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Process Design of Continuous Powder Blending Using Residence Time Distribution and Feeding Models
The present paper reports a thorough continuous powder blending process design of acetylsalicylic acid (ASA) and microcrystalline cellulose (MCC) based on the Process Analytical Technology (PAT) guideline. A NIR-based method was applied using multivariate data analysis to achieve in-line process mon...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7699818/ https://www.ncbi.nlm.nih.gov/pubmed/33233635 http://dx.doi.org/10.3390/pharmaceutics12111119 |
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author | Gyürkés, Martin Madarász, Lajos Köte, Ákos Domokos, András Mészáros, Dániel Beke, Áron Kristóf Nagy, Brigitta Marosi, György Pataki, Hajnalka Nagy, Zsombor Kristóf Farkas, Attila |
author_facet | Gyürkés, Martin Madarász, Lajos Köte, Ákos Domokos, András Mészáros, Dániel Beke, Áron Kristóf Nagy, Brigitta Marosi, György Pataki, Hajnalka Nagy, Zsombor Kristóf Farkas, Attila |
author_sort | Gyürkés, Martin |
collection | PubMed |
description | The present paper reports a thorough continuous powder blending process design of acetylsalicylic acid (ASA) and microcrystalline cellulose (MCC) based on the Process Analytical Technology (PAT) guideline. A NIR-based method was applied using multivariate data analysis to achieve in-line process monitoring. The process dynamics were described with residence time distribution (RTD) models to achieve deep process understanding. The RTD was determined using the active pharmaceutical ingredient (API) as a tracer with multiple designs of experiment (DoE) studies to determine the effect of critical process parameters (CPPs) on the process dynamics. To achieve quality control through material diversion from feeding data, soft sensor-based process control tools were designed using the RTD model. The operation block model of the system was designed to select feasible experimental setups using the RTD model, and feeder characterizations as digital twins, therefore visualizing the output of theoretical setups. The concept significantly reduces the material and instrumental costs of process design and implementation. |
format | Online Article Text |
id | pubmed-7699818 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-76998182020-11-29 Process Design of Continuous Powder Blending Using Residence Time Distribution and Feeding Models Gyürkés, Martin Madarász, Lajos Köte, Ákos Domokos, András Mészáros, Dániel Beke, Áron Kristóf Nagy, Brigitta Marosi, György Pataki, Hajnalka Nagy, Zsombor Kristóf Farkas, Attila Pharmaceutics Article The present paper reports a thorough continuous powder blending process design of acetylsalicylic acid (ASA) and microcrystalline cellulose (MCC) based on the Process Analytical Technology (PAT) guideline. A NIR-based method was applied using multivariate data analysis to achieve in-line process monitoring. The process dynamics were described with residence time distribution (RTD) models to achieve deep process understanding. The RTD was determined using the active pharmaceutical ingredient (API) as a tracer with multiple designs of experiment (DoE) studies to determine the effect of critical process parameters (CPPs) on the process dynamics. To achieve quality control through material diversion from feeding data, soft sensor-based process control tools were designed using the RTD model. The operation block model of the system was designed to select feasible experimental setups using the RTD model, and feeder characterizations as digital twins, therefore visualizing the output of theoretical setups. The concept significantly reduces the material and instrumental costs of process design and implementation. MDPI 2020-11-20 /pmc/articles/PMC7699818/ /pubmed/33233635 http://dx.doi.org/10.3390/pharmaceutics12111119 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Gyürkés, Martin Madarász, Lajos Köte, Ákos Domokos, András Mészáros, Dániel Beke, Áron Kristóf Nagy, Brigitta Marosi, György Pataki, Hajnalka Nagy, Zsombor Kristóf Farkas, Attila Process Design of Continuous Powder Blending Using Residence Time Distribution and Feeding Models |
title | Process Design of Continuous Powder Blending Using Residence Time Distribution and Feeding Models |
title_full | Process Design of Continuous Powder Blending Using Residence Time Distribution and Feeding Models |
title_fullStr | Process Design of Continuous Powder Blending Using Residence Time Distribution and Feeding Models |
title_full_unstemmed | Process Design of Continuous Powder Blending Using Residence Time Distribution and Feeding Models |
title_short | Process Design of Continuous Powder Blending Using Residence Time Distribution and Feeding Models |
title_sort | process design of continuous powder blending using residence time distribution and feeding models |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7699818/ https://www.ncbi.nlm.nih.gov/pubmed/33233635 http://dx.doi.org/10.3390/pharmaceutics12111119 |
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