Continuous (FDA)/ On going (EMA) Process Verification Process Control
Ensure process quality, Increase process knowledge, Process stability, Process capability and Supports continuous improvement
FDA Continued Process Verification
Ongoing collection and analysis of process data related to quality. Ensures cGMP adherence (detects variability), identifies problem and corrective action. Ensures quality attributes maintained at parameters at process qualification stage
Data collected in FDA Continued Process Verification
Trends in process; incoming materials, components, in-process materials and finished products quality
Ultimate Purpose of FDA Continued Process Validation
Establishes routine levels and frequency of sampling,. monitoring and statistical analysis
EMA Ongoing Process Verification
Monitors product quality to ensure controlled state is maintained throughout lifecycle, process trends. Verification reviewed periodically, better understands product performance. Incremintal changes overtime
Control Strategy Outline
Product design conclusion, validated by pharmacovigilance. Planned set of controls derived from current performance ensures product quality. Focus on; CQA, CPP and material attributes
Critical Quality Attribute (CQA) [ICH Q8]
Physical, chemical, biological, microbiological characteristics within an approved range to ensure product quality
Critical Process Parameters (CPP) [ICH Q8]
Process parameters variability has an impact on CQA should be monitored/controlled for desired quality. Measured during manufacturing
CQAs Examples
Physical attributes, Id, Impurity assay, content uniformity, water uniformity and microbial limits. Measured during batch release testing
CPPs Examples
Agitation Rate, Drying Rate, Temp
Raw Material Attributes Outline
Physical, chemical, biological and microbiological characteristics of input materials within an appropriate limit. Ensures desired output quality. Tested in incoming inspection
In Process Control (IPCs) Outline
Measured during manufacturing ensures quality maintained
Control Chart Outline
Indicates when process is out of control to identify special-cause variation. Demonstrates consistency and stability. Evals effectiveness of process change
Common Cause Variation Outline
Chance variation inherent in any process. Process can still be in statistical control with a common cause variant
Special Cause Variation Outline
Variation that causes inconsistency in process. If present, then process can’t be in control
Control Chart Ideal
Data evenly distributed across Mean line
Control Chart Lines: 6+ data points consecutively ascending/descending from mean line
Process is not in control
Control Chart 8+ consecutive points above/below mean line
Process is not in control
Control chart; 2+ datapoints, 2 SDs from mean line
Process is out of control
Capability Analysis (CP/CPK) Outline
Process variability over long period of time, all external influences present. Goal: quantifiable measure of meeting specification. Eliminates special cause variation
Importance of Capability Analysis
Compares process against predefined targets, identify process related problems. Used as benchmark for comparison (competitors, progress, ect)
Capability Analysis Ideal
Bar chart of normal distribution
If CP/CPK > 1
Process is capable/performing
If CP/CK = 1
Process is barely capable/performing