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Digital biomarkers can change the healthcare landscape

Your 6-Minute Guide to Digital Biomarkers

by Shadi Zarei, MD, MSc 6 minute read

Digital biomarkers are changing the landscape of medicine and biomedical research. Their popularity is increasing. Investments in them are growing, and more digital health and pharma companies are joining the field every day. But why? What are digital biomarkers, and what makes them so attractive? If you’ve got six minutes to spare, The Sidebar will answer these questions and more.

What are Traditional Biomarkers?

Traditional biomarkers are an essential part of clinical practice and research. The FDA-NIH Biomarker Working Group defines them as “characteristics that are measured as an indicator of normal biological processes, pathogenic processes, or responses to an exposure or intervention including therapeutic interventions. This can include molecular, histological, radiographic, or physiologic characteristics.”

Since the development of modern medicine, traditional biomarkers have been the leading player in assessing patients and evaluating diagnosis, treatments, and prognosis. 

Traditional biomarkers are collected through clinical tests or examinations when an individual visits a healthcare provider in-person. Blood pressure readings by a nurse or measuring serum cholesterol or blood sugar at a lab are examples of such biomarkers. However, the integration of smartphones and other digital devices into our daily lives has created a window of opportunity for the emergence of digital biomarkers.

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So, What are Digital Biomarkers?

Digital biomarkers refer to “objective, quantifiable, physiological, and behavioral measures that are collected by means of digital devices that are portable, wearable, implantable, or digestible.” A few examples include a smartwatch photoplethysmography sensor that detects irregular pulse rate, accelerometry that measures sleep duration, and wearable digital technologies that track mood. 

During the last decade, the number of digital biomarkers has increased rapidly. To better understand them, digital biomarkers, same as traditional biomarkers, can be divided into seven categories based on the clinical goal they serve. These categories are: diagnostic, safety, response, monitoring, prognostic, risk, and predictive. 

For example, a diagnostic digital biomarker such as a wearable heart monitor detects heart arrhythmias. Whereas a predictive one such as a wearable sensor assessing gait predicts falls in patients with Parkinson’s disease. Considering that digital biomarkers use a completely different process to produce outcomes, they are different from traditional biomarkers. 

How are Digital Biomarkers Different from Traditional Ones?

While traditional biomarkers are well-integrated with the current clinical practice, their limited measurement over time makes their analytical complexity limited, leading to a snapshot view of a condition. In addition, they can be invasive, labor-intensive, and expensive. In contrast, digital biomarkers are less or non-invasive and more cost-effective. More importantly, digital biomarkers continuously measure health data, producing a contiguous and longitudinal view of the medical condition and patient in real-time in their natural environment. 

How is the Healthcare Industry Responding to Digital Biomarkers?

The differences between digital and traditional biomarkers and the potential of digital biomarkers in providing personalized care for patients and increasing efficiency of clinical trials have fueled the interest of digital health and pharma companies alike. As a result, more companies sign agreements and enter partnerships to expand their healthcare offerings through digital biomarkers.

  • Digital health companies and digital biomarkers

In December 2019, Diabeloop, a digital health company producing an autonomous diabetes management system for type 1 diabetes, announced a $31 M funding. More recently, in November 2021, this company partnered with Terumo corporation to expand its services in helping diabetic patients to manage their condition more effectively. Element science is another digital health company that started a partnership with several companies, including Deerfield Healthcare, and raised $145.6 M to complete clinical testing of its product, a wearable cardioverter defibrillator that detects and treats lethal heart arrhythmias. In May 2021, Mindstrong, a digital mental health company, that has developed digital biomarkers to assess brain function through individuals’ smartphone behavior, announced $100 M funding.

It is not only digital health companies that have a place in the digital biomarker landscape. Pharma companies have also been investing and forming partnerships in the field. The business focus of pharma companies is changing from a product-based to a more service-oriented model. Therefore, they are now more focused on improving patient experience and outcomes by combining drug therapy with digital health services. 

  • Pharma companies and digital biomarkers

Janssen Pharmaceuticals, one of the Janssen Pharmaceutical Companies of Johnson & Johnson, has been collaborating with Huma (formerly Medopad) to work on a digital biomarker for Alzheimer’s disease that provides remote automated evaluations for individuals at risk of Alzheimer’s disease. Roche has also partnered with Nuvoair to make its technology, a digital health platform for assessing lung function at home, accessible to individuals with cystic fibrosis. Biogen and Ad Scientiam have also started a scientific collaboration to develop innovative digital solutions/biomarkers in clinical research in neuroscience.

These are only a few examples of the numerous advances and partnerships that have been happening in the digital biomarker landscape. But why do digital health and pharma companies find digital biomarkers so attractive to invest millions of dollars in them?

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Why are Digital Biomarkers so Attractive?

Here are four key reasons:

1. Digital biomarkers allow for early diagnosis of health conditions and timely treatment.

Wearable technologies and smartphones measure health data continuously; thus, digital biomarkers can detect abnormalities much sooner than traditional ones, allowing for earlier treatment. For example, the app-connected wearable defibrillator by Element Science continuously monitors patients’ heart activities.

