Digital Biomarkers and Wearables: Transforming Clinical Trial Data Collection

The Wrist Is the New Clinic: Why Digital Biomarkers Matter Now

Picture the moment a patient walks into a trial site. They have driven an hour, waited in a lobby, and are now asked to walk down a corridor for six minutes or rate their fatigue over the past two weeks from memory. The data recorded that afternoon will help determine whether a therapy worth billions reaches the market. Yet everyone in the room knows that a single visit captures only a sliver of the patient's reality, colored by a good night's sleep, a bad commute, or the simple pressure of being observed.

This is the quiet weakness at the heart of traditional clinical development. Many of the endpoints used to approve medicines rely on infrequent, clinic-based assessments and subjective recall. They are noisy, they burden patients, and they often miss the very changes that matter most in daily life.

Digital biomarkers offer a fundamentally different lens. Captured continuously through wearable devices, connected sensors and smartphones, they convert physiological and behavioral signals into objective, quantifiable measures of health. For the American pharmaceutical industry, operating in the world's largest and most competitive drug market, this is not a peripheral innovation. It is a structural change in how clinical evidence is generated, and leadership teams that understand it early will shape the standards that others follow.

Beyond the Clinic Snapshot: How Wearables Capture the Patient's Real Life

The appeal of wearables lies in their ability to observe patients where disease is actually experienced: at home, at work, and through the night. A wrist-worn accelerometer can track gait, activity and tremor across weeks. Patches can monitor heart rhythm, respiratory rate and skin temperature. Smartphones can measure speech patterns, typing speed and cognitive performance through brief, game-like tasks. Smart rings and bed sensors can quantify sleep quality with a granularity no sleep diary could match.

The result is a shift from episodic measurement to continuous observation. Instead of a handful of data points per patient across a trial, sponsors can collect thousands, revealing trends, fluctuations and responses to treatment that would otherwise remain invisible. In conditions such as Parkinson's disease, heart failure, multiple sclerosis, chronic pain and depression, where symptoms vary day to day, this richer picture can be the difference between detecting a meaningful benefit and missing it entirely.

Equally important is what these measures represent. Regulators, physicians and payers increasingly ask whether a therapy helps patients function better in their everyday lives. Wearable-derived measures of mobility, sleep or activity speak directly to that question in a way that laboratory values and clinic scales often cannot.

From Steps to Signals: Building Digital Biomarkers That Regulators Trust

Not every number generated by a wearable is a digital biomarker. Step counts on a consumer fitness tracker are interesting; a validated measure that reliably reflects disease progression or treatment response is something else entirely. The journey from raw sensor data to a regulatory-grade endpoint requires disciplined scientific work.

That work typically unfolds in layers. Verification confirms that the device accurately measures what it claims to measure, such as acceleration or heart rate. Analytical validation demonstrates that the algorithm converting raw signals into a metric performs consistently and correctly. Clinical validation establishes that the resulting measure meaningfully reflects a clinical state or outcome in the intended patient population. Above all of this sits the question of clinical meaningfulness: does a change in the measure matter to patients?

US regulators have signaled clear openness to this evolution. Federal guidance finalized in late 2023 set out expectations for using digital health technologies to acquire data remotely in clinical investigations, covering device selection, verification and validation, data integrity and patient usability. The message to sponsors is encouraging but demanding: digital endpoints are welcome, provided the evidence behind them is as rigorous as for any traditional measure. Early engagement with regulators on the context of use remains one of the most valuable investments a sponsor can make.

The Boardroom Equation: What Wearable Data Means for Cost, Speed and Statistical Power

For executives, the strategic value of digital biomarkers comes down to economics and probability of success. Because continuous measures are often more sensitive and less variable than episodic assessments, they can detect treatment effects with fewer patients or in shorter timeframes. In an environment where late-stage trials can cost hundreds of millions of dollars, even modest reductions in sample size or duration translate into substantial savings and earlier market entry.

Wearables also reduce the operational weight of trials. Fewer site visits mean lower site costs, less travel for patients and greater flexibility in study design. Remote monitoring supports decentralized and hybrid trial models, allowing sponsors to recruit beyond the narrow catchment areas of major academic medical centers.

There is a portfolio dimension too. Digital measures applied in early-phase studies can provide sharper signals of activity, helping leadership teams make faster, better-informed decisions about which assets to advance. And as payers demand evidence of real-world value, wearable data collected during trials can form the foundation for post-approval evidence generation, strengthening market access negotiations and differentiation in crowded therapeutic categories.

Patients as Partners: Wearables, Diversity and the Retention Dividend

One of the most persistent criticisms of American clinical research is that trial populations fail to reflect the patients who will ultimately use the medicines. Geography, transportation, work schedules and caregiving responsibilities all limit who can participate in studies that demand frequent site visits. Rural communities and lower-income patients are routinely underrepresented.

Wearable-enabled remote data collection can help break down these barriers. When much of the measurement happens at home, participation becomes feasible for patients who live hours from a research center or who cannot take repeated days off work. This aligns directly with growing federal expectations for diversity action plans in late-stage trials and with the ethical imperative to generate evidence that applies to all patients.

