Skip to main content

Presentation: Automated Quality Review: detecting discrepancies in Blinded Data Reviews

Presentation by: Bryan Morganti, BT Manager, Business Partner for Regulatory from Pfizer and Paul Milligan, Senior Product Manager from Linguamatics at Linguamatics Text Mining Summit 2017.

Checking for errors in documents for FDA submission is a complex problem, which is currently undertaken as a manual and costly process. Automation of this process -- ensuring that error checks are reliable, repeatable and accurate -- could speed it up and make it more efficient.

Pfizer have identified that analysis of Blinded Data Reviews is a key stage in the submission process: early enough in the process to prevent errors from propagating, but late enough that errors are difficult to detect manually. Pfizer and Linguamatics have worked together on a project to create a solution that allows reviewers to submit document packets and use I2E to generate reports summarizing the detected errors.

The solution has been implemented on premise at Pfizer, ensuring that the sensitivity of these documents is preserved.

To view this presentation, you will first need to fill out a short webform:


Ready to get started?

Request a Demo

Questions? Ask our experts