Aetion Urges FDA To Establish Cloud-Based RWE Platform
Aetion has issued a call for the FDA to implement a cloud-based real-world evidence (RWE) platform with robust data governance so that users can do data queries, archiving, access, and aggregation. Such a system, the company says, could help avoid unnecessary data duplication and support concurrent reviews by global regulators.
The FDA was going to discuss its September 2019 Technology Modernization Action Plan, an overarching plan that could include the use of RWE, at a meeting on March 27, but the meeting was rescheduled for June 30 due to COVID-19 concerns.
To better manage data, Aetion has recommended that the FDA use a cloud-based RWE platform that provides full transparency in the documentation of every methodological decision made during the analysis of that data. This could facilitate integration and interoperability of health care data and provide a way to collect and store data differently in the future.
A cloud-based system, the company wrote, should document data provenance and data transformation, store data on a long-term basis, provide query access to appropriate parties, and document data linkage and analytic cohorts. Sponsors should be able to use the platform to transmit and exchange data containing proprietary information, and FDA reviewers should be able to fully query patient-level data without the need to interact directly with patient-level records.
Aetion also wrote that a cloud-based system could support global interagency reviews, including multi-database studies, while addressing data privacy concerns. “One way to address global data privacy issues is through the use of a cloud-based RWE platform that can host data in specific geographies and restrict data access to users in the country where these data were produced,” the comment letter read.
The FDA should increase transparency for FDA reviewers, the letter read. “The modern data strategy should give FDA reviewers the ability to clearly understand data sources and their contents (e.g., for EHR data, a clear understanding of collection sites, data collected, and time range capture),” Aetion wrote in its comment letter. “Reviewers should be able to trace data provenance, to understand all the data transformations, to reproduce studies submitted, and to perform sensitivity analysis on submitted data.”
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