Data management in digital clinical investigations

In the digital era, data management in clinical investigations of medical devices and performance testing is becoming increasingly important.

With the integration of sensor-based data and the use of digital technologies, new challenges arise, but also opportunities for efficient and high-quality data management. Regulatory authorities such as the EMA (including the MDCG) and FDA have published guidelines in recent years to provide guidance on the use of digital technologies.

Importance of data management

Data management is a central component of clinical investigations as it ensures the integrity, reliability and robustness of the data collected. It includes processes such as data collection, processing, storage, transfer and archiving. Effective data management is critical for compliance with regulatory requirements, ensuring participant safety and the validity of study results.

Data Management Plan : The roadmap for effective data management

The data management plan (DMP) is an essential document that defines the strategy and processes for data management in a clinical investigation. It is prepared prior to the start of the trial and should cover the following aspects:

• Data collection: describing the methods and systems for collecting study data, including electronic data capture (EDC) systems, sensor-based appliances and mobile apps.
• Data transmission and storage: Definition of secure procedures for the transmission and storage of data, taking data protection into account.
• Data quality assurance: Processes to ensure data quality, such as validation rules, security data reconciliation and data cleansing.
• Data security and audit trail: Measures to protect data integrity, including user management, security measures and audit trails in accordance with EMA/226170/2021.
• Data management systems: Description of the EDC systems, sensor-based appliances and other digital technologies used, as well as their validation and qualification.
• Responsibilities: Definition of the roles and responsibilities of all parties involved in data management.

Regulatory standards for data management

Regulations (EU) 2017/745 and 2017/746 and ISO 14155 emphasise the need for robust data management in clinical investigations of medical devices and performance trials. The EMA guidelines EMA/226170/2021 and EMA/INS/GCP/454280/2010 set out specific requirements for the validation and qualification of computerised systems and the assurance of data integrity.

Since 2023, the Food and Drug Administration (FDA) has also published guidance. In addition, other regulations, such as the ethical principles of the Declaration of Helsinki and data protection regulations, must be observed to ensure the protection of participants' personal data and compliance with informed consent.

Why digital data management is superior to traditional data management

Advantages of digital data management:

• Cost efficiency: digital data collection and processing enable faster and more accurate data collection and analysis.
• Improved data quality: Validation rules and real-time monitoring help to improve data quality.
• Increased transparency and traceability: Digital systems increase transparency as all steps and data are documented in a traceable manner.
• Greater flexibility and patient involvement: Remote monitoring, electronic signatures after patient information has been provided (ISO14155) and decentralised data collection enable greater flexibility in the conduct of studies.

Challenges of digital data management

• Data security and data protection: As digitalisation increases, so do the requirements for data security. In its guidelines, the EMA emphasises the need for robust security measures to protect sensitive patient data.
• System validation: The FDA requires thorough validation of all computerised systems used in clinical studies. This is particularly challenging for complex, integrated systems.
• Data integrity over long periods of time: The MDCG emphasises the importance of ensuring the integrity and legibility of electronic data over the entire legally prescribed retention period (up to 25 years or longer).
• Standardisation and interoperability: To reap the full benefits of digital technologies, data must be interchangeable between different systems and platforms. Establishing uniform standards is an ongoing challenge.
• Training and acceptance: The introduction of new digital tools requires comprehensive training for study personnel and study participants. Acceptance and correct use of these technologies is crucial for success

In summary, robust data management that meets regulatory requirements and takes advantage of digital technologies is essential for the success and ethical acceptability of clinical investigations of medical devices and performance trials in the digital era.

The digital revolution in clinical studies: opportunities and challenges of data management in digital clinical investigations of medical devices and performance trials

To take full advantage of these benefits, sponsors and trial centres need to carefully consider regulatory requirements and proactively address challenges related to data security, system validation and long-term data integrity. With the right strategy and implementation, digital data management can make a decisive contribution to accelerating clinical research and improving patient care.

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