Challenge
A public biotech client ($700M+ market cap) faced the challenge of determining whether AI could handle highly complex, technical CMC documents. The task: turn data-dense, color-coded PDFs from a manufacturing partner into clear, regulatory-ready prose.
Solution
The client used Peer AI’s agentic platform to generate IND Module 3 sections for comparison against manual processes.
Peer AI Agents drove efficiency gains: specialized AI agents enabled faster interpretation of complex datasets and formatting consistency.
Used the same source files (PDFs, scans, CDMO stability/specs docs, protocols, CoAs)
Peer generated Draft 1 directly from these files
Customer TechOps team reviewed and scored quality metrics
Results & Impact
Quality Gain: Peer Draft 1 rated better than in-house final drafts
Completeness & Readability: Scored higher, with significantly improved readability
Accuracy: Comparable to manual authoring
Efficiency: Customer assessment that the Peer AI platform was more efficient than traditional methodology
Scalable platform: Demonstrated capability to author not just one, but multiple sets of complex CMC documents, showing how efficiency gains compound across use cases
"I couldn’t tell if I was reading our document or the one from Peer — they were identical! I like the formatting of the tables better in the Peer version — they are easier to read."
Technical Writer, Public Biotech client
