[Correlation of dry granulation process parameters and granule quality based on multiple regression analysis].

Area of Science:

• Pharmaceutical Technology
• Materials Science
• Chemical Engineering

Background:

• Dry granulation is a key process in pharmaceutical manufacturing.
• Optimizing process parameters is crucial for achieving desired granule properties like yield and friability.
• Microcrystalline cellulose is a widely used excipient in solid dosage forms.

Purpose of the Study:

• To investigate the impact of single and combined process parameters on granule yield and friability during dry granulation.
• To establish correlations between process parameters and the quality attributes of microcrystalline cellulose granules.
• To develop a predictive model for granule quality based on process variables.

Main Methods:

• Dry granulation of microcrystalline cellulose (WJ101) as a model material.
• Single-factor experiments to assess individual parameter effects.
• Multi-factor experiments to evaluate comprehensive parameter interactions.
• Multiple regression analysis to establish quantitative relationships and predictive equations.

Main Results:

• Established the order of influence for process parameters: roller speed > roller pressure > horizontal feed speed.
• Granule yield showed positive correlation with pressure and feed speed, but negative correlation with roller speed.
• Friability exhibited an inverse relationship compared to granule yield.
• Developed a regression model demonstrating high precision and reliability (P > 0.05) between predicted and actual values.

Conclusions:

• Process parameters significantly influence dry granulation outcomes for microcrystalline cellulose.
• Roller speed is the most critical parameter affecting both granule yield and friability.
• The developed regression model provides a reliable tool for optimizing dry granulation processes to achieve desired product quality.