MPS-Shift Quality Left: How Improving Manuscripts Before Peer Review Reduces Strain Across the System

The publishing industry spends significant resources detecting and correcting quality problems during peer review, copyediting, and production. But many of these problems originate upstream, in the language, structure, and metadata quality of manuscripts at submission. What if publishers invested in fixing them there?

This session presents an emerging workflow model in which manuscripts are automatically assessed for language quality at submission, triaged to AI-powered editing when needed, and returned to the author for review, all before peer review begins. When the publisher invests in manuscript quality upstream, the benefits cascade: reviewers receive cleaner papers, editors spend less time on remediation, and production costs drop. The session also examines how single-source publishing architecture shifts structural quality left.

Attendees will leave with a practical model for moving quality investment upstream and a framework for connecting language tools, AI editing, and modern publishing infrastructure to reduce costs and improve outcomes across the lifecycle.