Design space approach in optimization of fluid bed granulation and tablets compression process.

Area of Science:

• Pharmaceutical Technology
• Chemical Engineering
• Materials Science

Background:

• Optimizing pharmaceutical manufacturing processes is crucial for consistent drug product quality.
• The design space approach provides a framework for understanding process variability and ensuring product performance.
• Identifying critical formulation and process parameters is essential for robust tablet manufacturing.

Purpose of the Study:

• To optimize fluid bed granulation and tablet compression processes using a design space approach.
• To identify critical formulation and process parameters influencing granule and tablet characteristics.
• To develop predictive models for tablet hardness and paracetamol release profiles.

Main Methods:

• Plackett-Burman experimental design to screen critical parameters.
• Systematic variation of parameters including diluent type, binder concentration, temperatures, spray rate, atomization pressure, and compression force.
• Artificial Neural Networks (ANNs) to establish the design space and model relationships.

Main Results:

• Diluent type and atomization pressure were identified as the most significant parameters affecting granule characteristics.
• ANNs models successfully predicted tablet hardness and paracetamol release based on atomization pressure and compression force.
• Atomization pressure primarily influenced the drug dissolution profile, while compression force mainly affected tablet hardness.

Conclusions:

• The design space approach, coupled with ANNs, effectively optimizes pharmaceutical manufacturing processes.
• Key parameters like atomization pressure and compression force can be controlled to achieve desired tablet quality attributes.
• Predictive models enable robust control over tablet hardness and drug release, ensuring consistent product performance.