We know it is really October, but we held the posting of this edition until we could point you to the full scientific article on DCT Data Management. We hope you will find it to be worth the wait!
Welcome to the September edition of the DCT Blog.
Last month, we explored the increased need for site visit replacement services such as mobile phlebotomy and mobile nursing due to the COVID-19 pandemic. Keeping visits on track, be they on-site or remote, is critical to trial success during this unprecedented time.
But once the visits happen, are there any special data management considerations, once trials shift to a more decentralized methodology? This month, we will take a quick look at this, and invite you to download a recently published article that digs into more detail on this topic.
Clinical trial data management systems have been evolving since the first clinical trials began in the 1940s. The architecture of data management has for the most respect grown to match the needs of the clinical trial design. As trials have become more complex, so too have the means by which we collect, store, and analyze clinical trial data. The shift to more remote visits, and new types of data such as from wearable sensors, will cause the data management needs to shift accordingly. Traditional trials don’t use a “one size fits all” data management approach, and neither will DCTs.
Just as DCTs themselves involve an ecosystem of modular solutions such as patient apps, sample collections, drug supply, tele-visits, and so on, it has become increasingly critical that the data management architecture for DCTs be an ecosystem of flexible components that can react appropriately to the diversification of data sources that modernize clinical trials use. It’s important that eCRFs (electronic case report forms) generate a holistic clinical view at the subject level to allow the investigator to efficiently review the data and approve them.
Another challenge in DCT data management involves the greater range of devices and applications involved. A typical DCT will have the patients supplied with a provisioned device (a tablet or a smartphone) which is dedicated to the trial, or allow them to use personal smart devices or computers aka “bring your own device” or BYOD which increases the complexity of the environment in which trial apps and data collection will occur. This added complexity needs to be reviewed in the context of the regulatory environments in which the trial will occur. This adds a validation effort layer, which largely replaces the data transcription review that happens when data sources are not integrated directly.
These hot button issues only scratch the surface of all the considerations that need to be taken into account as we transition more and more trials to DCT models. For a complete review of these and many other factors around technology integration, quality and regulatory compliance, and vendor management, please download our article “Clinical Data Management Considerations for Decentralized Trial (DCT) Execution”.
Check back with us next month as we dig deeper into issues of system integration as driven by clinical trial design.
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