White papers

Generative AI is rapidly entering regulatory medical writing, yet the industry lacks standardized methods for measuring document quality. As AI takes on a larger role in drafting regulatory content, organizations must show that AI-assisted outputs meet the same standards of accuracy, completeness, and compliance as human-authored text. This article distinguishes quality assurance from quality measurement and argues that measurement must come first.

We propose a multilayered evaluation framework built around postedit distance and introduce the Peer Quality Index, a composite score spanning 6 dimensions, offering a defensible path toward transparency and trust in AI-assisted regulatory writing.