Eli Lilly used PI Event Frames and Seeq Vantage AI for faster deviation investigations and monitoring.
Deviation investigations were slow and asset qualification monitoring was manual, about 10 hours a month per asset. Lilly applied investigative analytics with PI Event Frames and Seeq Vantage AI for exception-based monitoring. The page states equipment cleanliness checks took 2 hours instead of 2 days and 40 relevant batches were isolated from 3,000.
Seeq is an industrial analytics software vendor used by pharma and biotech engineers for batch analysis, deviation investigation and scale-up
This sits in the Ship stage of the AI use-case lifecycle: Named examples from the vendors pharma teams use to get an AI system live inside a real, regulated production workflow — validation, CRM, safety and clinical systems of record.
Published by Seeq on its own site — read the original case study on seeq.com ↗
Note: Customer examples summarized in a Seeq blog post on Conneqt 2025.
Related use cases
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- 02Regeneron embedded Seeq in tech transfer and cut alert noise from 700 per batch to about 40 per month.
- 03A biopharma used Seeq on AWS to predict bad fill-weight batches before completion.
- 04Seeq let a biologics team compare lab and pilot batches without spreadsheets, speeding scale-up.
- 05Seeq built a live KPI dashboard for a pharma continuous manufacturing line.
- 06Merck uses OSIsoft and Seeq analytics on AWS to support continuous drug manufacturing.