Rethinking the Rationale for the Number of Process Validation Batches

The legacy “three batches” may no longer sail through regulatory review

The long‑standing convention of running three Process Validation batches has never been grounded in statistical science. Regulations have always placed the burden on manufacturers to justify the number of batches, with the true standard being: demonstrate homogeneity within a batch and consistency between batches.

Despite this, the three‑batch approach persisted for decades because it rarely triggered regulatory pushback. That era is ending.

With the May 2026 CMC Guidelines for Biologics License Applications (BLA), a shift in thinking is signaled.  While the regulations never required three batches, the new guidance removes any ambiguity: Manufacturers must justify the appropriate number of PPQ batches based on context‑specific scientific factors, including:

• the depth of product and process understanding

• process complexity

• the robustness of the control strategy

In other words, the historical “three batches” convention will no longer pass unchallenged without a defensible scientific rationale.

Building a Scientific Rationale for the Number of Batches

1. Depth of Scientific Knowledge About the Process

Your understanding of the process — and therefore the product — comes from far more than the PPQ runs themselves. The stronger and more clearly articulated your knowledge base, the fewer PPQ batches you may need to justify.

A useful way to visualize this is as three nested knowledge spaces.

Design Space

The multidimensional combination of material attributes and process parameters that assure product quality. In practical terms: your CQAs and how they respond to your CPPs.

Control Strategy

The set of controls that ensure process performance and product quality. This is the portion of the process you are actually validating during PPQ.

Knowledge Space

The totality of what you know about the product and process — including what happens when you exceed the Design Space or violate the Control Strategy. This includes insights from:

• similar products or platforms

• historical failures

• literature

• prior development work

• manufacturing experience

When these three areas are well understood and documented, smaller numbers of PPQ batches — and smaller batch sizes — can be scientifically justified.

Key discussion points that strengthen your rationale:

• How effectively is the Control Strategy monitored, and how reliably would deviations be detected?

• How much margin exists between the Design Space CPPs and the operational limits in the Control Strategy?

• How detectable are shifts in CQAs?

• How complete and well‑supported is your Knowledge Space, based on prior experience and similar products and processes?

  
  

2. Understanding the Level and Sources of Process Variation

Your PPQ strategy must capture the range of variability expected in commercial production. This does not always require more batches — it requires the right batches.

Examples:

• A highly automated process may not exhibit shift‑to‑shift variability.

• If process variability is significantly greater than raw material variability, multiple API lots may not be necessary.

Each potential source of variation should be:

1. identified

2. assessed for magnitude and impact

3. incorporated into the PPQ plan with clear rationale

A well‑constructed Process Validation Plan explains why the selected batches, materials, and conditions adequately represent commercial variability.

Need Support Developing a Defensible Rationale?

A‑Z Continuous Compliance, LLC provides scientific, risk‑based support for complex compliance challenges. Our network of seasoned industry experts and former FDA professionals works with your team to build the approaches you need today — and the internal capability you need for tomorrow.

Contact Us