FDA publishes 4,000+ Form 483s per year containing 12,000-16,000 individual observations. FDA Tracker classifies every observation against the QSIT framework automatically, routes intelligence to system owners, and generates audit checklists weighted by current citation frequency.
Key Highlights
Regulatory Context
The quality control unit had not finalized critical SOPs — including CAPA, OOS Results, and Batch Records — that remained in draft during active manufacturing. Batch records were not reviewed before distribution, and cleanroom certification reports were not reviewed by QA before producing sterile products.
Equipment qualification procedures were not followed for new API manufacturing equipment. The firm had documented procedures requiring performance qualification before production use, but these were not executed for recently installed equipment.
Laboratory control mechanisms were not established across three areas: expired EM plates without final disposition, analytical balance errors not investigated, and BET kinetic software reader errors post-PQ with the system released for use regardless.
Equipment in the QC microbiological laboratory was not adequately maintained. Inspection revealed rust in the HEPA filters of a Laminar Flow Hood used for microbiological testing.
Supplier qualification and raw material testing had not been conducted since 2019 — a gap of over five years. Incoming materials were accepted solely on supplier certificates of analysis without periodic revalidation.
The operator identified as performing a Grade A intervention was not the same operator who received gown monitoring. A CAPA was not implemented for a deviation identifying a defect category missing from the visual inspection kit.
The Problem
Audit Readiness by Six Systems in FDA Tracker
FDA Tracker classifies every 483 observation against FDA's Six System framework. AI agents parse observation text, identify the primary system, and flag cross-system dependencies.
FDA Sources
AI Classification
Six System Feeds
Each system has its own intelligence feed showing observations, trends, and citation frequency. System owners subscribe to their feed and receive only what is relevant to their area.
FDA Tracker tracks citation frequency for each system over time, showing which systems face increasing FDA scrutiny. System owners see trends before they become industry talking points.
For each system, FDA Tracker generates an audit readiness checklist weighted by citation frequency — the most commonly cited gaps appear first. Each system owner gets a focused, actionable checklist.
FDA Tracker maps dependencies across systems — showing how a Quality System CAPA failure connects to a Production System validation gap. The Head of Quality sees a unified view of cross-system risk.
Instead of a 4-6 week pre-inspection scramble, FDA Tracker provides continuous monitoring. When FDA shifts focus, system owners are alerted and checklists update automatically.
The Solution
Automated QSIT classification, per-system checklists, and continuous readiness monitoring.
FDA Tracker classifies every 483 observation and warning letter finding against the QSIT Six System framework. AI agents parse observation text, identify primary and secondary systems, and route intelligence to system owners automatically.
For each QSIT system, FDA Tracker generates audit readiness checklists weighted by citation frequency — the most commonly cited gaps appear first.
FDA Tracker tracks citation frequency across all six systems over time, surfacing trends invisible through manual monitoring.
Instead of a 4-6 week fire drill, FDA Tracker provides continuous enforcement intelligence per system. When FDA shifts focus, checklists update and system owners are alerted automatically.
Before & After
Results
Based on FDA Tracker's automated classification versus manual analyst workflows.
Next Step
Your system owners are all waiting for the same overloaded analyst to read the same 483s. FDA Tracker classifies every observation by system automatically and gives each owner their own enforcement-weighted intelligence feed.
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