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Unit Operation Optimization for the Manufacturing of Botanical Injections Using a Design Space Approach: A Case Study of Water Precipitation

Quality by design (QbD) concept is a paradigm for the improvement of botanical injection quality control. In this work, water precipitation process for the manufacturing of Xueshuantong injection, a botanical injection made from Notoginseng Radix et Rhizoma, was optimized using a design space approa...

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Detalles Bibliográficos
Autores principales: Gong, Xingchu, Chen, Huali, Chen, Teng, Qu, Haibin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4125280/
https://www.ncbi.nlm.nih.gov/pubmed/25101624
http://dx.doi.org/10.1371/journal.pone.0104493
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author Gong, Xingchu
Chen, Huali
Chen, Teng
Qu, Haibin
author_facet Gong, Xingchu
Chen, Huali
Chen, Teng
Qu, Haibin
author_sort Gong, Xingchu
collection PubMed
description Quality by design (QbD) concept is a paradigm for the improvement of botanical injection quality control. In this work, water precipitation process for the manufacturing of Xueshuantong injection, a botanical injection made from Notoginseng Radix et Rhizoma, was optimized using a design space approach as a sample. Saponin recovery and total saponin purity (TSP) in supernatant were identified as the critical quality attributes (CQAs) of water precipitation using a risk assessment for all the processes of Xueshuantong injection. An Ishikawa diagram and experiments of fractional factorial design were applied to determine critical process parameters (CPPs). Dry matter content of concentrated extract (DMCC), amount of water added (AWA), and stirring speed (SS) were identified as CPPs. Box-Behnken designed experiments were carried out to develop models between CPPs and process CQAs. Determination coefficients were higher than 0.86 for all the models. High TSP in supernatant can be obtained when DMCC is low and SS is high. Saponin recoveries decreased as DMCC increased. Incomplete collection of supernatant was the main reason for the loss of saponins. Design space was calculated using a Monte-Carlo simulation method with acceptable probability of 0.90. Recommended normal operation region are located in DMCC of 0.38–0.41 g/g, AWA of 3.7–4.9 g/g, and SS of 280–350 rpm, with a probability more than 0.919 to attain CQA criteria. Verification experiment results showed that operating DMCC, SS, and AWA within design space can attain CQA criteria with high probability.
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spelling pubmed-41252802014-08-12 Unit Operation Optimization for the Manufacturing of Botanical Injections Using a Design Space Approach: A Case Study of Water Precipitation Gong, Xingchu Chen, Huali Chen, Teng Qu, Haibin PLoS One Research Article Quality by design (QbD) concept is a paradigm for the improvement of botanical injection quality control. In this work, water precipitation process for the manufacturing of Xueshuantong injection, a botanical injection made from Notoginseng Radix et Rhizoma, was optimized using a design space approach as a sample. Saponin recovery and total saponin purity (TSP) in supernatant were identified as the critical quality attributes (CQAs) of water precipitation using a risk assessment for all the processes of Xueshuantong injection. An Ishikawa diagram and experiments of fractional factorial design were applied to determine critical process parameters (CPPs). Dry matter content of concentrated extract (DMCC), amount of water added (AWA), and stirring speed (SS) were identified as CPPs. Box-Behnken designed experiments were carried out to develop models between CPPs and process CQAs. Determination coefficients were higher than 0.86 for all the models. High TSP in supernatant can be obtained when DMCC is low and SS is high. Saponin recoveries decreased as DMCC increased. Incomplete collection of supernatant was the main reason for the loss of saponins. Design space was calculated using a Monte-Carlo simulation method with acceptable probability of 0.90. Recommended normal operation region are located in DMCC of 0.38–0.41 g/g, AWA of 3.7–4.9 g/g, and SS of 280–350 rpm, with a probability more than 0.919 to attain CQA criteria. Verification experiment results showed that operating DMCC, SS, and AWA within design space can attain CQA criteria with high probability. Public Library of Science 2014-08-07 /pmc/articles/PMC4125280/ /pubmed/25101624 http://dx.doi.org/10.1371/journal.pone.0104493 Text en © 2014 Gong et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Gong, Xingchu
Chen, Huali
Chen, Teng
Qu, Haibin
Unit Operation Optimization for the Manufacturing of Botanical Injections Using a Design Space Approach: A Case Study of Water Precipitation
title Unit Operation Optimization for the Manufacturing of Botanical Injections Using a Design Space Approach: A Case Study of Water Precipitation
title_full Unit Operation Optimization for the Manufacturing of Botanical Injections Using a Design Space Approach: A Case Study of Water Precipitation
title_fullStr Unit Operation Optimization for the Manufacturing of Botanical Injections Using a Design Space Approach: A Case Study of Water Precipitation
title_full_unstemmed Unit Operation Optimization for the Manufacturing of Botanical Injections Using a Design Space Approach: A Case Study of Water Precipitation
title_short Unit Operation Optimization for the Manufacturing of Botanical Injections Using a Design Space Approach: A Case Study of Water Precipitation
title_sort unit operation optimization for the manufacturing of botanical injections using a design space approach: a case study of water precipitation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4125280/
https://www.ncbi.nlm.nih.gov/pubmed/25101624
http://dx.doi.org/10.1371/journal.pone.0104493
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