Multivariate statistical process control of a continuous pharmaceutical twin-screw granulation and fluid bed drying...

Area of Science:

• Pharmaceutical Manufacturing
• Process Analytical Technology
• Quality Control

Background:

• Continuous manufacturing offers advantages in pharmaceutical production.
• Effective process monitoring is crucial for ensuring consistent tablet quality.
• Multivariate Statistical Process Control (MSPC) is a powerful tool for complex process analysis.

Purpose of the Study:

• To develop and evaluate a multivariate statistical process control (MSPC) strategy for the ConsiGma™-25 continuous tablet manufacturing line.
• To assess the capability of the MSPC model in detecting process deviations.
• To identify key process variables influencing manufacturing continuity.

Main Methods:

• Utilized 35 logged variables from a twin screw granulator, fluid bed dryer, and product control unit.
• Applied principal component analysis (PCA) to data from normal operating conditions.
• Evaluated model performance using imposed disturbances and Hotelling's T² and Q residuals control charts.

Main Results:

• All imposed process disturbances (dryer airflow/temperature, granulator parameters, powder dosing) were successfully detected.
• The MSPC strategy demonstrated effective monitoring of the tablet manufacturing process.
• Unforeseen deviations, particularly in granulator barrel temperature, were also identified.

Conclusions:

• The developed MSPC strategy is a viable and effective tool for real-time monitoring of continuous tablet manufacturing.
• This approach enhances process understanding and facilitates early detection of quality-impacting events.
• MSPC implementation contributes to robust quality control in pharmaceutical production.