Optimization of the Ethanol Recycling Reflux Extraction Process for Saponins Using a Design Space Approach
Optimization of the Ethanol Recycling Reflux Extraction Process for Saponins Using a Design Space Approach
Xingchu Gong 0
Ying Zhang 0
Jianyang Pan 0
Haibin Qu 0
0 Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University , Hangzhou, 310058 , China
A solvent recycling reflux extraction process for Panax notoginseng was optimized OPEN ACCESS using a design space approach to improve the batch-to-batch consistency of the CHit(a2t0io1n4): OGpotnimgizXa,tiZohnaonfgthYe,PEathnaJn,oQlRuecycling extract. Saponin yields, total saponin purity, and pigment yield were defined as the RDeefsluigxnESxptraaccetioAnppPrrooaccehs.sPfoLroSSaOpNonEin9s(1U2s)i:ng a process critical quality attributes (CQAs). Ethanol content, extraction time, and the e114300. doi:10.1371/journal.pone.0114300 ratio of the recycling ethanol flow rate and initial solvent volume in the extraction Editor: Qinghui Zhang, University of Nebraska tank (RES) were identified as the critical process parameters (CPPs) via Medical Center, United States of America quantitative risk assessment. Box-Behnken design experiments were performed. Received: September 2, 2014 Quadratic models between CPPs and process CQAs were developed, with Accepted: November 8, 2014 determination coefficients higher than 0.88. As the ethanol concentration Published: December 3, 2014 decreases, saponin yields first increase and then decrease. A longer extraction Copyright: 2014 Gong et al. This is an open- time leads to higher yields of the ginsenosides Rb1 and Rd. The total saponin purity aCcrceeastisvearCtiocmlemdoisntrsibAuttterdibuutniodnerLitcheentseer,mwshoicfhthe increases as the ethanol concentration increases. The pigment yield increases as permits unrestricted use, distribution, and repro- the ethanol concentration decreases or extraction time increases. The design dauncdtisoonuirnceanayremcerdeiudmite,dp.rovided the original author space was calculated using a Monte-Carlo simulation method with an acceptable Data Availability: The authors confirm that all data probability of 0.90. Normal operation ranges to attain process CQA criteria with a underlying the findings are fully available without probability of more than 0.914 are recommended as follows: ethanol content of 79restriction. All relevant data are within the paper. 82%, extraction time of 6.1-7.1 h, and RES of 0.039-0.040 min21. Most of the FSu&nTdMinagjo:rThPirsowjeocrtkowfaCshisnuapp(2o0rt1e2dZbXy09th1e01N2a0ti1o-nal results of the verification experiments agreed well with the predictions. The 003) and Research Fund for the Doctoral Program verification experiment results showed that the selection of proper operating oHfaHibiignhQeruErdeucceaivteiodntohfeCfihrsintafu(n2d0.1T10h1e0w11e2b0s1it4e9i)s. ethanol content, extraction time, and RES within the design space can ensure that t(hhettps:e//cwownwd.mfunodst..gTohve.cwne/)b.sXitiengisch(huttGp:o//nwgwwre.cceuitveecdh. the CQA criteria are met. edu.cn/cn/kyjj/gdxxbsdkyjj/A010301index_1.htm). Funds were used to buy materials, chemicals, and pay labor costs. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Solvent recycling reflux extraction is an extraction process wherein extraction and
concentration are conducted simultaneously . The extract in the extraction
tank is pumped out and concentrated in the concentration tank during the
extraction process; meanwhile, the evaporated solvent is condensed and pumped
back into the extraction tank. Compared with the conventional heat reflux
extraction, solvent recycling reflux extraction has several advantages . Because
the solvent is renewed in the extraction, the mass transfer driving force is greater,
which leads to a shorter extraction time. The reuse of the solvent in the extraction
also decreases the amount of solvent needed. In addition, no storage tank is
required before the concentration process, which can reduce the fixed investment.
The high efficiency of the solvent recycling reflux extraction process was verified
in the extraction of polysaccharides from Grifola frondosa  and the preparation
of Jianwei Xiaozhang pills , Xinmaikang tablets , and other botanical
extracts . Because of these advantages, solvent recycling reflux extraction is
increasingly applied to extract botanical components in botanical medicine
factories to lower costs.
