Rethinking Clinical Trials with Digital Biomarkers
From Czuee Morey
This is a summary of a presentation I gave at the Life Science Forum Basel, Switzerland, on June 7, '18 and at the eClinical Forum, Darmstadt, Germany, on May 16, '18.
What are digital biomarkers?
I think everyone has heard of a Fitbit, and probably many of us use a Fitbit or similar device to track our movement or mobility and sometimes even our heart rate. Increasingly, there are also many smartphone apps available for health management with or without a connection to these sensor devices.
There are now more than 318,000 health applications and more than 340 sensor devices, and the number of applications is doubling every two years.
This technological advance has enabled "consumers" to track their health, but also represents an interesting opportunity for remote patient monitoring in healthcare and clinical trials. Data collected on a patient's activity and vital signs can be used to get a daily picture of the patient's health status and disease progression. The problem, however, is that the majority of these applications and devices are intended for wellness purposes and not for the diagnosis or treatment of disease.
So how can we use these digital devices as biomarkers - that is, to obtain a precise description of a disease, the course of a disease or the effect of a treatment?
This is a question that the field of digital biomarkers revolves around.
How can wearables help in clinical trials and healthcare?
In a typical clinical trial or clinical setting, the patient visits the hospital or clinic no more than once a month or even less. So the clinician can only observe the patient's signs and symptoms during that visit and has virtually no view of how the patient is doing for the 99% of the time they spend outside the clinic. Also, in some cases, such as neurological disorders, the assessments made by clinicians are based on observation, leading to variability in assessment between clinics.
Patients are only observed during hospital visits, and in many cases (such as CNS disorders) disease assessments are based on physician observation rather than quantitative and unbiased measurements.
When digital biomarkers are used, patients can perform these tests from the comfort of their own home using smartphones or sensors. For example, in a Parkinson's study, various aspects of the patient's health (as shown in the figure) were collected in a remote study using smartphone-based apps. This allows for the collection of quantitative and unbiased data on a frequent or near-continuous basis. The clinician can get near real-time feedback on each patient as to whether they are getting better or worse. This feedback can help inform the study protocol or even stop the study if the drug does not seem to be working for most patients.
The Clinical Trials Transformation Initiative (CTTI) provides a framework and detailed guidance for the development of digital biomarkers. They also outline various benefits of using digital biomarkers in clinical trials, such as patient-centricity and the ability to make faster decisions that save time and costs.
"Mobile technologies for data collection should be considered in all future studies to improve the quality and efficiency of clinical trials and the value of the data collected. - CTTI recommendations
Why do we need to validate digital biomarkers?
Recently, a few self-driving car accidents have made headlines, even though we have hundreds of car accidents every day that are due to human error! When we are dealing with human lives (compared to online shopping predictions), we want to make sure that the device and algorithms make accurate predictions even in the changing conditions of the real world.
For this reason, we need to rigorously develop and validate digital biomarkers to ensure that we are really capturing what we want to capture.
Considerations for the development and validation of digital biomarkers.
- Selection of endpoints: The first and most important consideration in developing digital biomarkers is not which device to use, but deciding which disease symptoms to capture that best represent the disease. Involving patients, caregivers and physicians in the discussion is necessary to understand which symptoms matter to patients. At the same time, it is important to consider whether these symptoms can be measured objectively and what is a meaningful change in measurement that reflects treatment benefit.
- Device selection & validation: Once it is clear which endpoints need to be measured, the right device can be selected. The device technology needs to be verified (measurement errors, deviations, etc.) and the device also needs to be validated for the specific application (reproducibility; accuracy & precision compared to gold standard or independent measurements). An observational study is required to ensure the suitability of the device before it is used in a trial.
- Data collection and analysis: Continuous measurement of vital signs in multiple patients leads to a wealth of data that is not always necessary for the required endpoints. It is therefore necessary to determine during the feasibility study which measures are useful to collect. It is important to establish appropriate controls to ensure data quality and to deal with missing data and data variability, and the maxim "garbage in - garbage out" applies not only to the input data, but also to the statistical models used
The algorithms and statistical models developed to convert the input data into a clinically relevant phenotype also need to be validated. This is particularly important as the data is collected in the real world and not in a clinical setting, which can lead to a lot of noise and outliers.
Which diseases can be tracked with digital biomarkers?
"There is a lack of technology-derived measures being used as actual outcome assessments in studies of neurological diseases such as Parkinson's and Alzheimer's, where there is a significant unmet need for interventions." - CTTI
Measurements of heart disease and diabetes are common applications for sensor-based devices. However, digital biomarkers may have the greatest impact in the monitoring of CNS disorders, as they give us the ability to measure symptoms that were previously largely untreatable. A recent article from Roche describes an observational study on the use of digital biomarkers for active and passive monitoring in a Parkinson's disease trial.
Various sensor devices are available to track different aspects of health such as activity, heart rate, blood sugar and even sleep, breath, voice and temperature. Most smartphones are equipped with multiple sensors that can perform various motion, sound and light-based tests. In addition, the smartphone can be used for psychological tests or to detect finger movements via the touchscreen. These measurements can be used in various combinations to predict the required health aspects or symptoms. I have given some examples below.
Digital therapeutics - the next frontier
As you can imagine, digital biomarkers can have various applications beyond clinical trials, e.g. in diagnostics - to identify patients affected by a disease, to collect evidence from the real world and for other services beyond the pill.
However, the most interesting application is in digital therapy, where the device/application can be used as a treatment! Last year, Pear Therapeutics received the first ever FDA approval for a digital therapeutic. They showed a clinically relevant outcome when using their app for substance use disorders compared to face-to-face therapy. Similar results were also achieved in various other disease areas.
Challenges
Digital biomarkers offer a great opportunity to measure endpoints in a remote, objective and unbiased way, which has been largely difficult until now. However, there are still some challenges that need to be considered before developing and using them to measure endpoints in clinical trials. A risk-benefit analysis of the benefits and risks on a case-by-case basis can help guide development in this area.
What do you think are the biggest challenges in implementing digital biomarkers in the clinical setting? Look forward to your comments below!
I am an Innovation Consultant & Business Analyst in the field of Digital Health at Wega Informatik in Basel.
Contact me at czuee.morey@wega-it.com for consulting or project assignments on digital biomarkers or for other digital health projects.