which will enable the generation of more novel health insights.

  • Improved data sharing across patients, providers, researchers, and geographies thereby enabling more diverse population health insights.

  • More decentralised clinical trials due to the increasing use of continuous remote patient monitoring technologies, which can improve patient access and diversity.

  • Use of "digital twins" that integrate multimodal digital biomarker data with other clinical information to create dynamic virtual patient models for simulation and prediction.

  • More gamification approaches involving digital biomarkers to better motivate patient engagement in care and self-management.

The adoption of digital biomarkers in respiratory care promises to deliver significant value both to patients, pharmaceutical companies and healthcare systems. Amongst other benefits digital biomarkers can enable earlier exacerbation detection, improve clinical decision making and provide treatment personalization. However, to impact on patient care we must both select biomarkers with high clinical relevance and ensure they are robustly validated.

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References

[1] Blakey JD, Bender BG, Dima AL, et al. Digital technologies and adherence in respiratory diseases: the road ahead. European Respiratory Journal. 2018;52:1801147.

[2] Vasudevan S, Saha A, Tarver ME, et al. Digital biomarkers: Convergence of digital health technologies and biomarkers. NPJ Digit Med. 2022;5:36.

[3] Babrak LM, Menetski J, Rebhan M, et al. Traditional and Digital Biomarkers: Two Worlds Apart? Digit Biomark. 2019;3:92–102.

[4] National Institute for Health and Care Excellence (NICE). Asthma: What is the prevalence of asthma? [Internet]. [cited 2023 Oct 26]. Available from: https://cks.nice.org.uk/topics/asthma/background-information/prevalence/.

[5] National Institute for Health and Care Excellence (NICE). Chronic obstructive pulmonary disease: How common is it? [Internet]. [cited 2023 Oct 26]. Available from: https://cks.nice.org.uk/topics/chronic-obstructive-pulmonary-disease/background-information/prevalence-incidence/.

[6] Dagenais S, Russo L, Madsen A, et al. Use of Real‐World Evidence to Drive Drug Development Strategy and Inform Clinical Trial Design. Clin Pharmacol Ther. 2022;111:77–89.

[7] Cruz J, Brooks D, Marques A. Home telemonitoring effectiveness in COPD: a systematic review. Int J Clin Pract. 2014;68:369–378.

[8] Shah SA, Velardo C, Farmer A, et al. Exacerbations in Chronic Obstructive Pulmonary Disease: Identification and Prediction Using a Digital Health System. J Med Internet Res. 2017;19:e69.

[9] Pitta F, Troosters T, Probst VS, et al. Physical Activity and Hospitalization for Exacerbation of COPD. Chest. 2006;129:536–544.

[10] Garcia-Rio F, Rojo B, Casitas R, et al. Prognostic Value of the Objective Measurement of Daily Physical Activity in Patients With COPD. Chest. 2012;142:338–346.

[11] Shawon MSR, Perret JL, Senaratna C V., et al. Current evidence on prevalence and clinical outcomes of co-morbid obstructive sleep apnea and chronic obstructive pulmonary disease: A systematic review. Sleep Med Rev. 2017;32:58–68.

[12] Davies SE, Bishopp A, Wharton S, et al. The association between asthma and obstructive sleep apnea (OSA): A systematic review. Journal of Asthma. 2019;56:118–129.

[13] Marin JM, Soriano JB, Carrizo SJ, et al. Outcomes in Patients with Chronic Obstructive Pulmonary Disease and Obstructive Sleep Apnea. Am J Respir Crit Care Med. 2010;182:325–331.

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