PIC/S Releases New Guide on Qualification and Validation
The Pharmaceutical Inspection Co-operation Scheme (PIC/S) has issued PI 006-4, Recommendations on Qualification and Validation, a major revision that will shape how inspectors and manufacturers approach validation programs from October 1, 2026 onward. Here’s what you need to know.
What’s Changing
PI 006-4 replaces PI 006-3, the framework in place since 2007. While PI 006-3 was split across four separate recommendation documents: Validation Master Plan (VMP), Installation and Operational Qualification (IQ/OQ), Non-Sterile Process Validation, and Cleaning Validation, PI 006-4 consolidates them into a single unified document.
The new guide was updated to align with the 2015 revision of Annex 15 and weaves quality risk management (ICH Q9) into every section, rather than treating it as a standalone topic.
New Elements Introduced
PI 006-4 expands the scope of qualification and validation to explicitly cover:
- Prequalification stages
- Performance qualification
- Ongoing process verification (OPV)
- Transport verification
- Packaging validation
- Utility qualification
- Test method validation
These principles now apply across active pharmaceutical ingredients (APIs), intermediates, and finished dosage forms.
A Notable Shift: Batch Numbers
One of the more consequential changes is around process validation batch justification. PI 006-4 moves away from a default “three-batch” approach, instead expecting manufacturers to scientifically justify the number of validation batches based on process knowledge and risk. In places, this puts PI 006-4 ahead of, and more demanding than, the current Annex 15 wording, which it treats as transitional.
What Sites Should Do Now
With entry into force just weeks away, a structured gap assessment is the recommended next step, covering:
- Your VMP against the new content requirements
- Process validation status for legacy products (is OPV running for every marketed process?)
- Batch number justifications for new products and revalidations
- Deviation management and data integrity practices