▲ JNPMEDI SooYoung Kwak Senior PL, Gurum Shin Consultant
Modern medicine is advancing at an unprecedented pace through its convergence with digital technologies, creating a foundation for safer and more effective treatment options. Clinical research, in particular, stands at the forefront of this digital shift. Digital clinical trials go beyond simply eliminating paper; they actively utilize advanced technologies across the entire lifecycle of data collection, management, and analysis to maximize efficiency and accuracy.
Digital Clinical Trials and Data Management Innovation: Transparency as a Global Standard
The core of digital clinical trials lies in innovation in data management. With tools such as Electronic Data Capture (EDC), wearable devices, and remote monitoring systems, it has become possible to collect and analyze large amounts of data in real time. This not only accelerates clinical trial timelines and reduces costs, but also enables the capture of daily-life patient data that was previously difficult to measure—providing deeper clinical insight.
Today, data transparency is no longer optional; it has become a global standard demanded by regulators and medical experts worldwide. No matter how innovative the results, clinical trial data lacking transparency cannot be recognized. Internationally, digital clinical trials are discussed with core values such as enhancing patient-centeredness, improving efficiency in data collection and monitoring, and expanding accessibility.
For example, the ICH E6(R3) guideline encourages the proactive use of digital technologies in clinical trial design and execution, highlighting the importance of ensuring data quality and integrity.
Korea, too, established a leading position in digital healthcare regulation by enacting the Digital Medical Products Act in February 2024—effective from February 2025—as the first country in the world to do so. The Act defines digital medical devices as those incorporating advanced technologies such as AI, robotics, and ICT. Digital clinical trials can generate clinical evidence to support domestic regulatory approval of such devices, and transparency requirements for data generated in digital trials are enforced even more strictly under this legal framework.
Technological and Regulatory Changes for Ensuring Data Reliability
“To ensure data reliability, both technological and regulatory changes must occur simultaneously.”
On the technology side, digital tools can be applied directly to data collection.
In Decentralized Clinical Trials (DCTs), wearable devices such as smartwatches and smart patches collect biometric data—heart rate, activity levels, sleep patterns—in real time. Remote Patient Monitoring (RPM) systems automatically record and transmit data such as blood glucose and blood pressure. These technologies increase data accuracy and immediacy while minimizing manual documentation errors.
Blockchain technology can also be used to prevent tampering and maintain a transparent record of data generation, storage, and use—further strengthening data integrity.
On the regulatory side, guidance from national authorities is becoming increasingly important. Regulatory agencies must present new guidelines suited to digital clinical trial environments and establish concrete procedures and standards for ensuring data reliability.
In the U.S., the FDA has issued multiple guidelines related to the growth of digital health technologies. The Digital Health Center of Excellence (DHCoE), launched in 2020, supports the development and regulatory approval of digital health products. SaMD guidance provides evaluation standards for safety and effectiveness of software-based medical devices. 21 CFR Part 11 defines requirements for the validity of electronic records and signatures, establishing trust in electronic data used in digital clinical trials.
In Korea, the Digital Medical Products Act (effective February 2025) provides safety and quality standards for digital medical products across development, approval, manufacturing, distribution, and post-market management. The Act reflects the nature of software medical devices by simplifying approval pathways and including change management plan requirements for continuous updates—an important step in addressing the challenge of regulations failing to keep pace with rapidly evolving technologies.
Real-World Applications of Digital Clinical Trial Technologies
Digital technologies are increasingly used in real-world clinical trials.
One of the most widely known examples is Moderna’s COVID-19 vaccine (mRNA-1273). Moderna used decentralized clinical trial methods and adopted Medidata’s cloud-based clinical solutions to streamline research during the pandemic. EDC enabled rapid data capture, eCOA supported patient-centered outcome assessments, and centralized monitoring tools helped accelerate enrollment and site oversight.
As a result, Moderna completed vaccine development in a remarkably short period, demonstrating how digital solutions can dramatically improve the speed and efficiency of drug development.
GSK’s PARADE study is another example of DCT implementation. It used smartphones to remotely collect physical function data from patients with rheumatoid arthritis, reducing participant burden and improving trial duration and cost efficiency.
FDA’s PCCP and Korea’s Change Management Requirements
The FDA’s Predetermined Change Control Plan (PCCP) is a framework for managing updates to AI/ML-based SaMD. Finalized in 2024, it acknowledges that machine learning–based SaMD may continue to learn and improve after market release and allows predefined updates to be implemented without undergoing a full approval process for each change.
