Technology Training for Clinical Trial Participants

There are now more trials than ever that require trial participants to use computerized systems and digital health tools. Applications of these systems and devices aim to facilitate data collection in clinical trials and provide greater convenience for trial participants.

However, inadequate training on (and support with) these systems and tools may cause trial volunteers distress and burden. If left unaddressed, trial sponsors may see these results:

• Negatively impacted participant recruitment and retention
• Incorrect or missing data
• Participant fatigue and disengagement
• Drop-outs from the trial

Providing trial participants with adequate training on computerized systems is critical to mitigating these risks. This blog outlines how such training has been addressed in recent industry and regulatory guidance.

Good Clinical Practice and Technology Training for Clinical Trial Participants

The ICH E6 Good Clinical Practice (GCP) Guideline is an international ethical and scientific quality standard for designing, conducting, recording, and reporting trials that involve human volunteer participation.

The original guideline, dated 1996, was updated in 2016 (R2). It’s currently being revamped to R3, with the review process at the public consultation stage. The revamp is driven by changes in the clinical research environment since the guideline’s previous update, including increasing diversity of clinical trial designs and data sources that serve to support regulatory and health policy decision-making.

Section 2.12 (Records), E6 (R3) outlines the expectation to provide trial participants with computerized systems training. It states that, where equipment for data acquisition is provided to trial participants by the investigator, the investigator/institution should ensure that traceability is maintained and participants are provided with appropriate training (2.12.9 -c).

Likewise, Section 3.16 (Data and Records) states that, when using computerized systems in a clinical trial, trial sponsors should:

• Provide guidance to trial participants, where relevant, on the expectations for data capture, data changes, data retention, and data disposal (3.16.1 -g)

• Ensure that documented procedures and adequate training are in place to ensure the correct development, maintenance, and use of computerized systems in the trial. Notably, the attached caveat is that these requirements should be proportionate to the importance of the computerized system and the data or activities they’re expected to process (3.16.1 -w -ii).

More detailed guidance is provided in the new Section 4 (Data Governance ꟷ Investigator and Sponsor). This section focuses on systems and data that may impact the safety and rights of trial participants and reliability of trial results. It also covers the need for a comprehensive (risk-proportionate) approach to computerized systems and tools.

Section 4.3 (Computerised Systems) includes a separate sub-section on training. This sub-section reiterates the expectation of providing appropriate training for intended users (4.3.2). Additionally, it recommends involving representatives of intended participant populations and healthcare professionals when designing computerized systems(where relevant). This step helps ensure such systems are suitable for use by the intended user population.

Regulatory Expectations Regarding Technology Training for Clinical Trial Participants

Regulators, such as the EMA and U.S. FDA, support the critical importance of training trial participants on appropriate use of trial-enabling technologies. These regulators have set expectations in their various respective guidance documents. Their expectations cover a broad range of aspects around:

• Scope of training
• Recommended formats, modes, and timeframe for training delivery
• Need for customization to meet the specific needs of the end users
• Data integrity and traceability
• Document and change control
• Availability for regulatory review.

The table below provides a reference point highlighting some (non-exhaustive) examples.

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