Patient and Caregiver
Investigator
Regulator
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Tech, Device,
PayerTrial Design Stage
Published Date: April 29, 2025
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Helpful Terms and Definitions
*This list is not exhaustive, nor does CTTI officially endorse the resources created by other organizations.
Synopsis
Always select the technology AFTER selecting the outcome
Questions To Ask
- What are the primary and secondary objectives of the trial?
- What endpoints will be measured, and how can technology support accurate, reliable, and efficient data capture?
- How can technology support participant recruitment, retention, and engagement?
- Can digital tools (e.g., mobile apps, wearables) reduce burden and improve participation?
- What types of data will be collected, and how can technology streamline collection and management?
- How will systems such as EDC, remote monitoring tools, and analytics platforms integrate and support data quality?
- Is the technology fit-for-purpose and compliant with applicable regulatory expectations?
- Has the technology been appropriately validated for accuracy, reliability, and data integrity within the trial context?
- How will technology support study operations (e.g., site workflows, monitoring, reporting)?
- Are tools such as CTMS or remote monitoring platforms appropriate for the study design?
- What are the implementation, training, and maintenance costs?
- Do resource requirements align with study scope and timelines?
- Can the technology scale with study size and geographic footprint?
- Is it adaptable to protocol changes or amendments, if needed?
Why involve tech, device, and data companies now?
The synopsis phase is where study design becomes more concrete, making it a critical point to assess whether proposed endpoints and data collection strategies are operationally feasible and supported by appropriate technologies.
Engaging technology, device, and data partners at this stage helps ensure alignment between study objectives, endpoint definitions, and data capture capabilities—reducing the risk of protocol amendments, implementation delays, or data quality issues later in development.
Early collaboration also supports planning for system integration, data flow, and usability across sites and participants, while enabling realistic assessment of operational complexity—particularly in studies involving multiple vendors or decentralized elements.
What aspects of the synopsis should they inform?
- Endpoint feasibility (including digital or remote measurement)
- Study population feasibility (based on data availability and capture methods)
- Inclusion and exclusion criteria (impact on recruitment and data capture)
- Sample size planning (informed by feasibility and data considerations)
- Site and geographic feasibility (technology capabilities and infrastructure)
- Data collection strategy and system integration
- Operational feasibility and risk identification
Tech, Device, and Data Company Resources
A Smarter Approach to Clinical Trial Design and Delivery
Using digital technologies in clinical trials: current and future applications
Embracing Hybrid Trial Design - How, When, & Why To Use It
Artificial Intelligence for Clinical Trial Design
Clinical Trial Management Systems