One representative example is the Caption Interpretation Automated Ejection Fraction Software(cleared September 2022). This AI-driven imaging analysis tool continuously updates its algorithms to improve accuracy, and the FDA allows this through the PCCP framework. The case demonstrates how PCCP can provide practical regulatory efficiency for AI-based diagnostic software.
In Korea, the enforcement regulations of the Digital Medical Products Act include a change management plan similar in concept. Article 7 specifies the submission of a change management plan, allowing minor updates—such as changes in training data or bug fixes—without requiring additional approval.
However, Korea’s change management framework differs from the FDA’s PCCP in several ways. PCCP demands detailed, data-driven plans for predictable updates—what data will be added, how algorithms will be improved, and how these changes will affect performance. Clear validation criteria must also be provided.
By contrast, Korea’s current framework provides fewer specifics regarding acceptable types of changes and their evaluation. This lack of clarity can reduce predictability for companies and make consistent regulatory review more difficult.
Recommendations for Strengthening Korea’s Regulatory Framework
Korea’s FDA-equivalent authority has taken important steps by enacting the Digital Medical Products Act. To further enhance its impact and accelerate innovation in digital healthcare, the following improvements should be considered—especially given the continuously evolving nature of AI medical devices:
1. Clear criteria for modifying machine learning training data
- Guidelines should define when and how new training data may be added, and how changes should be assessed for performance impact.
2. Explicit standards for algorithm updates
- Minor updates should be differentiated from major changes requiring additional review.
3. Detailed validation procedures
- Clear methodologies for re-verifying safety and effectiveness after updates should be provided.
4. Stronger transparency obligations
- Companies should be required to clearly communicate what changes were made and how they affect device performance.
Benefits of Improved Data Reliability in Digital Clinical Trials
Enhancing regulatory clarity and data reliability will unlock significant benefits:
- Acceleration of precision medicine, allowing ML-driven tools to provide more personalized diagnostics and treatments
- Improved access for rare disease and hard-to-enroll patient populations, enabling efficient digital trials without geographical limitations
- More effective management of chronic diseases, with real-time monitoring enabling proactive intervention and reducing healthcare burden
Digital clinical trials require more than technological advancement alone. When paired with well-defined, practical regulatory frameworks, Korea’s proactive regulatory efforts will help realize the full potential of digital healthcare and support continuous innovation in the medical field.
▲ JNPMEDI SooYoung Kwak Senior PL, Gurum Shin Consultant
Modern medicine is advancing at an unprecedented pace through its convergence with digital technologies, creating a foundation for safer and more effective treatment options. Clinical research, in particular, stands at the forefront of this digital shift. Digital clinical trials go beyond simply eliminating paper; they actively utilize advanced technologies across the entire lifecycle of data collection, management, and analysis to maximize efficiency and accuracy.
Digital Clinical Trials and Data Management Innovation: Transparency as a Global Standard
The core of digital clinical trials lies in innovation in data management. With tools such as Electronic Data Capture (EDC), wearable devices, and remote monitoring systems, it has become possible to collect and analyze large amounts of data in real time. This not only accelerates clinical trial timelines and reduces costs, but also enables the capture of daily-life patient data that was previously difficult to measure—providing deeper clinical insight.
Today, data transparency is no longer optional; it has become a global standard demanded by regulators and medical experts worldwide. No matter how innovative the results, clinical trial data lacking transparency cannot be recognized. Internationally, digital clinical trials are discussed with core values such as enhancing patient-centeredness, improving efficiency in data collection and monitoring, and expanding accessibility.
For example, the ICH E6(R3) guideline encourages the proactive use of digital technologies in clinical trial design and execution, highlighting the importance of ensuring data quality and integrity.
Korea, too, established a leading position in digital healthcare regulation by enacting the Digital Medical Products Act in February 2024—effective from February 2025—as the first country in the world to do so. The Act defines digital medical devices as those incorporating advanced technologies such as AI, robotics, and ICT. Digital clinical trials can generate clinical evidence to support domestic regulatory approval of such devices, and transparency requirements for data generated in digital trials are enforced even more strictly under this legal framework.
Technological and Regulatory Changes for Ensuring Data Reliability
“To ensure data reliability, both technological and regulatory changes must occur simultaneously.”
On the technology side, digital tools can be applied directly to data collection.
In Decentralized Clinical Trials (DCTs), wearable devices such as smartwatches and smart patches collect biometric data—heart rate, activity levels, sleep patterns—in real time. Remote Patient Monitoring (RPM) systems automatically record and transmit data such as blood glucose and blood pressure. These technologies increase data accuracy and immediacy while minimizing manual documentation errors.