In addition to economic considerations, botanical drug quality is important for
botanical drug manufacturers. Because of the complexity of the compositions of
botanical extracts, maintaining batch-to-batch consistency is a challenging task.
Quality by design (QbD) is a paradigm that has recently been used to improve the
batch-to-batch consistency of the pharmaceutical process based on risk
management and knowledge management [5, 6]. In the implementation of the
QbD concept, steps including critical quality attribute (CQA) definition, risk
assessment, critical process parameter (CPP) determination, design space
development, control strategy design, and continual improvement in the product
lifecycle are required [7, 8]. The design space is a region for the control of process
parameters. When the parameters vary within this region, the change in the
process product quality can be neglected . To determine the design space,
mathematical models between CQAs and CPPs are required. Experimental design
is often applied to establish the models . To quantify the ability of the design
space to keep the CQAs within the desired ranges, the probability of attaining the
CQA ranges must be calculated . Monte-Carlo and Bayesian methods are
commonly used to calculate this probability . 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.
To realize a solvent recycling reflux extraction process with high batch-to-batch
consistency, the extraction of Panax notoginseng was investigated. Panax
notoginseng, the root of Panax notoginseng (Burk.) F. H. Chen, is a medicinal and
edible plant in China and is used as a dietary supplement in the USA . Many
botanical drugs widely applied in China are made from Panax notoginseng, such as
Xuesaitong injections, Compound Danshen Dripping Pills, and Yunnan Baiyao.
In this work, the extraction process was optimized using a design space approach
 consisting of CQA definition, risk assessment, CPP determination, design
space development and verification. The CQAs of the extraction process were
defined, and the CPPs were identified via risk assessment. Quantitative models
were developed between CQAs and CPPs. The influences of different parameters
were discussed. The probability-based design space was calculated using a
MonteCarlo method. Finally, the design space was verified.
Methods and Materials
Materials and chemicals
Panax notoginseng was collected from Wenshan of Yunnan Province (China). No
specific permissions were required for the described field studies. The locations
are neither privately owned nor protected by the Chinese government. No
endangered or protected species were sampled. The specific location of this study
is longitude: 120.07E, latitude: 30.28N. Standards of the notoginsenoside R1,
ginsenoside Rg1, ginsenoside Rb1, and ginsenoside Rd were purchased from
Shanghai Winherb Pharmaceutical Technology Development Co., Ltd. (Shanghai,
China). Acetonitrile (HPLC grade) and methanol (HPLC grade) were obtained
from Merck (Darmstadt, Germany). Formic acid (HPLC grade) was purchased
from Tedia (Darmstadt, Germany). Ethanol (analytical grade) was purchased
from Shanghai Lingfeng Chemical Reagent Co., Ltd. (Shanghai, China).
Tartrazine (HPLC grade) was purchased from Aladdin Industrial Corporation
(Shanghai, China). Glycerol (analytical grade) was purchased from China Sun
Specialty Products Co., Ltd. (Changshu, China). A Milli-Q academic water
purification system (Milford, MA, USA) was used to produce deionized water.
A schematic chart of the experimental setup is shown in Figure 1. Two
constanttemperature tanks (ZCY-15B, Ningbo Tianheng Instrument Factory, Ningbo,
China) were used to heat the extraction tank and concentration tank. The extract
in the extraction tank was pumped into the concentration tank. The solvent was
evaporated in the concentration tank and then condensed. The ethanol solution
was collected in a storage tank and then pumped back into the extraction tank
with a fixed flow rate. In this process, the saponins were kept in the concentration
tank, and the solvent was recycled. In the experiments, 50.0 g of Panax
notoginseng and 500.0 ml of ethanol-water mixture were added to the extraction
tank. After soaking for 2 h, 150 mL of extract was pumped into the concentration
Pigment yield (mg/g Panax notoginseng)
Ginsenoside Rg1 yield (mg/g Panax notoginseng)
Ginsenoside Rb1 yield(mg/g Panax notoginseng)
Ginsenoside Rd yield(mg/g Panax notoginseng)
Pigment yield(mg/g Panax notoginseng)
EV: Experimental value
PV: Predicted value.
tank at a flow rate of 25 mL/min. The flow rates of the two pumps were set to the
value required by the experimental design.
