Decentralized Clinical Trials (DCTs) are pioneering a shift towards a more patient-centric approach in clinical research by leveraging the Internet of Things (IoT) and wearables technologies. These advancements facilitate real-time monitoring and data collection directly from the trial participants, rendering a seamless and interactive trial experience. However, it comes with risks that can critically impact a clinical trial. This piece delineates the potential risks highlighted by the FDA, emphasizes the necessity for Software as a Medical Device (SAMD) validation, and explores risk mitigation strategies focusing on an integrated data repository for enhanced data monitoring.

Risks of Wearables as outlined by the FDA in DCT Guidance:

The FDA’s guidance on DCTs highlights several risks associated with integrating wearables. The primary focal points of concern are data privacy, security, and integrity.

  • Data Privacy: Ensuring data privacy is collected remotely in a decentralized setup is paramount.
  • Data Security: The risk of data manipulation or loss during transmission poses significant challenges.
  • Data Integrity: Interoperability issues among various devices and platforms could lead to data inconsistencies or breaches.

Imagine a scenario where a DCT aimed at monitoring blood sugar levels in diabetics, where due to lax security measures, the data transmitted from smart glucose monitors could be intercepted or manipulated by unauthorized entities or hackers. This poses a grave risk to patient privacy and could lead to inaccurate data collection. If not managed properly, such a breach could result in erroneous conclusions being drawn from the trial, ultimately compromising the safety and effectiveness of the interventions being studied. This scenario underscores the imperative need for robust security measures to ensure the integrity and confidentiality of the data collected remotely.

The Importance of SAMD and Sponsor Validation in DCTs:

Validation of Software as a Medical Device (SAMD) extends beyond mere device functionality to the software, enabling data collection, transmission, and analysis.

  • Validation Process: The software driving medical devices must undergo rigorous validation to ensure accuracy and secure data transmission.
  • Reliability and Security: SAMD validation is crucial for ensuring the reliability and security of data derived from wearables in clinical trials.

For instance, imagine a scenario where a digital health startup developed an app, without undergoing SAMD validation, was used in a decentralized clinical trial. The app might malfunction or deliver inaccurate readings, failing to transmit data to healthcare providers securely. Consequently, healthcare providers could act on incorrect information, endangering patient safety. Furthermore, the lack of accurate and reliable data could lead to erroneous conclusions about the efficacy or safety of the studied interventions, thereby compromising the integrity of the trial results. This could result in significant delays in the development timelines, financial losses, and even legal liabilities for the sponsors. Hence, employing a non-SAMD-validated device could jeopardize the entire study, underlining the critical importance of SAMD validation in ensuring the accuracy, reliability, and security of data collected through digital means in DCTs.

If SAMD is not available, it is recommended that sponsors conduct a thorough app or device validation to ensure data reliability, accuracy, and security.

Mitigating DCTs Risks through Strategic Integration:

The FDA guidance outlines a robust framework for risk mitigation, highlighting the creation of an integrated data repository, among other strategies.

  • Integrated Data Repository: Centralizing data monitoring from various wearable devices to ensure data integrity, security, and privacy.
  • Real-Time Monitoring: Implement real-time monitoring with alert systems to identify and address potential issues promptly.
  • User Training: Training users on device usage, data privacy protocols, and real-time monitoring to ensure secure and accurate data collection and transmission.

Imagine you’re running a cardiovascular study, where smartwatches and blood pressure monitors are employed to collect participants’ heart rate and blood pressure data. All the collected data is directed to an integrated data repository. You built a backend system with algorithms to filter out noise from the data for more accurate real-time monitoring. This setup contains useful visualizations that identify abnormal readings promptly, triggering immediate notifications to study staff. Participants are trained on using these devices and data privacy, ensuring accurate data collection. Through this setup, despite the challenges posed by data noise from multiple sources, the study provides clearer insights into cardiovascular health with meaningful data analysis for both sponsors and investigators while also protecting patient safety and data integrity.


Integrating IoT and wearables in decentralized clinical trials is a monumental stride towards a more patient-centric clinical research paradigm. However, it comes with a set of challenges that necessitate a robust framework for risk mitigation. The FDA’s guidance offers a solid foundation, while the concept of SAMD and sponsor validation adds another layer of assurance for data reliability and security. Developing an integrated data repository further fortifies the data monitoring process, ensuring a secure, efficient, and streamlined data flow from various devices to the researchers. As the realm of DCTs continues to expand, adeptly navigating the risks while harnessing the potential of IoT and wearables will be indispensable for successful future clinical trials.


[1] FDA Guidance Software as a Medical Device (SAMD): Clinical Evaluation

[2] FDA Guidance on Decentralized Clinical Trials for Drugs, Biological Products, and Devices

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Moe Alsumidaie Chief Editor
Moe Alsumidaie is Chief Editor of The Clinical Trial Vanguard. Moe holds decades of experience in the clinical trials industry. Moe also serves as Head of Research at CliniBiz and Chief Data Scientist at Annex Clinical Corporation.