Stop reviewing good data: review‑by‑exception for chromatography QC

Published: 27-Nov-2025

Labs spend hours confirming routine chromatograms while real risks hide in plain sight; regulators support a better path if data are captured and surfaced correctly, notes George Van Den Driessche, Data Science Product Manager at TetraScience

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Analytical quality control (QC) is drowning in data. Currently, the industry requires an exhaustive second‑person review process that verifies every chromatogram integration event and audit‑trail entry.

This approach was an absolute necessity in the predigital era and feels familiar and safe.

Yet, manual second-person review dilutes attention from where risk lives — anomalies, out‑of‑trend patterns and unexplained changes that threaten product quality and delay batch release timelines. 

Delays have huge consequences for patients who expect high-quality therapeutics to be delivered on time.

Contract Pharma reports that delaying a batch release by just one day can cost the industry almost $800,000 in lost sales and revenues.1


Patients deserve and demand better quality drugs with as few delays as possible. The pharma industry’s economics depend on accelerating outcomes.


The industry needs a better review process that can scale to meet rising demands, ensure product releases are timely and guarantee quality by design. 

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