In clinical research, data decides everything. The quality and accuracy of information gathered during remote patient monitoring (RPM) clinical trials shape how well researchers understand the safety and efficacy of new drugs and treatments. Traditional data collection has long struggled with recall bias, inconsistent self-reporting, and a lack of real-world context.
Connected devices and wearable technology are changing that. Remote tools now let researchers capture richer, more objective data streams as they happen. From smartwatches and activity trackers to continuous glucose monitors and smart inhalers, connected devices open a window into the daily lives of trial participants.
This article explains how connected devices and wearable technologies improve remote patient monitoring clinical trials, what recent research shows, and how updated regulatory guidance supports their use.
What Are Remote Patient Monitoring Clinical Trials?
Remote patient monitoring clinical trials use connected medical devices to collect participant health data outside a traditional research site. Instead of relying only on scheduled clinic visits, study teams gather vital signs, activity, and symptoms from participants at home. This model sits at the center of what the FDA now calls trials with decentralized elements.
In September 2024, the FDA issued its final guidance, Conducting Clinical Trials With Decentralized Elements. The agency moved away from labeling a study as either traditional or decentralized. It now focuses on the specific decentralized elements a trial uses, such as telehealth visits, digital health technologies, and direct-to-participant shipping. This shift makes room for remote patient monitoring in nearly any study design.
Benefits of Connected Devices in Remote Patient Monitoring Clinical Trials
How exactly do remote patient monitoring technologies improve trial data and open new research frontiers? Connected devices in clinical trials can track many metrics at once, including activity levels, sleep patterns, heart rate, glucose levels, medication use, and reported symptoms. This multidimensional view paints a fuller picture than intermittent reports or infrequent clinic visits.
A large analysis in Nature Reviews Drug Discovery reviewed 1,021 interventional trials registered between 2001 and 2025 that built wearable-derived data into their protocols. The trend is clear: sponsors increasingly treat wearable data as a core endpoint, not an add-on.
The sections below outline the main benefits of using RPM in clinical trials.
Richer Data Streams
Connected devices enable continuous monitoring 24 hours a day, showing how a participant’s condition shifts over time. This data is objective, which removes the recall bias and inconsistency of self-reported information. Researchers see actual behaviors and physiological changes rather than a participant’s memory of them.
These remote monitoring systems have been well studied in cancer patients undergoing standard chemotherapy. A study in The Oncologist found that many oncology researchers had limited experience with remote technologies before the COVID-19 pandemic. While 75% of respondents had used telemedicine, RPM, or both for remote care, 62% had never provided remote care to trial patients before the pandemic. Adoption has grown quickly since.
Greater Accuracy
Because participants follow their normal routines while using connected devices, researchers can study how therapies perform in real-world settings rather than an artificial clinical environment. A participant’s natural surroundings remove factors such as white coat syndrome, which can distort blood pressure readings taken in a clinic.
Passive, non-invasive data collection also reduces participant burden. Lower burden tends to improve compliance, which strengthens the reliability of the dataset.
Real-World Context and Participant Experience
Joining a trial can overwhelm patients already living with the physical and emotional weight of a disease. In cancer research, remote patient monitoring reduces the load on both sites and participants. Remote data capture cuts the number of required site visits, which eases logistical barriers.
Lower barriers help recruitment and retention. They also make trials more accessible to rural, older, and underserved populations that site-only studies often miss. In a real-world study conducted in 2025, Johnson & Johnson asked cancer patients to use RPM devices to capture vital signs in the days after treatment, when close monitoring matters most.
How AI Strengthens Remote Patient Monitoring Clinical Trials
Continuous data capture creates a new problem: volume. A single wearable can generate thousands of data points per participant, and study teams cannot review all of it manually. Artificial intelligence helps close that gap.
AI-driven platforms sift through incoming data and surface the readings that need attention. This lets study teams focus on genuine safety signals instead of scrolling through normal readings. Used well, AI supports faster and safer oversight without adding staff.
A few ways AI adds value in remote patient monitoring clinical trials include:
- Signal detection: Algorithms flag physiological changes that may indicate an adverse event, prompting timely review.
- Compliance monitoring: AI identifies participants who stop transmitting data or miss doses, allowing early outreach.
- Digital biomarkers: Machine learning converts raw sensor data into validated measures, such as mobility decline or arrhythmia frequency.
- Predictive insight: Historical trends help teams anticipate risk before a participant reports symptoms.
Regulatory Support for Remote Patient Monitoring Clinical Trials
Regulators now treat RPM as a recognized method of data capture. The FDA’s 2024 final guidance confirms that data from participant-owned devices, often called bring your own device (BYOD), is acceptable for regulatory review. The guidance also states that participants who lack a protocol-specified device should not be excluded, and sponsors should provide one so participation stays accessible.
Internationally, the updated ICH E6(R3) Good Clinical Practice guideline modernizes trial oversight and supports risk-based monitoring and digital endpoints. Together, these frameworks give sponsors a clearer path to build remote patient monitoring into study protocols with confidence.
Best Practices for Using RPM in Clinical Trials
Teams planning to add connected devices to a study can strengthen results by following a few principles:
- Match the device to the endpoint. Choose sensors that measure what the protocol actually needs, not the widest possible dataset.
- Plan for data volume early. Decide how AI or analytics tools will filter readings before the trial begins.
- Provide devices when needed. Offer provisioned hardware so participants without their own technology can still take part.
- Validate digital biomarkers. Confirm that sensor-derived measures are accurate and reproducible before relying on them.
- Build in participant support. Give clear training and a point of contact so participants can resolve device issues quickly.
Understanding Remote Patient Monitoring Clinical Trials
Connected devices make remote patient monitoring clinical trials more informative and more efficient. With richer flows of objective data, researchers can draw more reliable conclusions about the safety and effectiveness of new drugs and treatments. Updated FDA and ICH guidance now gives sponsors a clear framework to capture that data remotely, while AI helps teams manage the scale. Remote patient monitoring is connecting the future of clinical research to the real world where patients actually live.
Tenovi works exclusively with companies that offer remote patient monitoring to healthcare providers, including RPM software companies, chronic care management companies, and telehealth platforms. Our cellular-connected, no sync, no app devices transmit patient data automatically through the Tenovi Gateway, giving research and care partners a reliable real-world data stream. Book your free demo and consultation today.
