Workflow for Criticality Assessment Applied in Biopharmaceutical Process Validation Stage 1

Area of Science:

• Pharmaceutical Manufacturing
• Biopharmaceutical Process Development
• Statistical Quality Control

Background:

• Process validation requires identifying critical process parameters (CPPs) impacting product quality.
• Traditional methods like design of experiments (DOE) may miss parameters with high uncertainty due to unexpected experimental variance.
• Overlooked parameters with high uncertainty can lead to undesirable product quality and limit critical product attributes.

Purpose of the Study:

• To introduce a novel retrospective power analysis permutation test for identifying overlooked CPPs.
• To evaluate the test's effectiveness using industrial biopharmaceutical process data.
• To present a workflow for mitigating risks associated with undetected parameter effects.

Main Methods:

• Development and application of a retrospective power analysis permutation test.
• Evaluation using data from two unit operations in a biopharmaceutical process.
• Comparison of a priori expected variance with observed residual variance in experiments.

Main Results:

• The analysis revealed significantly larger than expected variance in one unit operation.
• Low statistical power was observed for non-significant parameters in that unit operation.
• The developed workflow demonstrated a statistically sound method for CPP identification.

Conclusions:

• The retrospective power analysis permutation test effectively identifies parameters that traditional methods might overlook.
• The proposed workflow enhances the identification of CPPs, leading to statistically sound process validation.
• Implementing this approach supports consistent product quality, reduced process variance, and increased patient safety in biopharmaceutical manufacturing.