The influences of three independent variables, namely, the ethanol concentration
(v/v, X1), extraction time (h, X2), and ratio of recycling ethanol flow rate and
initial solvent volume in the extraction tank (RES, min21, X3), were investigated.
A three-variable, three-level BoxBehnken design (BBD) was employed. The
coded and uncoded values of the three independent variables are given in Table 1.
The run order of the experiments is listed in Table 2. After the design space was
developed, verification experiments with the conditions listed in Table 3 were
carried out and repeated three times.
The quantitative analysis of four saponins, namely, the notoginsenoside R1,
ginsenoside Rg1, ginsenoside Rb1, and ginsenoside Rd, was performed using
HPLC. HPLC analysis was performed on an Agilent 1260 series HPLC system with
an Acquity UPLC CSH C18 column (50 mm62.1 mm i.d, 1.7 mm). The column
temperature was maintained at 40C to keep column pressure in an acceptable
range. The standards and samples were separated using a gradient mobile phase
consisting of phase A (0.01% formic acid in deionized water) and phase B (0.01%
formic acid in acetonitrile). The gradient conditions are as follows: 06.0 min, 18
20% B; 6.06.8 min, 2030% B; 6.811.0 min, 3035% B; 11.017.0 min, 3590%
B; and 17.025.0 min, 90% B. The column was then conditioned with 18% B for
15 min. The flow rate was set at 0.35 ml/min. The injection volume was 5 mL. The
detection wavelength was set at 203 nm. The chromatogram is shown in Figure 2.
The dry matter content was determined gravimetrically using a precision
electronic balance (AB204-N, Mettler Toledo Shanghai Co., Ltd.). Before
weighing, the samples were dried at 105C in an oven (DZF-6050, Shanghai Jing
Hong Laboratory Instrument Co., Ltd.) for 3 h and then stored in a desiccator for
0.5 h. The pigment content was determined using spectrophotometry. The
absorbance of each sample was measured at 420 nm using a UV-vis
spectrophotometer (T6, Pukinje Co., Ltd., Beijing, China). The pigment yield was
calculated using tartrazine as the standard.
where C and m refer to the extract concentration and mass, respectively; subscript
i (i51 to 4) corresponds to notoginsenoside R1, ginsenoside Rg1, ginsenoside Rb1,
or ginsenoside Rd, respectively; and subscripts e and pn refer to the extract and
Panax notoginseng, respectively. The concentration of total saponin (TS) in an
extract was calculated using Equation 2.
aSeverity: 1, no impact; 2, small impact; 3, moderate impact; 4, remarkable impact.
bOccurrence: 1, seldom occur; 2, sometimes occur.
cDetection: 1, can be detected easily; 2, can be detected with difficulty.
where DM is the dry matter content of an extract. The yield of pigment (PY) was
calculated using Equation 4.
where the subscript pi represents the pigment content using tartrazine as the
Equation 5 was used to model the results of the Box-Behnken design
where Y is the response, a0 is a constant, and a1 to a9 are regression coefficients.
Logarithmic values were used in the model development for pigment yield. Design
Expert V188.8.131.52 (State-Ease Inc., MN) was used to analyze the results of the
BoxBehnken design experiments.
A self-written Matlab (R2010b, Version 7.11, MathWorks, USA) program was
used to calculate the design space using a Monte-Carlo method. In the
MonteCarlo simulation, it is hypothesized that the relative standard deviations (RSD) of
concentrations for all of the experimental results were the same as the RSD values
of the center point. In each simulation, random data following a normal
distribution were created. The simulation was carried out 50000 times to calculate
g e 2 0 89 71 *
to ta 33 012 7 4 5 9 90 57 3 7 51 05
l.tssu xaonn gR1 itsEm .6264 .922 .2180 .6312 .7561 .6660 .202 .952 .712 .012 .100 .190
the probability. The acceptable level of probability for the design space was set as
Results and Discussion
Process CQA definition
Saponins are the main bioactive components of Panax notoginseng . Saponins
possess many pharmacological activities, such as antithrombotic,
anti-atherosclerotic, fibrinolytic, antioxidant and cardioprotective activities .