Blockchain technology can also be used to prevent tampering and maintain a transparent record of data generation, storage, and use—further strengthening data integrity.
On the regulatory side, guidance from national authorities is becoming increasingly important. Regulatory agencies must present new guidelines suited to digital clinical trial environments and establish concrete procedures and standards for ensuring data reliability.
In the U.S., the FDA has issued multiple guidelines related to the growth of digital health technologies. The Digital Health Center of Excellence (DHCoE), launched in 2020, supports the development and regulatory approval of digital health products. SaMD guidance provides evaluation standards for safety and effectiveness of software-based medical devices. 21 CFR Part 11 defines requirements for the validity of electronic records and signatures, establishing trust in electronic data used in digital clinical trials.
In Korea, the Digital Medical Products Act (effective February 2025) provides safety and quality standards for digital medical products across development, approval, manufacturing, distribution, and post-market management. The Act reflects the nature of software medical devices by simplifying approval pathways and including change management plan requirements for continuous updates—an important step in addressing the challenge of regulations failing to keep pace with rapidly evolving technologies.
Real-World Applications of Digital Clinical Trial Technologies
Digital technologies are increasingly used in real-world clinical trials.
One of the most widely known examples is Moderna’s COVID-19 vaccine (mRNA-1273). Moderna used decentralized clinical trial methods and adopted Medidata’s cloud-based clinical solutions to streamline research during the pandemic. EDC enabled rapid data capture, eCOA supported patient-centered outcome assessments, and centralized monitoring tools helped accelerate enrollment and site oversight.
As a result, Moderna completed vaccine development in a remarkably short period, demonstrating how digital solutions can dramatically improve the speed and efficiency of drug development.
GSK’s PARADE study is another example of DCT implementation. It used smartphones to remotely collect physical function data from patients with rheumatoid arthritis, reducing participant burden and improving trial duration and cost efficiency.
FDA’s PCCP and Korea’s Change Management Requirements
The FDA’s Predetermined Change Control Plan (PCCP) is a framework for managing updates to AI/ML-based SaMD. Finalized in 2024, it acknowledges that machine learning–based SaMD may continue to learn and improve after market release and allows predefined updates to be implemented without undergoing a full approval process for each change.
One representative example is the Caption Interpretation Automated Ejection Fraction Software(cleared September 2022). This AI-driven imaging analysis tool continuously updates its algorithms to improve accuracy, and the FDA allows this through the PCCP framework. The case demonstrates how PCCP can provide practical regulatory efficiency for AI-based diagnostic software.
In Korea, the enforcement regulations of the Digital Medical Products Act include a change management plan similar in concept. Article 7 specifies the submission of a change management plan, allowing minor updates—such as changes in training data or bug fixes—without requiring additional approval.
However, Korea’s change management framework differs from the FDA’s PCCP in several ways. PCCP demands detailed, data-driven plans for predictable updates—what data will be added, how algorithms will be improved, and how these changes will affect performance. Clear validation criteria must also be provided.
By contrast, Korea’s current framework provides fewer specifics regarding acceptable types of changes and their evaluation. This lack of clarity can reduce predictability for companies and make consistent regulatory review more difficult.
Recommendations for Strengthening Korea’s Regulatory Framework
Korea’s FDA-equivalent authority has taken important steps by enacting the Digital Medical Products Act. To further enhance its impact and accelerate innovation in digital healthcare, the following improvements should be considered—especially given the continuously evolving nature of AI medical devices:
1. Clear criteria for modifying machine learning training data
- Guidelines should define when and how new training data may be added, and how changes should be assessed for performance impact.
2. Explicit standards for algorithm updates
- Minor updates should be differentiated from major changes requiring additional review.
3. Detailed validation procedures
- Clear methodologies for re-verifying safety and effectiveness after updates should be provided.
4. Stronger transparency obligations
- Companies should be required to clearly communicate what changes were made and how they affect device performance.
Benefits of Improved Data Reliability in Digital Clinical Trials
Enhancing regulatory clarity and data reliability will unlock significant benefits:
- Acceleration of precision medicine, allowing ML-driven tools to provide more personalized diagnostics and treatments
- Improved access for rare disease and hard-to-enroll patient populations, enabling efficient digital trials without geographical limitations
- More effective management of chronic diseases, with real-time monitoring enabling proactive intervention and reducing healthcare burden
Digital clinical trials require more than technological advancement alone. When paired with well-defined, practical regulatory frameworks, Korea’s proactive regulatory efforts will help realize the full potential of digital healthcare and support continuous innovation in the medical field.