Human Review at Scale: The Expert Layer
AI-generated regulatory documents require expert review. This is not optional, and it's not a hedge — it's a fundamental requirement of a well-functioning system. The question is not whether to have expert review, but how to design it so that expert time is used for expert work.
The current failure mode
In most regulatory writing operations, expert review is poorly structured. Reviewers receive a document and are asked for "comments." The result is that a significant fraction of reviewer time goes to:
- Finding consistency errors that AI could have caught
- Reformatting tables to match FDA guidance
- Cross-checking citations that should have been auto-verified
- Fixing terminology inconsistencies that a style guide should have caught
This is not a good use of a regulatory expert's time. And because it takes so long, reviewers often skim the sections where their judgment is actually critical.
The designed review workflow
A well-designed expert review workflow has three tiers:
Tier 1 — AI-handled pre-review: Before the document reaches any human reviewer, AI runs a systematic check: formatting compliance with applicable FDA guidance, consistency of all numbers against source data, completeness of citations, terminology consistency with defined style guide. Any issue at this tier is flagged and corrected automatically or sent to a writer for quick resolution.
Tier 2 — Medical/scientific review: Once Tier 1 is clean, the document goes to medical and scientific reviewers whose time is explicitly scoped to the interpretive content — benefit-risk framing, clinical interpretation of findings, strategic decisions about what to emphasize or contextualize.
Tier 3 — Regulatory strategy review: Final review by the regulatory lead focuses on agency interaction strategy, precedent alignment, and labeling language. This review is informed by AI-generated competitive analysis: how have similar submissions framed similar sections?
The result
This tier structure reduces total expert review time per NDA cycle by 30-40% — not by reducing scrutiny, but by eliminating the time experts spend doing non-expert work. And because the AI-handled pre-review eliminates most consistency issues before the document reaches expert reviewers, the quality of the expert review actually improves.