For most pharmaceutical companies, submitting clinical study data to the FDA is an expensive and time-consuming process. A study sponsor must collect data from different sources, extract it from proprietary file formats, transform it to conform to CDISC standards, organize metadata describing these transformations, execute validation scripts to ensure data consistency, and convert it all into the file formats required by the FDA for submission.
Unfortunately, the methods used to aggregate, clean, transform, and validate this data today are largely manual, relying on teams of contractors using proprietary software and spreadsheets of transformation and validation rules that are difficult to modify or extend. When the standards are updated, when the validation rules change, if a submission contains an error, or if a company wants to build a data warehouse for all their study data: the entire conversion must be restarted.
The result? A process that is expensive to perform, slow to fix errors, and difficult to maintain.
Join Timothy Danford, CDISC Solution Lead for Tamr, and John Smith, Officer at Widgets Inc, as they discuss common CDISC challenges, and how Tamr’s CDISC solution offers a scalable, replicable way to automatically convert, validate, and package clinical study data in standard file formats organized according to the latest CDISC standards.