Adaptive designs have the potential to accelerate clinical development, and improve the probability of trial success. While the principle is simple- to reduce the uncertainty in clinical development by obtaining additional information from the ongoing trial- the statistical methodologies can be complex, and expert support is often required to conduct the clinical trial design. There's also complexity in the data collection itself, so knowledgable data management support is needed to successfully execute an innovative trial design. In this blog, we take a look at 5 top considerations for successful adaptive trial data management.
Planning ahead
In general, there is more upfront time involved in planning and setting up an adaptive trial. If working with a group whose biostatistics and data management (DM) group is closely aligned, it is possible to ensure that the DM group is kept well abreast of developments so that data collection considerations are taken into account as early as possible in the process. This enables the database design to be initiated as soon as appropriate.
Technology to ease operational challenges
Integrated EDC, randomization and trial supply systems are increasingly common. Effective deployment of these technologies can help to simplify the operational challenges of adaptive trials. A change need only to be made once in the integrated system to cascade through and address all elements. Cytel’s data management experts can advise on the most appropriate system for your trial.
Interim Analyses
At the interim analysis, the length of time needed to make a decision relative to the time of enrollment must be small. It’s critical that data processing and analysis is managed efficiently to minimize potential overrun (patients enrolling while the interim analysis is taking place). For data management, an interim analysis is treated as a ‘soft lock’ employing the identical rigor which would be applied to a full database lock. Once the soft lock date has been identified, the data manager needs to carefully manage the timeline, working backwards to ensure that all of the data up to that point is entered and monitored. Close alignment between biostatistics and data management groups is fundamental to success. It’s also useful to have access to a global team that can work around the clock to meet often tight deadlines.
Communication and Project Management
Adaptive trials usually bring added complexity, and therefore, the data manager needs to be able to handle the additional data, communication and project management demands. In a recent project handled by our data management group, subjects were randomized once, but into a multiple arm scenario. During the trial the subjects could be switched from placebo to drug or drug to placebo. The unblinded data manager therefore had a crucial role to play in ensuring that that all parties were getting the information they needed at the right time. In such cases, it’s extra important that the clinical data managers are highly experienced and adept at stakeholder communication and education.
CRF Design
Some adaptive design scenarios may require changes to the CRF as part of adaptation. Therefore, in the planning stages, it's important to prepare for CRF redesign, revalidation, and redeployment. It is also prudent to plan ahead for the more probable scenarios.
Cytel has designed and implemented more adaptive trials than any other CRO, and our data management team regularly manages trials with innovative designs.
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Thanks to Patti Arsenault, Director Data Management at Cytel
