Smartwatches Are Transforming Clinical Trials: Insights from Digital Primary Endpoints
July 8, 2025
The landscape of clinical research is continually evolving, with a growing emphasis on leveraging digital technologies to enhance efficiency and data quality. Among these innovations, wearable devices like the Apple Watch have emerged as promising tools for continuous and remote patient monitoring.
We recently analyzed the current application of smartwatches in clinical trials, focusing on their role in capturing digital primary endpoints across a variety of therapeutic areas. Here, I share some of our key findings, including major application areas as well as the benefits and challenges associated with their wider adoption in clinical research.
Digital primary endpoints
One way smartwatches are being used in clinical trials is to collect digital primary endpoints — sensor-generated data often collected outside a clinical setting.
To understand the potential impact of smartwatches in this context, we analyzed 87 completed or terminated clinical trials listed on ClinicalTrials.gov that used Apple Watch technology, examining key variables such as therapeutic focus, endpoint types, geographic distribution, and study design. Here is what we found:
Key Findings
- High completion rate: 93.1% of the trials were completed successfully.
- Top therapeutic areas: Cardiology led with 28.7% of studies, followed by neurology (21.8%) and oncology (11.5%).
- Common endpoints: ECG changes (18.4%), heart rate variability (12%), and oxygen saturation (10%) were the most frequently measured.
- Study design: Interventional trials dominated (64%), with high recruitment rates across the board.
- Geographic trends: North America hosted the majority of trials (55%), followed by Europe (30%).
Importantly, validation studies confirmed the diagnostic accuracy of these devices, supporting their potential for regulatory approval.
Cossio, M. & Gilardino, R. (2025, May 15). Leveraging Consumer-Grade Wearables in Clinical Trials: Insights From Digital Primary Endpoints [Conference presentation]. ISPOR 2025, Montreal, Canada.
Why wearables matter in clinical trials
In clinical trials, smartwatches offer several unique advantages:
- Continuous, remote monitoring: Smartwatches enable continuous, remote monitoring of patients, reducing the need for in-person visits and enhancing data collection.
- Scalability: Smartwatch use is ideal for decentralized or hybrid trials, where flexibility and patient engagement are key, enabling participation across wide geographies.
- Reduced costs: Smartwatches can also help reduce trial costs by requiring fewer site visits, enabling decentralized trials, providing real-time data collection and automated uploads, and so on.
- Improved patient adherence and engagement: Smartwatches often include reminders, notifications, and user-friendly interfaces that help patients stay compliant with treatment schedules, data input, and study protocols.
- Objective, high-frequency data: Smartwatches gather physiological metrics (e.g., heart rate, activity levels, sleep patterns) with high frequency and objectivity, reducing reliance on subjective self-reporting.
- Increased accessibility and inclusivity:
Smartwatches can broaden trial access for populations who may face barriers to travel or mobility, thereby enhancing demographic diversity and generalizability of trial findings.
The growing use of wearables and the future of clinical trials
The growing use of wearables in clinical trials signals a shift toward more scalable, cost-effective, and patient-friendly research models. However, challenges remain — particularly around technical reliability and patient adherence. Future research should focus on integrating wearables into value-based healthcare and global trial frameworks.
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Manuel Cossio
Director, Innovation and Strategic Consulting
Manuel Cossio is Director, Innovation and Strategic Consulting at Cytel. Manuel is an AI engineer with over a decade of experience in healthcare AI research and development. He currently leads the creation of generative AI solutions aimed at optimizing clinical trials, focusing on hierarchical multi-agent systems with multistage data governance and human-in-the-loop dynamic behavior control.
Manuel has an extensive research background with publications in computer vision, natural language processing, and genetic data analysis. He is a registered Key Opinion Leader at the Digital Medicine Society, a member of the ISPOR Community of Interest in AI, a Generative AI evaluator for the EU Commission, and an AI researcher at UB-UPC- Barcelona Supercomputing Center.
He holds an M.Sc. in Translational Medicine from Universitat de Barcelona, a Master of Engineering in AI from Universitat Politècnica de Catalunya, and a M.Sc. in Neuroscience from Universitat Autònoma de Barcelona.
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