Victoria Hunter

Respiratory conditions are some of the most pressing in terms of new therapies, as the 

 worldwide. Clinical trials for respiratory conditions

 as expensive as the average clinical trial at an average of $91 million versus $48 million estimated cost of trials per drug by therapeutic area. Digital biomarkers may be one avenue to accelerate research and potentially bring study costs down.

Digital biomarkers are measurements collected through a digital device, such as portable, digital spirometers and smartwatches that can track real-time changes in a person's health or behavior. These are objective, quantifiable measures of physiological or behavioral functions that can be captured to assess patient response to therapy, or for patient screening.

While often it’s necessary to develop entirely new digital biomarkers when moving to remote data collection, that’s not usually the case in respiratory research, since these biomarkers are often digitized, at-home versions of the current gold standard. For example, a patient will use a Bluetooth-enabled spirometer at home, rather than an analog spirometer handed to them by a nurse in a clinic.

For respiratory studies, digital biomarkers offer a non-invasive way to monitor respiratory function and provide objective data on symptoms and disease progression in clinical trials. The tests can be conducted at home, in the clinic, or used during at-home visits, eliminating travel-related patient burdens. With more data points captured in a shorter period, a respiratory clinical trial could potentially be completed faster without sacrificing quality. With digital biomarkers, a patient can also undergo repeated testing. By capturing a high volume of data, researchers can control for factors that drive variation in spirometry measures, to potentially increase a study’s statistical power and decreasing the number of patients needed to demonstrate treatment effect.

Asthma is an ideal condition in which to build this body of evidence with digital biomarker studies. While both obstructive and restrictive lung disease will be able to benefit from remote data collection, obstructive lung disease, and the corresponding FEV-1 (Forced Expiratory Volume in the first second) measure, has been proven as suitable and effective.

, which is a single arm interventional trial comparing the detection of treatment effects by means of at-home mobile spirometry using an ultrasonic spirometer and a smartphone, compared to in-clinic spirometry in participants with moderate asthma. The ongoing study will recruit up to 60 participants with moderate uncontrolled asthma over a six-week treatment period who are taking inhaled corticosteroids at the time of study enrollment but require 

At-home assessments can provide researchers more complete data, and offer patients simpler and more accessible ways to participate in clinical research. While increasing efficiency and the potential for more diverse study populations, at-home assessments can also uncover new insights. For instance, repeat measurements from mobile spirometry have been 

 to uncover information about diurnal variation in respiratory conditions—the way symptoms change throughout the day and night. Digital biomarkers used in remote assessments can also answer t

A respiratory clinical trial using at-home measures must be designed in a way that solves for not only compliance, but for participant motivation—a problem across all research, but particularly for respiratory studies since the assessments often require additional effort from study participants. Newly diagnosed patients may be less accustomed to lung function tests, and training and coaching can help them to understand not only the technology and the process, but the importance of completing the assessment with total effort.

One primary challenge is ensuring that remote measures are collected with consistency and quality. While variability of at-home versus in-clinic measures has been a 

 have shown that at-home results can match in-clinic efforts. Advances in hardware, software, and patient-centric trial design make this possible. For example, ultrasonic spirometers improve upon traditional turbine spirometers by having no moving parts to be calibrated. Automatic overreading, powered by AI, is another example of advancement—this time, in data-quality review, to ensure not only that patients are compliant throughout a trial, but that they are completing assessments to their full capacity.

At-home spirometry is a challenging assessment in clinical trials. However, remote data collection has the potential to reduce many other challenges that clinical trials face, and the challenges it does pose have been addressed by a growing number of experts. Training and coaching must be accompanied by a suite of educational and motivational resources such as pamphlets, short videos, step-by-step in-app directions, and regular check-ins with adequate trained study-site staff, to help patients stay engaged in the trial.

The adoption of digital biomarkers in clinical trials may help remove some of the barriers to study participation for patients, with improved data capture and enhanced data analysis. This can improve decision-making, but most importantly, digital biomarkers in clinical trials is another example of how the future is developing in connected healthcare to create a more inclusive experience for patients.

, digital biomarker director; both with Koneksa

Articles

Increased data output from the use of devices can accelerate trials for this therapeutic area in need of new therapies. 

Victoria Hunter

Articles

Breathing New Life into Respiratory Clinical Trials with Digital Biomarkers