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Port congestion significantly impacts the reliability of container ship schedules. However, the existing research often treats vessel time in port as a random variable, failing to systematically consider the complex impact of port congestion on ship schedules. This study addresses the issue of container ship schedule design under port congestion. Vessel waiting times in ports are predicted and quantified by queueing theory, along with information on vessel schedules, cargo handling volumes, and available port operating time windows. We propose a mechanism for selecting container handling efficiencies for arriving vessels, thereby determining their in-port handling times. By jointly considering the uncertainty of vessel waiting and handling times in port, we establish a mixed-integer nonlinear programming model aimed at minimizing the total cost of liner transportation services. We linearize the model and solve it using CPLEX, ultimately devising a robust ship schedule. A simulation analysis is conducted on a real liner shipping route from Asia to the Mediterranean, revealing that extreme weather events, geopolitical conflicts, and other factors can lead to severe congestion at certain ports, necessitating timely adjustments to vessel schedules by shipping companies. Moreover, such events can impact the marine fuel market, prompting shipping companies to adopt strategies such as increasing vessel numbers and reducing vessel speeds in response to high fuel prices. Additionally, the container handling efficiency selection mechanism based on information sharing enables shipping companies to flexibly design liner schedules, balancing the economic costs and service reliability of container liner transportation.

Abstract Percolation is a common extraction method of food processing industry. In this work, taking the percolation extraction of salvianolic acid B from Salvia miltiorrhiza (Salviae Miltiorrhizae Radix et Rhizoma) as an example, the percolation mechanism model was derived. The volume partition coefficient was calculated according to the impregnation. experiment. The bed layer voidage was measured by single-factor percolation experiment and the internal mass transfer coefficient was calculated by the parameters obtained by fitting the impregnation kinetic model. After screening, the Wilson and Geankoplis, and Koch and Brady formulas were used to calculate the external mass transfer coefficient and the axial diffusion coefficient, respectively. After substituting each parameter into the model, the process of percolation of Salvia miltiorrhiza was predicted, and the coefficient of determination R2 was all greater than 0.94. Sensitivity analysis was used to show that all the parameters studied had a significant impact on the prediction effect. Based on the model, the design space including the range of raw material properties and process parameters was established and successfully verified. At the same time, the model was applied to the quantitative extraction and endpoint prediction of the percolation process.

Abstract The present work reports developing the first process analytical technology (PAT)-based real-time feedback control system for maintaining the Ginkgo biloba leaf dripping pills weight during manufacturing. The opening degree of the drop valve and the weight of dripping pills were chosen as the manipulated variable and as the controlled variable, respectively. A proportional-integral controller was programmed to automatically reach the desired dripping pills weight by adjusting the opening degree of the drop valve. The closed-loop feedback control system could automatically compensate for the disturbances and ensure a predefined weight of the dripping pills with excellent robustness, high accuracy, and high efficiency during manufacturing. Furthermore, the closed-loop feedback control system improved the process capability of the dripping process, and the process capability index was > 1.67. This study provides a new approach to real-time control of the weight of dripping pills and improves the process capability during Ginkgo biloba leaf dripping pills manufacturing.

Abstract Process analysis and monitoring during the manufacturing of the dripping pills are essential. However, research on developing sensor‐based technology or process analytical technology (PAT) tools to analyze and monitor the dripping process is minimal. The purpose of this work is to develop a fast and non‐destructive laser detection system for quantitative visualization of droplets, which involves detecting the size of the droplet and calculating the weight of the dripping pills during the dripping process. Several factors influencing the detection performance of the detection system and the detection system capability for quantitation of the pill weight were explored. The laser detection system accurately detects the weight of the dripping pills with the coefficients of determination (R2) higher than 0.99. It was also robust concerning the variation in critical process parameters and critical material attributes. Furthermore, the laser detection system was successfully applied to the production line of Ginkgo biloba leaf dripping pills to monitor the dripping pills weight. The proposed laser detection system can analyze and monitor the dripping process in dripping pill manufacturing with stable performance, high accuracy, and high efficiency.

A novel approach was developed to detect bed fluidity in gas–solid fluidized beds using diffuse reflectance near-infrared (NIR) spectroscopy. Because the flow dynamics of gas and solid phases are closely associated with the fluidization state, the fluidization quality can be evaluated through hydrodynamic characterization. In this study, the baseline level of NIR spectra was used to quantify the voidage of the fluidized bed. Two indicators derived from the NIR baseline fluctuation profiles were investigated to characterize bed fluidity, named bubble proportion and skewness. To establish a robust fluidity evaluation method, the relationships between the indicators and bed fluidity were investigated under different conditions firstly, including static bed height and average particle size. Then, a generalized threshold was identified to distinguish poor and good bed fluidity, ensuring that the probability of the α- and β-errors was less than 15% regardless of material conditions. The results show that both indicators were sensitive to changes in bed fluidity under the investigated conditions. The indicator of skewness was qualified to detect bed fluidity under varied conditions with a robust threshold of 1.20. Furthermore, the developed NIR method was successfully applied to monitor bed fluidity and for early warning of defluidization in a laboratory-scale fluidized bed granulation process.

