Clinical Researcher—August 2025 (Volume 39, Issue 4)
SPECIAL FEATURE
Naresh Poondla, MBA, PhD; Justin Scott Brathwaite, MBA; Milan Sheth, MS
Enhancing Trial Results Through Digital Innovation
Digital biomarkers are derived from various mediums including wearables, smartphones, and connected medical devices. They are becoming invaluable tools that offer continuous, objective insights into a patient’s health in real-world settings. Unlike traditional clinical outcome assessments, which rely on intermittent and sometimes subjective clinic-based measurements, digital biomarkers enable a richer, more dynamic understanding of disease progression and treatment response.{1} In this article, we provide examples of how digital biomarkers are revolutionizing clinical trials, focusing on our shared experiences managing trials within the fields of neurology and oncology.
Revolutionizing Clinical Trials and Patient Monitoring: Lessons from Stroke Research
In stroke, clinical research teams use advanced remote monitoring tools—including wearable devices, telehealth platforms, and digital data capture systems—to continuously track a patient’s health outside traditional clinical settings. This not only reduces measurement bias but also better reflects that patient’s natural environments.{1} The results are improved detection of subtle neurological changes in real time and earlier interventions, which are vital to improving outcomes for various neurological conditions from stroke to cognitive decline.
We have also witnessed a shift toward decentralized and hybrid clinical trial models that enable patients to participate from the comfort of their homes, while still generating high-quality, real-world data (RWD). Electronic consent and secure data-sharing platforms have made research more efficient, inclusive, and scalable. These technologies reduce patient burden while enabling researchers to reach more diverse populations, ensuring studies reflect real-world settings.
Innovating Stroke Drug Development and Enhancing Patient Outcomes with Technology
Stroke trials now leverage cutting-edge technology to fundamentally transform drug development and improve patient outcomes. Clinical trial teams are integrating advanced digital platforms, artificial intelligence (AI), and RWD analytics to streamline every phase of the trial process—from protocol design to patient follow up.
In stroke trials, remote monitoring devices and wearable biosensors gather real-time data, enabling more accurate tracking of patient recovery and facilitating early interventions when needed. This enhances safety and efficiency while also enabling more personalized therapeutic approaches, allowing teams to track subtle neurological changes in real time, respond faster to early warning signs, and adapt care based on individual patient profiles.
By combining clinical biomarkers, imaging data, and patient-reported outcomes, researchers can personalize treatment strategies more precisely than ever before. Additionally, AI-driven tools are now being used to optimize patient selection, predict treatment responses, and identify subtle patterns that might otherwise be missed in traditional trials. These innovations are accelerating the ability to test, validate, and bring new therapies to patients faster.
What we, the authors, find most exciting is how technology is making research more inclusive by reducing the burden of site visits while offering remote participation options. Ultimately, this is the foundation of how smarter, patient-centric research is conducted and care is delivered. Therefore, we believe the future of precision medicine lies in the seamless integration of technology, RWD, and compassionate, evidence-driven care.
While the application of digital biomarkers in neurology highlights their transformative potential, their impact in oncology—a field defined by highly individualized treatment responses and complex patient journeys—is equally profound and illustrative of what is possible across therapeutic areas.
Examples of Digital Biomarkers in Oncology Clinical Trials
Digital biomarkers are transforming oncology clinical trials by providing a continuous, high-resolution view of patient health and treatment responses. While traditional approaches have relied on periodic imaging and laboratory tests, digital tools now offer a far richer and more dynamic understanding of each patient’s journey.{2,3}
Established digital biomarker strategies, such as wearable devices monitoring heart rate variability, sleep quality, and activity levels, have already reshaped how we assess treatment tolerance and functional status. When combined with electronic patient-reported outcome (ePRO) tools, these approaches capture daily symptom fluctuations—moving beyond static clinic visits and providing a real-world perspective of each patient’s experience.{4}
Drawing from our experiences supporting advanced oncology trials, we have seen these methods evolve into even more sophisticated, multidimensional approaches. For instance, initiatives are now integrating continuous physiologic and behavioral data with circulating tumor DNA dynamics, creating a composite picture of disease progression and systemic resilience. This integration supports adaptive dosing strategies and may allow clinicians to detect relapses earlier than they can through traditional imaging.{5}
Additionally, new efforts leverage smartphone-based cognitive assessments and voice analysis to detect subtle signs of cognitive impairment, often referred to as “chemo brain.” Patterns in app usage or texting behavior can further reveal early emotional distress or social withdrawal, prompting timely mental health interventions and tailored supportive care.
Another promising frontier is the exploration of the “digital microenvironment,” where contextual signals—such as light exposure, sleep-wake rhythms, and environmental noise—are captured using smart home devices. These data illuminate how lifestyle and environment influence immune function, fatigue, and treatment tolerance, guiding more personalized care strategies.
Importantly, real-time insights from digital biomarkers are strengthening patient-clinician partnerships. By sharing continuous quality-of-life and symptom data, patients become active participants in shared decision-making around treatment adjustments, transforming the patient’s lived experience into an essential component of clinical care and trial design. This empowers patients to receive more personalized, timely interventions, ultimately improving safety, enhancing treatment adherence, and supporting better overall clinical outcomes.