When the app detects life-threatening arrhythmias, it delivers an electrical shock to resume normal heart rhythm, preventing sudden cardiac death. 

Another example is Clarigent Health’s app that analyzes vocal characteristics to detect early indicators of suicidality and violence, allowing patients and clinicians to act early and prevent serious events before it is too late.

2. Digital biomarkers allow for personalized remote patient care and better self-management with lower costs.

The ability of smartphones and wearable technologies to measure health data continuously and to integrate data from different sources enables patients to get a better picture of their condition and make better health decisions. In addition, when this data is sent to the clinician, they can provide personalized care remotely. Since all these activities can be done remotely without visiting a clinician or a hospital, the cost reduces. For example, Glooko by Glooko company is a digital tool that syncs data from glucose meters, insulin pumps, Continuous Glucose Monitoring (CGM) devices, and logs meals and activity. Patients can use this data to better self-manage their diabetes, and the healthcare team can analyze the data to provide patients with personalized care remotely. 

3. Digital biomarkers leverage the current technology.

Portable smartphones, connected wearable devices, and mobile health apps are already part of people’s lives. As the daily usage of these devices is high and they already have inbuilt sensors (e.g. voice recorder and camera) to measure and record health data, digital biomarkers leverage these factors to improve clinical practice and patient care. For example, Bluestar by WellDoc is a digital health application that gathers data from blood glucose meters and fitness trackers. It provides real-time feedback to patients with diabetes to improve disease management over the long-term. Another example is FibriCheck, an app that works with both Fitbit and smartwatches, that detects heart arrhythmias and shares the results with the individual and the healthcare team to allow for early diagnosis and treatment.

4. Digital biomarkers increase efficiency in clinical trials.

Smartphones and wearable technologies provide objective and continuous digital biomarkers that improve the efficiency of clinical trials in collecting and analyzing data for drug development and patient monitoring.

For example, Koneksa Health, a digital biomarker company, has partnered with Novartis and Merck to remotely gather and analyze data for drug trials. Also, AiCure, an AI and data analytics company, has been collaborating with Syneos Health to improve adherence and patient engagement, enhancing the success of clinical trials.

What are the Opportunities Presented by Digital Biomarkers?

The above reasons and examples show that the potential of digital biomarkers is significant. In addition, the field of digital biomarkers is still quite young. Therefore, lots of opportunities exist for digital biomarkers across healthcare. Here are four of these opportunities. Digital biomarkers can be used for:

  • Personalized preventive care

Preventive care tailored to patients’ features and behavior creates an exciting opportunity for digital biomarkers. Digital technologies that monitor patients’ health data and provide feedback can enable early intervention and improve preventative care. For example, an AI-based digital app that monitors heart activity and integrates data from other activities can aid the prediction and prevention of cardiovascular events.

  • Disease management 

One of the golden opportunities for digital biomarkers lies in monitoring and managing outbreaks at a national level and disease self-management at the individual level. Using COVID19 as an example, digital biomarkers that can measure and analyze temperature, breathing patterns, and voice characteristics to detect infection can be used at hospitals or larger healthcare settings to manage the infection. In addition, the collected data can provide policymakers with a deeper insight into the trends and patterns of the outbreak, allowing for better predictions and managements. Such biomarkers can also help individuals detect infection earlier and self-isolation more effectively, minimizing the transfer of the infection. 

  • Risk evaluation

Monitoring health conditions throughout the course of the disease provides another exciting avenue for digital biomarkers. Monitoring biomarkers that can constantly assess patients and analyze their risk of progression or developing comorbidities enables clinicians to gain deeper insight into patient care. This would allow for early diagnosis and treatment of comorbidities and also identify patients at risk. For example, a digital biomarker that monitors and analyzes blood glucose, weight, activity, and diet in a diabetic patient over the long-term can evaluate the risk of comorbidities and detect individuals at risk, allowing for early risk management by adjusting treatment and lifestyle. 

  • Mental health conditions

The increasing awareness of mental health and the need to detect and manage mental illnesses early creates a great opportunity for digital biomarkers. Digital tools that monitor and assess individuals’ conditions can trigger early intervention before a serious event like suicide happens. In addition, these digital tools can connect the individual to support groups and available services in the community, providing patients with constant support. 

What are the Challenges in the Field of Digital Biomarkers?

Digital biomarkers collect data continuously; therefore, they can produce extensive complex data that may be challenging for data analytics and management. In addition, the devices vary, and individuals’ ways of wearing and using them also differ, leading to great variations affecting data quality and reliability. Adding to that, variations in healthcare settings in different areas and countries create a challenge for the standardization of digital biomarkers, which may affect their values. Finally, the complex coding and changing nature of machine learning algorithms may make the validation and interpretation of digital biomarkers challenging.

Digital biomarkers create an exciting field in healthcare to improve patient care and clinical research. So far, digital biomarkers have shown promising results. They have great potential, and many opportunities exist for developing objective and novel digital tools to improve clinical practice. However, there is still room for improving these biomarkers and addressing the challenges ahead.

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