Control the effects caused by noise parameter fluctuations to improve pharmaceutical process robustness: A case study of design space development for an ethanol precipitation process

Gong, Xingchu; Yao, Li; Guo, Zheng-Tai; Qu, Haibin

doi:10.1016/j.seppur.2014.05.014

Cited by 20 publications

(12 citation statements)

References 37 publications

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“…Familiar variation rules were observed in most of other chemical markers, including acetate, malonate, fructose, sucrose, ra nose, stachyose, mannotriose, DSS, LA, RA, SaB, SaA. Changing rules of several phenolic acids studied in this article were consistent with previous reports 12,14,15 . In the model of PA, the values of R 2 are less than 0.5, which suggests that the models cannot explain most of the variability in the observed data and show signi cant lack of t. According to the original data, in the most processes of ethanol precipitation, retention ratio of PA kept more than 0.8, indicating PA owned less risk of uctuation during the ethanol precipitation progress and was an easy-to-control indicator of ethanol precipitation, although it suffered loss to some extent.…”

Section: Mlr For Ethanol Precipitation Process Modeling and Understansupporting

confidence: 91%

“…The knowledge of the compounds affected by this process is an important part of the research and development of HMs. To understand the process of ethanol precipitation, numerous studies have tested how precipitation conditions, such as temperature, ethanol consumption, concentration of ethanol, stirring speed and the attributes of materials, affect the process performance in recently years [11][12][13][14][15][16] . Most of these studies focused on the retention of one or a few bioactive compounds, impurity removal rate, and other performance attributes of precipitation.…”

Section: Introductionmentioning

confidence: 99%

“…According to our previous research, ethanol precipitation was identi ed as the critical control point in the multi-step manufacturing chain of Danshen preparation 27 . However, most of the previous studies for ethanol precipitation were focused on improving the retention rate of a few important activity compounds, and indirectly controlling the retention of impurities by controlling the retention of total solids or total sugars without individualized indicators [11][12][13][14][15][16] . A comprehensive investigation of the retention trend of various metabolites in ethanol precipitation have not come up to realize deep understanding of the process, which is a research gap in process quality control of ethanol precipitation.…”

Section: Introductionmentioning

confidence: 99%

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Process characterization for ethanol precipitation of Salviae Miltiorrhizae Radix et Rhizoma using 1H NMR spectroscopy and chemometrics

Zhao

Pan

et al. 2020

Preprint

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Background Quality control of the herbal medicines (HMs) still hits technical bottlenecks due to their complicated multi-step pharmaceutical processes. Nuclear magnetic resonance (NMR) spectroscopy could serve as a powerful technique able to obtain comprehensive information of chemical compounds in the manufacturing process of HMs by a single analytical test. In this study, ethanol precipitation of Salvia miltiorrhiza Radix et Rhizoma (Danshen in China), a critical purification process of a particularly commonly used herbal medicinal material, was employed as the research subject. Methods Processed with different variables, including ethanol-material ratio, apparent ethanol concentration and moisture concentration of the raw material, 40 lab-scale experiments of ethanol precipitation were orchestrated by a full factor design with additional central composite circumscribed experiments. After 1H NMR tests, chemometrics methods, including orthogonal partial least squares-discriminant analysis (OPLS-DA), principle component analysis (PCA) and multiple linear regression (MLR), were applied to analyze the spectra of samples. Results 16 metabolites were recognized as the most critical potential chemical markers in the process of Danshen ethanol precipitation by 1H NMR spectra and OPLS-DA, including γ-aminobutyrate, pyroglutamate, succinate, acetate, malonate, fructose, sucrose, raffinose, stachyose, mannotriose, danshensu, lithospermic acid, protocatechuic aldehyde, rosmarinic acid, salvianolic acid A and B. PCA reasonably distinguished all the process intermediates as a function of different process variables adopted during the ethanol precipitation. MLR made the statistical interpretation by quadratic equations to characterize how do significant variables affect the chemical markers. Conclusions Our study indicates that NMR can track detailed potential chemical markers of ethanol precipitation process, which could promote the further understanding of ethanol precipitation process and open up possibilities to develop a more effective process quality control and consistency evaluation methodology of an HM, through providing a more in-depth and improved theoretical process understanding and characterization.

