This is a ready-to-use form for justifying how many PPQ batches you will run. There is no regulatory requirement for three batches; the number must be a conclusion of a documented risk assessment. Complete this form, attach it to the PPQ protocol, and keep it as the record an inspector will ask for. Replace every <<FILL: ...>> placeholder with your own specifics. A worked filled specimen follows. This is general guidance to adapt, not legal or regulatory advice.
Control header
| Field | Entry |
|---|---|
| Form number | <<FILL: FRM-ID, e.g. VAL-FRM-041>> |
| Linked PPQ protocol | <<FILL: protocol number and version>> |
| Product / strength / presentation | <<FILL>> |
| Site | <<FILL>> |
| Prepared by / date | <<FILL>> |
| Reviewed by (QA) / date | <<FILL>> |
1. Risk-factor assessment
Score each factor by how it pushes the batch count. Use a simple higher/lower or a numeric scale, but state the reasoning, not just the score. The number of batches is the output of this reasoning.
| Factor | Assessment (state the reasoning) | Direction |
|---|---|---|
| Stage 1 process knowledge and characterization | <<FILL: DoE-based? CPP ranges established? control strategy approved? development data volume?>> | <<FILL: lower / neutral / higher count>> |
| Product and patient risk | <<FILL: dosage form; sterile injectable? biologic with complex CQAs? narrow therapeutic index? patient population?>> | <<FILL>> |
| Inherent process variability | <<FILL: manual vs automated steps; historically variable attributes; scale-up gap>> | <<FILL>> |
| Analytical method maturity | <<FILL: validated, well-established methods vs new or high-variability assays>> | <<FILL>> |
| Novelty of process / equipment | <<FILL: established platform vs new technology or first use on this line>> | <<FILL>> |
2. Variability sources to span
List the real sources of variability and how the batch set will represent them. If a source is not spanned, justify why.
| Source | Present for this product? | How the batch set spans it (or why not) |
|---|---|---|
| Critical raw-material lots | <<FILL: number of lots in window>> | <<FILL: e.g. lots A and B across batches>> |
| Operators / shifts | <<FILL>> | <<FILL>> |
| Equipment trains / parallel units | <<FILL: single / parallel>> | <<FILL>> |
| Hold times / campaign position | <<FILL>> | <<FILL>> |
| Resin / column cycles (biologics) | <<FILL: applicable?>> | <<FILL: spanned in PPQ or carried to CPV>> |
3. Statistical basis (optional, if used)
If the count is set on a statistical basis, show the math, do not just assert it.
| Item | Entry |
|---|---|
| Method | <<FILL: tolerance interval / attribute scheme (e.g. ANSI/ASQ Z1.4) / variables scheme (Z1.9)>> |
| Confidence and coverage | <<FILL: e.g. 95% confidence that 99% of units are within spec>> |
| Resulting sample sizes / batch implication | <<FILL>> |
| Basis reference | <<FILL: study or calculation attachment>> |
4. Bracketing or matrixing (if used)
<<FILL: for multiple strengths or pack sizes on the same line by the same process, state the bracketing/matrixing approach and how it reduces the total qualification batches, or "not applicable">>.
5. Conclusion
| Item | Entry |
|---|---|
| Number of PPQ batches | <<FILL: N>> |
| Consecutive? | <<FILL: yes / no, with rationale>> |
| Variability sources represented | <<FILL: summary>> |
| Trigger to run additional batches | Unexpected variability in the executed data, or a deviation revealing a control gap; the decision and basis will be recorded |
| Overall justification statement | <<FILL: one paragraph tying the number to the factors above>> |
6. References
FDA Guidance for Industry, Process Validation: General Principles and Practices (January 2011): the number of PPQ batches should reflect process variability, Stage 1 knowledge, and risk. EudraLex Volume 4, Annex 15 (2015): the number of batches should be justified; three is a conventional minimum, not a rule. ICH Q9(R1), Quality Risk Management: the risk basis for the assessment.
Confirm the current version of each reference before issue.
Filled specimen
Illustrative completed justification for a standard immediate-release tablet. The company and numbers are illustrative; replace them with your own.
Risk-factor assessment:
| Factor | Assessment | Direction |
|---|---|---|
| Stage 1 process knowledge | DoE across blend time and compression force; CPP ranges established; control strategy approved; 9 development/scale-up batches | Lower count |
| Product and patient risk | Immediate-release tablet, wide therapeutic index, non-sterile | Lower count |
| Inherent process variability | Automated blending and compression; content uniformity historically tight | Lower count |
| Analytical method maturity | Assay, CU, dissolution methods validated and low-variability | Lower count |
| Novelty | Established granulation-compression platform, existing qualified line | Lower count |
Variability sources: 2 API lots (A, B) spanned across the three batches; 3 operators across 2 shifts spread across batches; single blender and press (no parallel span needed); no biologic resin considerations.
Conclusion: 3 consecutive PPQ batches. Batch 1 = API lot A, day shift; batch 2 = API lot B, evening shift; batch 3 = API lot A, mixed team. Additional batches will be run if executed data shows unexpected variability. Justification: a well-characterized, low-risk, automated process on a qualified line with mature methods supports the conventional minimum of three, arranged to span the two available API lots and the operator population.
The specimen shows the shape an inspector accepts: every “lower count” conclusion is tied to a specific piece of evidence, the two material lots are actually spanned, and the number is presented as the output of the reasoning, not as “three because that is standard.”
Common inspection findings this form prevents
- “Three batches per industry standard” written with no analysis behind it.
- A reproducibility claim from three batches that all used one operator, one shift, and one material lot.
- A statistical basis asserted (“95/99”) with no calculation attached.
- No recorded trigger for when more batches would be run.
How to adapt this form
- Score each factor from your real Stage 1 data and product risk, and write the reasoning.
- List the actual variability sources and show how the batch set spans them.
- If you use a statistical basis, attach the calculation.
- State the number as a conclusion, and attach the completed form to the PPQ protocol.
- Confirm every reference against the current published version before issue.