By Ben Berkey, Tina Gartside, and Katie Robbins, inSeption Group
Applying effective data quality control (QC) to clinical regulatory and publications documents requires a sound process, adaptable to the time crunch of being among the final tasks preceding regulatory submission.
Medical writing QC encompasses a complete check of source data, internal consistency, formatting, and an editorial review of clinical documents. Source data comprises validated data points from statistical output, published peer-reviewed articles, presentations at medical conferences, or documents on file at biopharma companies. All data in clinical documents must have retrievable, verifiable source data. In short, QC is a 100% check to ensure documents contain accurate and verifiable clinical data.
While a document may have only one writer, it likely has several contributors, which may lead to the inadvertent introduction of sourcing errors, untracked edits, or versioning issues that make it hard to determine which draft is the most up-to-date. The discovery of such errors by agency reviewers in just a few documents can undermine regulators’ confidence in the accuracy of an entire submission.