Multivariate Data Analysis to Assess Process Evolution and Systematic Root Causes Investigation in Tablet Manufacturing at an Industrial Scale-A Case Study Focused on Improving Tablet Hardness
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View abstract on PubMed
Summary
This summary is machine-generated.This study identified key variables impacting tablet hardness in high-shear wet granulation, leading to improved product quality and reduced variability. Optimized process conditions ensure robust tablet hardness, enhancing manufacturing efficiency and yield.
Area Of Science
- Pharmaceutical Manufacturing
- Process Analytical Technology (PAT)
- Quality by Design (QbD)
Background
- Limited industrial-scale studies address input variability's impact on product quality in non-simulated conditions.
- Investigating root causes of low and variable tablet hardness in high-shear wet granulation is crucial.
Purpose Of The Study
- To identify root causes of low and variable tablet hardness using batch statistical modeling.
- To verify the effectiveness of improvement actions for tablet hardness.
Main Methods
- Utilized multivariate methods for complex data assessment at an industrial scale.
- Analyzed data from two proportional composition strengths with varying tablet shapes and sizes.
- Identified inter-related active ingredient and process variables impacting hardness.
Main Results
- Identified four critical variables: API particle size, granulation nozzle type, wet discharge, and drying intensity.
- Developed an updated control strategy with specific ranges for these variables.
- Demonstrated ability to accommodate wider API particle size (d0.5 up to 70 microns) while maintaining adequate tablet hardness.
Conclusions
- Reduced risk of out-of-specification hardness results.
- Achieved cost avoidance and yield improvement.
- Confirmed significant average hardness increase (15-20%) and decreased batch variability, reaching sigma quality levels of 2.5.
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