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Section: Mlr For Ethanol Precipitation Process Modeling and Understansupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Process characterization for ethanol precipitation of Salviae Miltiorrhizae Radix et Rhizoma using 1H NMR spectroscopy and chemometrics

Zhao

Pan

et al. 2020

Preprint

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“…Peterson et al gave several examples using the Bayesian predictive method to calculate the probability-based design space [ 4 , 12 ]. Our group developed design spaces for the ethanol precipitation process [ 13 ], the water precipitation process [ 14 ], and the extraction process [ 15 ] using a Monte Carlo simulation method. The Monte Carlo simulation method was also used successfully in the design space development for several analytical methods [ 16 – 19 ].…”

Section: Introductionmentioning

confidence: 99%

Design Space Development for the Extraction Process of Danhong Injection Using a Monte Carlo Simulation Method

Gong

Chen

et al. 2015

PLoS ONE

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A design space approach was applied to optimize the extraction process of Danhong injection. Dry matter yield and the yields of five active ingredients were selected as process critical quality attributes (CQAs). Extraction number, extraction time, and the mass ratio of water and material (W/M ratio) were selected as critical process parameters (CPPs). Quadratic models between CPPs and CQAs were developed with determination coefficients higher than 0.94. Active ingredient yields and dry matter yield increased as the extraction number increased. Monte-Carlo simulation with models established using a stepwise regression method was applied to calculate the probability-based design space. Step length showed little effect on the calculation results. Higher simulation number led to results with lower dispersion. Data generated in a Monte Carlo simulation following a normal distribution led to a design space with a smaller size. An optimized calculation condition was obtained with 10000 simulation times, 0.01 calculation step length, a significance level value of 0.35 for adding or removing terms in a stepwise regression, and a normal distribution for data generation. The design space with a probability higher than 0.95 to attain the CQA criteria was calculated and verified successfully. Normal operating ranges of 8.2-10 g/g of W/M ratio, 1.25-1.63 h of extraction time, and two extractions were recommended. The optimized calculation conditions can conveniently be used in design space development for other pharmaceutical processes.

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“…Monte-Carlo and Bayesian methods are commonly used to calculate this probability [11] – [13] . Recently, ethanol precipitation and water precipitation, two separation processes that are widely applied in the manufacturing of botanical drugs [14] , [15] , have been successfully optimized according to the QbD paradigm.…”

Section: Introductionmentioning

confidence: 99%

Optimization of the Ethanol Recycling Reflux Extraction Process for Saponins Using a Design Space Approach

et al. 2014

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A solvent recycling reflux extraction process for Panax notoginseng was optimized using a design space approach to improve the batch-to-batch consistency of the extract. Saponin yields, total saponin purity, and pigment yield were defined as the process critical quality attributes (CQAs). Ethanol content, extraction time, and the ratio of the recycling ethanol flow rate and initial solvent volume in the extraction tank (RES) were identified as the critical process parameters (CPPs) via quantitative risk assessment. Box-Behnken design experiments were performed. Quadratic models between CPPs and process CQAs were developed, with determination coefficients higher than 0.88. As the ethanol concentration decreases, saponin yields first increase and then decrease. A longer extraction time leads to higher yields of the ginsenosides Rb1 and Rd. The total saponin purity increases as the ethanol concentration increases. The pigment yield increases as the ethanol concentration decreases or extraction time increases. The design space was calculated using a Monte-Carlo simulation method with an acceptable probability of 0.90. Normal operation ranges to attain process CQA criteria with a probability of more than 0.914 are recommended as follows: ethanol content of 79–82%, extraction time of 6.1–7.1 h, and RES of 0.039–0.040 min−1. Most of the results of the verification experiments agreed well with the predictions. The verification experiment results showed that the selection of proper operating ethanol content, extraction time, and RES within the design space can ensure that the CQA criteria are met.

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Control the effects caused by noise parameter fluctuations to improve pharmaceutical process robustness: A case study of design space development for an ethanol precipitation process

Cited by 20 publications

References 37 publications

Process characterization for ethanol precipitation of Salviae Miltiorrhizae Radix et Rhizoma using 1H NMR spectroscopy and chemometrics

Process characterization for ethanol precipitation of Salviae Miltiorrhizae Radix et Rhizoma using 1H NMR spectroscopy and chemometrics

Design Space Development for the Extraction Process of Danhong Injection Using a Monte Carlo Simulation Method

Optimization of the Ethanol Recycling Reflux Extraction Process for Saponins Using a Design Space Approach

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