These innovations also enable decentralized and hybrid models, reducing logistical burdens and broadening access for diverse and underrepresented populations. Ultimately, integrating continuous digital monitoring, behavioral and psychosocial data, and multi-omics approaches signals a transformative shift toward a more precise, holistic, and patient-centered era of oncology research. By capturing the full spectrum of each patient’s physiologic, emotional, and environmental story, we move closer to realizing a future in which cancer care is not only scientifically rigorous but also deeply compassionate—and where improved outcomes reflect care that is truly tailored to each individual’s needs.
Digital Biomarkers are Transforming Evidence Generation
Digital health technologies are reshaping how evidence is generated in clinical research across multiple dimensions, including:
- From Intermittent to Continuous Monitoring: Traditional trials offer periodic snapshots of health. In contrast, digital biomarkers enable high-resolution, longitudinal data collection. For example, continuous glucose monitors offer real-time insights into glycemic patterns in diabetes trials.{6}
- From Clinic-Centric to Decentralized Trials: Mobile health tools allow for remote participation, shifting data collection into patients’ everyday environments. This approach enhances both convenience and real-world relevance.{7}
- Enhancing Data Robustness: While patient-reported outcomes remain vital, digital biomarkers provide continuous, objective data that capture daily symptom fluctuations, offering a more comprehensive view of disease impact.{8}
- Passive Data Collection: Many digital tools operate in the background, reducing participant burden and improving data completeness.{9}
Technological Integration Under ICH E6(R3): Shaping the Future of Clinical Trials
We previously highlighted how the recently updated International Council for Harmonization (ICH) E6(R3) guideline on Good Clinical Practice aims to enhance patient safety, optimize efficiency, and improve data integrity.{10} Through the lens of ICH E6(R3), there is a greater emphasis on flexibility, risk-based quality management, and integration of digital technologies, which seamlessly aligns with the capabilities of digital biomarkers; indeed, a central tenet of ICH E6(R3) is its encouragement of decentralized and hybrid trial designs.{11} Digital biomarkers facilitate this through wearables and mobile apps that gather continuous, real-world physiological and behavioral data. These tools reduce patient burden and broaden access to underrepresented populations, aligning with the guideline’s focus on patient centricity.
The guideline also supports risk-based quality management, moving beyond static documentation. Digital biomarkers can serve as critical-to-quality factors, offering real-time insights into patient safety and treatment efficacy. Abnormal trends or data anomalies can prompt immediate corrective actions, improving oversight and minimizing protocol deviations.
ICH E6(R3) further stresses data governance and security. Digital biomarkers produce vast volumes of sensitive, time-stamped data, necessitating rigorous cybersecurity measures and data lifecycle management. When well-managed, these data streams support auditability and traceability, reinforcing trial integrity.
In short, digital biomarkers are not optional in this evolving landscape—they are essential. Their real-time capabilities, objectivity, and adaptability help realize the goals of ICH E6(R3): trials that are more efficient, inclusive, and aligned with modern clinical practice.
Navigating the Potential Challenges of Digital Biomarkers
Although digital biomarkers hold transformative promise for clinical trials, several challenges remain that require careful attention and proactive mitigation, including in terms of how data quality and accuracy can vary across devices and settings. For instance, differences in sensor calibration, environmental factors, and user behavior could introduce variability or measurement errors.{12}
Moreover, algorithmic bias and generalizability also pose potential risks. Many digital biomarker algorithms are trained on limited demographic groups, potentially reducing accuracy in underrepresented populations.{13} Therefore, it is imperative to include diverse participants during algorithm development to help mitigate these biases.
Most importantly, issues persist with privacy and data security concerns. Digital biomarkers generate large volumes of sensitive personal health data, creating potential for misuse or breaches. Robust data governance frameworks, including encryption, anonymization, and adherence to regulatory expectations like the General Data Protection Regulation from the U.K. and the Health Insurance Portability and Accountability Act from the U.S., are critical to protect patient confidentiality and build trust.{3}
To the authors’ knowledge, there is currently no universal framework for validating or approving digital biomarkers as clinical endpoints, and this creates uncertainty for sponsors and clinicians. Collaborative efforts between industry, academia, and regulatory bodies are needed to develop clear guidelines for validation, approval, and integration into trial designs.
Conclusion: A New Standard for Clinical Research
Digital biomarkers are redefining clinical research by enabling real-time, patient-centered, and objective evidence generation. As regulatory standards such as ICH E6(R3) push the industry toward more flexible, decentralized, and risk-based models, digital biomarkers stand out as a transformative force.
By improving endpoint sensitivity, enabling proactive safety monitoring, and expanding access to diverse populations, digital biomarkers address long-standing challenges in trial design and execution. While hurdles remain—particularly around validation, standardization, and data governance—industry-wide collaboration promises steady progress.
Ultimately, digital biomarkers are poised to become regulatory-grade assets that enhance data integrity, drive innovation, and improve outcomes for patients and researchers alike. Their continued integration will be central to shaping the next generation of clinical trials.
References
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Naresh Poondla, PhD, MBA, is a Clinical Research Scientist at the Icahn School of Medicine at Mount Sinai.
Justin Scott Brathwaite, MBA, is a PhD student in Clinical Research at the University of Jamestown and a Senior Site Readiness and Regulatory Startup Specialist at Fortrea.
Milan Sheth, MS, is a Clinical Research Coordinator specializing in oncology trials at Houston Methodist Neal Cancer Center.
