The USFDA has issued a Warning Letter to Shiva Analyticals’ Bangalore facility following significant cGMP deviations observed during an inspection in January 2025. The facility (FEI: 3006192929) was inspected by FDA investigators Timothy H Vo and Pratik S Upadhyay.
The letter highlights serious concerns regarding:
- Deficient handling of Out-of-Specification (OOS) results
- Data Integrity lapses in managing cGMP documents and chromatographic systems
The FDA has asked Shiva Analyticals to undertake substantial improvements in Investigation competencies, Quality Unit (QU) oversight and also for an independent assessment of laboratory practices
Out-of-Specification (OOS) Investigations
- Investigations lacked scientific rationale to support root causes and failed to extend to previously analyzed batches.
- No effective Corrective and Preventive Actions (CAPA) were implemented for reducing recurring human errors contributing to OOS incidents.
- New analytical results were used to invalidate OOS findings without robust justification.
Data Integrity Concerns
- Torn and discarded cGMP documents—including method verification reports, balance printouts, and pH meter readings—were found in the document disposal area.
- Audit trail reviews of MassLynx software revealed analyst had performed “hundreds of entries” involving Add/Delete/Modify peaks and Alter existing files.
Learnings
- Human error is not a root cause—it’s a symptom. FDA Warning letters have repeatedly shown that human error alone as a reason for OOS incidents is not acceptable. It could be procedural lapses, skills and competencies of analysts, poor analytical practices, instrument or method issues and so on. The root cause investigation must focus on the underlying reasons, evaluate past incidents and trends and CAPA actions address the same. There should be effective processes to enhance analytical competencies of the analysts.
- Electronic data systems must have stringent controls. At the analyst level user access privileges should be limited to functional requirements to run samples, generate results. Any method or data modifications or modification to data processing parameters must be documented with clear rationale. Original data and audit trail of all changes should be available.
- Data Integrity is non-negotiable. Management must foster a strong quality culture, ensure robust QU oversight, and maintain control over all aspects laboratory and manufacturing operations to ensure integrity.
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