Therefore, saponins are usually used as the main indices for Panax notoginseng
product evaluation [22, 23]. Ginsenoside Rg1, ginsenoside Rb1, ginsenoside Rd,
and notoginsenoside R1 are the Panax notoginseng saponins present in the highest
levels . Recently, the action mechanisms of ginsenoside Rg1, ginsenoside Rb1,
ginsenoside Rd, and notoginsenoside R1 have been found to involve multiple
targets and multiple pathways using a network-based approach . Therefore,
the yields of notoginsenoside R1, ginsenoside Rg1, ginsenoside Rb1, and
ginsenoside Rd are selected as process CQAs. Higher saponin yields are favored.
Considering that the active compound purity represents the difficulties in process
quality control , total saponin purity is considered as a process CQA. In the
extraction process, polysaccharides, pigments, salts, and other compounds will
also be extracted, which will result in an increase in the dry matter yield. The dry
matter yield is a function of saponin yield and total saponin purity, as seen in
Therefore, the dry matter yield is not defined as a CQA. Color is another index
of drug quality; therefore, pigment yield is also selected as a process CQA. A total
of six process CQAs were taken into consideration, including the four saponin
yields, total saponins purity, and pigment yield. The upper and lower limits of
CQAs are given in Table 4.
Possible critical process parameters in the ethanol recycling reflux extraction
process were identified using an Ishikawa diagram analysis, as shown in Figure 3.
The main causes of environment, material attributes, solvent, equipment, and
extraction procedure and the related sub-causes were considered.
For the further selection of critical process parameters (CPPs), a failure mode
and effects analysis (FMEA) was conducted. In this analysis, a severity ranking
from 1 to 4 is used to reflect the impact of each parameter on the process. The
occurrence probability of a failure was ranked from 1 to 2 in each parameter. The
ability to detect a failure was also ranked from 1 to 2 in each parameter. The
scores for severity, occurrence, and detectability are obtained based on literature
results and experience and are presented in Table 5. In Bai et al.s work, the effect
of the size distribution of Panax notoginseng on saponin extraction was small .
Instead, ethanol content, ethanol addition amount, and number of extractions
have been found to be significant factors [24, 28]. The risk priority number (RPN)
score was used as the criterion to identify the CPPs. The RPN was obtained by
multiplying the scores for severity, occurrence, and detectability, as shown in
Effects of CPPs on process CQAs
The results of the Box-Behnken design experiments are shown in Table 2. The
extraction yield of ginsenoside Rg1 varied from 33.17 to 48.14 mg/g Panax
notoginseng. The ginsenoside Rb1 yield ranged from 30.42 to 50.71 mg/g Panax
notoginseng. The yields of notoginsenoside R1 and ginsenoside Rd were lower than
15 mg/g Panax notoginseng. The TSP varied from 23.11% to 32.55%. The pigment
yield was between 0.14 and 7.87 mg/g Panax notoginseng.
Mathematical models were developed to describe the relationships between
CQAs and CPPs. The estimated regression coefficients are listed in Table 6.
Analysis of variance (ANOVA) was carried out, and the p-values of the parameters
are listed in Table 6. For all of the models, the determination coefficients (R2) are
higher than 0.88, which means that most of the variations of the process CQAs
can be explained by ethanol concentration, RES, and extraction time. The models
are significant, as the p-values are less than 0.05. The linear term or quadratic term
of ethanol concentration is important in all the models. The RES is also important
for all of the criteria. Extraction time is significant for Rd yield and pigment yield.
According to the models, contour plots for saponin yields can be obtained, as
given in Figures 47. As the ethanol concentration increases, the yields of all of the
saponins first increase and then decrease. A lower ethanol content means more
water in the extract, which can result in increased swelling of Panax notoginseng.
Saponins can be extracted in a shorter time when the swelling of Panax
notoginseng is greater. However, more saponins may hydrolyze when the water
content in the mixed solvent is higher because of the higher boiling temperature
[16, 18, 29, 30]. More ginsenoside Rb1 and ginsenoside Rd can be extracted using
longer extraction times. However, the yields of notoginsenoside R1 and
ginsenoside Rg1 may decrease for very long extraction times. Ginsenoside Rg1 is
the hydrolysis product of notoginsenoside R1 . The hydrolyzation of
ginsenoside Rg1 forms ginsenoside Rh1 . A higher RES leads to higher
concentration differences between Panax notoginseng and the extract for a
saponin, which accelerates the saponin extraction. Therefore, the saponin yields
increase as the RES increases.