Retention benefits as well. Dropout is a costly and chronic problem, and every lost participant weakens the statistical integrity of a study. Trials that respect patients' time and reduce travel burden tend to keep them engaged. Thoughtful design matters here: devices must be comfortable, intuitive and unobtrusive, and patients should understand why their data matters. Treating participants as partners rather than data sources is not only good ethics but good business.

Case Study: The Ankle Sensor That Redefined a Pivotal Trial Endpoint

Few examples illustrate the potential of digital biomarkers more clearly than recent progress in Duchenne muscular dystrophy, a rare and progressive genetic disease that primarily affects young boys and steadily erodes their ability to walk.

For years, the standard measure of ambulatory function in Duchenne trials was the six-minute walk test, performed in a clinic under supervision. The test had well-known limitations. A child's performance on a single day could swing with motivation, fatigue, mood or simple unfamiliarity with the hospital setting. The resulting variability meant trials needed larger populations and longer durations to detect a treatment effect, a serious problem in a rare disease with a limited pool of eligible patients.

A team of researchers and clinicians pursued a different approach. Patients wore small sensors on their ankles during normal daily life over extended periods, allowing continuous measurement of how they actually moved at home, at school and at play. From this data, investigators derived a measure known as stride velocity 95th centile, essentially reflecting the speed of a patient's fastest strides during everyday activity. Because it captured peak real-world performance across many days rather than one supervised test, the measure proved more stable and better reflected the child's true functional capacity.

The supporting evidence was built step by step: device accuracy, algorithm performance, correlation with established clinical measures, sensitivity to change over time and relevance to patients and families. In 2019, a major regulator accepted the measure as a secondary endpoint in Duchenne trials. In 2023, it was qualified as a primary endpoint, widely recognized as the first time a wearable-derived digital measure had reached that status for pivotal studies in the eyes of a leading regulatory authority.

For American pharmaceutical leaders, the lessons are striking. A small, inexpensive sensor, paired with rigorous science and patience, changed what counts as evidence in an entire disease area. It reduced burden on young patients, offered a more faithful picture of their daily lives, and created a pathway to more efficient trials in a population where every participant counts. The case shows that regulatory acceptance of digital biomarkers is not a distant aspiration; it is achievable today for sponsors willing to invest in the validation work.

Validation, Privacy and Data Deluge: The Hard Truths of Wearable-Driven Trials
The opportunity is real, but so are the obstacles, and leadership teams that underestimate them risk costly setbacks.

Data volume is the first challenge. Continuous sensors generate enormous streams of information, and raw data is not insight. Sponsors need robust infrastructure to ingest, clean, store and analyze these datasets, along with clear plans for handling missing data when patients forget to wear or charge their devices. Without pre-specified analytical strategies, digital endpoints can create more confusion than clarity.

Device and algorithm variability is the second. Hardware generations change rapidly, firmware updates can alter outputs, and algorithms developed in one population may not perform equally well in another. Locking down device versions and documenting algorithm performance across diverse groups, including variations in skin tone, body size and age, is essential to avoid bias and protect data integrity.

Privacy and cybersecurity form the third. Wearables collect highly personal information, sometimes including location and behavior patterns. Compliance with HIPAA and an increasingly complex patchwork of state privacy laws demands careful attention to consent, data minimization and secure transmission. A single breach could damage patient trust and corporate reputation far beyond the trial itself.

Finally, there is the organizational gap. Digital biomarker programs sit at the intersection of clinical development, data science, engineering, regulatory affairs and patient engagement. Few companies have historically organized themselves to work this way, and success depends on breaking down functional silos.

Building the Digital Biomarker Enterprise: Leadership Moves That Matter Now

The companies pulling ahead are treating digital biomarkers as an enterprise capability rather than a series of isolated pilots. That begins with strategic focus: identifying the therapeutic areas where continuous measurement offers the greatest advantage, such as neurology, cardiometabolic disease, respiratory conditions and psychiatry, and committing to sustained investment there rather than scattering small experiments across the portfolio.

It continues with talent. Data scientists, biomedical engineers and digital health specialists must work alongside clinicians and statisticians from the earliest stages of program design, not be brought in after protocols are written. Precompetitive collaboration also has a role to play. Validating a new digital measure is expensive and time-consuming, and shared frameworks across sponsors, academic researchers and patient communities can accelerate acceptance for everyone.

Most importantly, it requires leadership conviction. Digital endpoints often demand upfront investment and a willingness to run them alongside traditional measures before they can stand alone. Executives who view that investment as building long-term competitive advantage, rather than as an experimental cost, will be the ones who define the next generation of clinical evidence.

Conclusion: Measuring What Truly Matters in the Age of Wearables

Clinical development has always been limited by what it could measure. For most of the industry's history, that meant brief, controlled observations in clinical settings. Digital biomarkers and wearables remove that constraint, offering a continuous, objective and patient-centered view of how therapies change lives.

For American pharmaceutical leaders, the implications reach well beyond trial operations. More sensitive endpoints can mean smaller and faster studies. Remote measurement can broaden participation and strengthen retention. Real-world functional data can sharpen the value story for payers and physicians. The barriers of validation, privacy and organizational readiness are significant, but the Duchenne experience shows they can be overcome.

The question facing the boardroom is no longer whether digital biomarkers will reshape clinical evidence, but whether their organization will help lead that change or follow standards set by others. The patients are already wearing the technology. The opportunity now is to listen to what it is telling us.