Applicability of image analysis to support QbD driven development of pellets

Area of Science:

• Pharmaceutical Sciences
• Process Engineering

Background:

• Optimizing pellet production is crucial for drug delivery.
• Scale-up challenges require robust process understanding.
• Quality by Design (QbD) principles enhance pharmaceutical manufacturing.

Purpose of the Study:

• Investigate high drug-loaded pellet preparation stages.
• Utilize static and dynamic imaging for process understanding and scale-up.
• Demonstrate Quality by Design (QbD) and Process Analytical Technology (PAT) in pellet development.

Main Methods:

• Pellet preparation at laboratory and production scales (granulation, extrusion/spheronization, drying, coating).
• Investigation of process parameters' influence on pellet properties (aspect ratio, yield, size distribution).
• Application of static and dynamic image analysis (DIA) for quality assessment and agglomeration detection during coating.

Main Results:

• Confirmed effects of kneading time, water content, and extrusion screen plate (ESP) parameters on pellet properties.
• Identified ESP quality as a critical factor alongside dimensions.
• Demonstrated comparable coating thickness measurements between static and DIA.
• Showcased real-time agglomeration detection during coating using PATVIS APA.

Conclusions:

• Dynamic image analysis (DIA) is an effective Process Analytical Technology (PAT) tool for real-time evaluation of spheronization and coating.
• The study confirmed the design space for key process parameters.
• PATVIS APA facilitates in-line monitoring and control for improved pellet quality and manufacturing efficiency.