The mass of saccharides, such as sucrose, fructose, and sucrose , was more
than 60% of the dry matter content in the water extract of Panax notoginseng .
Saccharide solubilities usually decrease as the ethanol content in the mixed
ethanol-water mixture increases . Therefore, a higher ethanol
concentration means that less saccharides will be extracted and a higher TSP can be
obtained, as seen in Figure 8. The extract is easily saturated by saccharides, but the
recycling of the ethanol solution can prevent this saturation, thereby allowing
more saccharides to be extracted. Accordingly, a lower RES also results in a higher
Maillard reaction between reducing sugars and amino acids forms aroma
compounds, ultra-violet-absorbing intermediates, and melanoidins, which results
in a darkened extract [37, 38]. Longer extraction times result in a larger amount of
Maillard reaction products. Accordingly, the pigment yield increases, as seen in
Figure 9(a) and 9(c). A lower ethanol concentration corresponds to a higher water
content in the extract and a higher extraction temperature for reflux. Water is also
a reactant in the Maillard reaction . Therefore, a lower ethanol concentration
also leads to a higher pigment yield, as seen in Figure 9(a) and 9(b).
Design space development and verification
The design space with a possibility above 0.90 of satisfying the CQA criteria is
calculated using a Monte-Carlo method. The results are shown in Figure 10(a).
The design space is irregular in shape and composed of two parts. For easier
operation, normal operation ranges are calculated, comprised of an ethanol
concentration of 7982%, extraction time of 6.17.1 h, and RES of
0.0390.040 min21. The probability of satisfying the CQA criteria is 0.914 when the
parameters are controlled within the normal operation region.
To further confirm the accuracy of the models as well as the design space,
verification experiments were carried out. The experimental conditions and
results are shown in Table 3. The conditions of Experiments V1 and V2 are plotted
in Figure 10(b). The relative deviation (RD) values between the experimental and
predicted values are calculated using Equation 7.
where VExp is the average value of the verification experimental data, and VCal is
the calculated value of the model. The RD values are less than 6% for ginsenoside
Rg1 yield, ginsenoside Rb1 yield, ginsenoside Rd yield, and TSP of the extract,
indicating that these models are accurate. The results of Experiment V1 are within
the target ranges of the CQAs. However, the yields of the four different saponins
in Experiment V2 are lower than their criteria. Thus, operation within the design
space can ensure that all CQAs are within the predefined limits.
The design space approach is applied to optimize the solvent recycling reflux
extraction process of Panax notoginseng. The notoginsenoside R1 yield,
ginsenoside Rg1 yield, ginsenoside Rb1 yield, ginsenoside Rd yield, pigment yield, and
total saponin purity in the extracts were defined as the process CQAs. An Ishikawa
diagram was applied to identify potential CPPs. Ethanol concentration, extraction
time, and RES were identified as CPPs using an FMEA model. The models
between the CPPs and process CQAs were built using quadratic models with R2
values greater than 0.88. As the ethanol concentration increases, the saponin yields
first increase and then decrease. For the ginsenosides Rb1 and Rd, a longer
extraction time leads to higher yields. The total saponin purity increases as the
ethanol concentration increases. Meanwhile, the pigment yield decreases with
increasing ethanol concentration or decreasing extraction time. The design space
was calculated via Monte-Carlo simulation using 0.90 as the acceptable
probability. Normal operation ranges were also recommended, namely, an ethanol
concentration of 7982%, extraction time of 6.17.1 h, and RES of 0.039
0.040 min21. The probability of satisfying the CQA criteria with parameters in
normal operation ranges is higher than 91.4%. The design space was verified, and
the results of the verification experiment showed that the use of operating CPPs
within the design space provides a high probability of satisfying the process CQA
Conceived and designed the experiments: HBQ XCG. Performed the experiments:
YZ JYP. Analyzed the data: XCG HBQ YZ JYP. Contributed reagents/materials/
analysis tools: HBQ XCG. Wrote the paper: XCG HBQ YZ JYP.
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