Publicação
A continuous manufacturing model for the production of granules by roller compaction
| Resumo: | Continuous manufacturing is an encouraging and a sustaining innovation in pharmaceutical manufacturing, build upon quality-by-design principles, with a huge potential to improve agility, flexibility and robustness to the manufacturing process. In this field, the Roller Compaction (RC) process plays an important role since it enables continuous dry granulation of powders. Here, the powder is densified by two counter-rotating rolls that produce a ribbon. Then, the ribbon is milled into granules, adequate for tableting or capsule filling. RC overcomes granulation problems with thermolabile moisture or solvents sensitive compounds. In this work, an experimental design was performed in order to identify the critical process parameters (CPP) and evaluate their impact on the critical quality attributes (QCA) of granules produced by RC. The roller compactor used was the Hosokawa Bepex Pharmapaktor® L200/30P, with a Flake Crusher FC 200. The RC process was monitored by a near infrared (NIR) system and a direct imaging analyzer for granules’s size (Eyecon). For the DoE the CPP’s proposed and their respective range were: compression force (15-35 kN), roller speed (3-8 rpm) and mill speed (50-250 rpm). The produced granules were characterized according to their particle size, as well as their bulk and tapped density – granules’ CQA’s. All process variables were kept constant 2 minutes after the process onset. The compression force fluctuated throughout the process run time. The compression force was the variable that most affected the granules’ CQA’s: the size and the density of the granules are directly proportional to the compression force. The Eyecon´s measurements exhibited significant deviations when compared with the gold standard method, thus it was not an accurate method for monitoring the granules’ size. Two approaches were followed for the prediction of granules’ physical properties. The first model, that used partial least squares to predict the granules’ size, was built upon near infrared data. It returned a high RMSEP (50.54 μm) and a poor coefficient of determination for the prediction set (0.19), so it was not acceptable for the prediction of the granules’ size. The second approach considered process parameters data to predict the bulk density, tapped density and size of the granules. One partial least squares model was built to predict each response. The coefficient of determination for the prediction set was high for the three models (0.93 for granules’ size, 0.95 for tapped density and 0.96 for bulk density) demonstrating a good prediction ability. |
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| Autores principais: | Dias, Rute Sofia Fonseca Cordeiro |
| Assunto: | Continuous Manufacturing Critical Process Parameters Near-infrared Spectroscopy Partial Least Squares Roller Compaction Teses de mestrado - 2017 |
| Ano: | 2017 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório da Universidade de Lisboa |
| Resumo: | Continuous manufacturing is an encouraging and a sustaining innovation in pharmaceutical manufacturing, build upon quality-by-design principles, with a huge potential to improve agility, flexibility and robustness to the manufacturing process. In this field, the Roller Compaction (RC) process plays an important role since it enables continuous dry granulation of powders. Here, the powder is densified by two counter-rotating rolls that produce a ribbon. Then, the ribbon is milled into granules, adequate for tableting or capsule filling. RC overcomes granulation problems with thermolabile moisture or solvents sensitive compounds. In this work, an experimental design was performed in order to identify the critical process parameters (CPP) and evaluate their impact on the critical quality attributes (QCA) of granules produced by RC. The roller compactor used was the Hosokawa Bepex Pharmapaktor® L200/30P, with a Flake Crusher FC 200. The RC process was monitored by a near infrared (NIR) system and a direct imaging analyzer for granules’s size (Eyecon). For the DoE the CPP’s proposed and their respective range were: compression force (15-35 kN), roller speed (3-8 rpm) and mill speed (50-250 rpm). The produced granules were characterized according to their particle size, as well as their bulk and tapped density – granules’ CQA’s. All process variables were kept constant 2 minutes after the process onset. The compression force fluctuated throughout the process run time. The compression force was the variable that most affected the granules’ CQA’s: the size and the density of the granules are directly proportional to the compression force. The Eyecon´s measurements exhibited significant deviations when compared with the gold standard method, thus it was not an accurate method for monitoring the granules’ size. Two approaches were followed for the prediction of granules’ physical properties. The first model, that used partial least squares to predict the granules’ size, was built upon near infrared data. It returned a high RMSEP (50.54 μm) and a poor coefficient of determination for the prediction set (0.19), so it was not acceptable for the prediction of the granules’ size. The second approach considered process parameters data to predict the bulk density, tapped density and size of the granules. One partial least squares model was built to predict each response. The coefficient of determination for the prediction set was high for the three models (0.93 for granules’ size, 0.95 for tapped density and 0.96 for bulk density) demonstrating a good prediction ability. |
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