ArticlePloS one2014
Unit operation optimization for the manufacturing of botanical injections using a design space approach: a case study of water precipitation.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 17 citations in OpenAlex.
- Process characterization strategy for a precipitation step for host cell protein reduction.Biotechnology progress · 2020Article
- Critical pharmaceutical process identification considering chemical composition, biological activity, and batch-to-batch consistency: A case study of notoginseng total saponins.Chinese herbal medicines · 2020Article
- The development of an herbal material quality control strategy considering the effects of manufacturing processes.Chinese medicine · 2019Article
- Design space development for the extraction process of Danhong injection using a Monte Carlo simulation method.PloS one · 2015Article
- Optimization of the ethanol recycling reflux extraction process for saponins using a design space approach.PloS one · 2014Article
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4 authors at 1 institution in 1 country.
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Abstract
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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