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Modeling of a roller-compaction process using neural networks and genetic algorithms
M Turkoglu1, I Aydin, M Murray
1Marmara University, Faculty of Pharmacy, Istanbul, Turkey. turkoglu@marun.edu.tr
Summary
This study optimized acetaminophene roller-compaction using artificial neural networks and genetic algorithms. Hydroxypropyl methyl cellulose (HPMC) at 20% with two passes yielded acceptable tablets, while PEG and Carbopol offered sustained-release potential.
Area of Science:
- Pharmaceutical Technology
- Materials Science
Background:
- Roller-compaction is a critical process in tablet manufacturing.
- Binder selection significantly impacts tablet properties and performance.
- Optimization of process parameters is essential for robust tablet production.
Purpose of the Study:
- To model and optimize the roller-compaction of acetaminophene.
- To investigate the influence of binder type, concentration, and process parameters on tablet characteristics.
- To compare the predictive capabilities of Artificial Neural Networks (ANN) and genetic algorithms (GA) for optimization.
Main Methods:
- Experimental design involving 42 batches of acetaminophene.
- Evaluation of binder types: hydroxypropyl methyl cellulose (HPMC), polyethylene glycol (PEG), and Carbopol.
- Assessment of binder concentrations (5%, 10%, 20%), roller-compaction passes (1 or 2), and microcrystalline cellulose addition.
- Data analysis and optimization using Artificial Neural Networks (ANN) and Genetic Algorithms (GA).
Main Results:
- ANN and GA models achieved R2 values ranging from 0.3593 to 0.9991 for measured responses.
- Genetic algorithm predictions demonstrated superior accuracy compared to ANN during validation.
- Optimization identified HPMC at 20% with two roller-compaction passes as optimal for mechanically acceptable acetaminophene tablets.
- PEG and Carbopol binders showed potential for sustained-release formulations and eliminated the need for external lubricants with PEG.
Conclusions:
- Genetic algorithms provide a powerful tool for optimizing roller-compaction processes and predicting tablet properties.
- Hydroxypropyl methyl cellulose (HPMC) is effective for producing mechanically robust acetaminophene tablets via roller-compaction.
- Polyethylene glycol (PEG) and Carbopol offer alternative binder options, particularly for sustained-release applications, with PEG providing manufacturing advantages.
- The study successfully established a data-driven approach for optimizing pharmaceutical tablet manufacturing.