Twin-screw wet granulation (TSWG) is a method of continuous pharmaceutical manufacturing and a potential alternative method to batch granulation processes. It has attracted more and more interest nowadays due to its high efficiency, robustness, and applications. To improve both the product quality and process efficiency, the process understanding is critical. This article reviews the recent work in process understanding and optimization for TSWG. Various aspects of the progress in TSWG like process model construction, process monitoring method development, and the strategy of process control for TSWG have been thoroughly analyzed and discussed. The process modeling technique including the empirical model, the mechanistic model, and the hybrid model in the TSWG process are presented to increase the knowledge of the granulation process, and the influence of process parameters involved in granulation process on granule properties by experimental study are highlighted. The study analyzed several process monitoring tools and the associated technologies used to monitor granule attributes. In addition, control strategies based on process analytical technology (PAT) are presented as a reference to enhance product quality and ensure the applicability and capability of continuous manufacturing (CM) processes. Furthermore, this article aims to review the current research progress in an effort to make recommendations for further research in process understanding and development of TSWG.

The continuous twin-screw wet granulation (TSWG) process was investigated and optimized with prediction-oriented I-optimal designs. The I-optimal designs can not only obtain a precise estimation of the parameters that describe the effect of five input process parameters, including the screw speed, liquid-to-solid (L/S) ratio, TSWG feed rate, and numbers of the 30° and 60° mixing elements, on the granule quality in a TSWG process, but it can also provide a prediction of the response to determine the optimum operating conditions. Based on the constraints of the desired granule properties, a design space for the TSWG was determined, and the ranges of the operating parameters were defined. An acceptable degree of prediction was confirmed through validation experiments, demonstrating the reliability and effectiveness of using the I-optimal design method to study the TSWG process. The I-optimal design method can accelerate the screening and optimization of the TSWG process.

Dammarane-type saponins (DTSs) exist in various medicinal plants, which are a class of active ingredients with effects on improving myocardial ischemia and immunomodulation. In this study, a quantitative 1H NMR method of total DTSs in herbal medicines was developed based on the analytical procedure lifecycle. In the first stage (analytical procedure design), the Ishikawa diagram and failure mode effects and criticality analysis were used to conduct risk identification and risk ranking. Plackett–Burman design and central composite design were used to screen and optimize critical analytical procedure parameter. Then, the method operable design region was obtained through modeling. In the second stage (analytical procedure performance qualification), the performance of methodological indexes was investigated based on analytical quality by design. As examples of continued procedure performance verification, the method was successfully applied to determine the total DTSs in herbal pharmaceutical preparations and botanical extracts. As a general analytical method to quantify total DTSs in medicinal plants or pharmaceutical preparations, the developed method provides a new quality control strategy for various products containing dammarane-type saponin.

The current prevention options for postmenopausal osteoporosis are very limited. E’Jiao is a collagen-rich traditional Chinese medicine with the potential to prevent osteoporosis but more comprehensive investigations are lacking. This study aimed to investigate the skeletal protective effects of E’Jiao in a rat model of osteoporosis caused by ovariectomy. Female Sprague Dawley rats (n = 42) were randomly assigned into baseline, sham, ovariectomised (OVX) control, OVX-treated with low-dose (0.26 g/kg), medium dose (0.53 g/kg) and high dose E’Jiao (1.06 g/kg), as well as calcium carbonate (1% w/v) groups. Daily treatment through oral gavage was initiated 7 days after OVX. The rats were euthanised after eight weeks of treatment. Bone mineral density and content were measured at baseline, 1 and 2 months after treatment. Blood was collected for the measurement of bone remodelling markers. Femur and tibial bones were collected for histomorphometry and biomechanical strength analysis. Untreated OVX rats showed high bone remodelling marked by the increased bone formation and bone resorption markers, as well as increased mineralising surface/bone surface ratio. In addition, osteoclast surface and single-labelled surface were increased while mineral apposition rate was reduced in the untreated OVX rats. These changes were antagonised by E’Jiao at all doses. However, the structural, cellular and biomechanical parameters were not affected by ovariectomy and treatment. In conclusion, E’Jiao prevented high bone remodelling during oestrogen deficiency but a long-term study will be required to establish its effects on structural and biomechanical changes due to oestrogen deficiency.

E’Jiao is a traditional Chinese medicine derived from donkey skin. E’Jiao is reported to suppress elevated bone remodelling in ovariectomised rats but its mechanism of action is not known. To bridge this research gap, the current study aims to investigate the effects of E’Jiao on skeletal mineralisation, osteocyte and WNT signalling inhibitors in ovariectomised rats. Female Sprague–Dawley rats (3 months old) were ovariectomised and supplemented with E’Jiao at 0.26 g/kg, 0.53 g/kg and 1.06 g/kg, or 1% calcium carbonate (w/v) in drinking water. The rats were euthanised after two months of supplementation and their bones were collected for Fourier-transform infrared spectroscopy, histomorphometry and protein analysis. Neither ovariectomy nor treatment affected the skeletal mineral/matrix ratio, osteocyte number, empty lacunar number, and Dickkopf-1 and sclerostin protein levels (p > 0.05). Rats treated with calcium carbonate had a higher Dickkopf-1 level than baseline (p = 0.002) and E’Jiao at 0.53 g/kg (p = 0.002). In conclusion, E’Jiao has no significant effect on skeletal mineralisation, osteocyte and WNT signalling inhibitors in ovariectomised rats. The skeletal effect of E’Jiao might not be mediated through osteocytes.

Background: Xiaochaihu capsule is composed of seven traditional Chinese medicines. The pharmacopoeia only focuses on the quantitative detection of baicalin, which cannot fully reflect the quality of the preparation. Some medium polar components were used to establish the fingerprint of Xiaochaihu capsule, but there was no report on the strong polar components. Methods: A high performance liquid chromatography-corona charged aerosol detection technology was used to establish a fingerprint analysis method for Xiaochaihu capsules following an analytical quality by design approach. Definitive screening designed experiments were used to optimize the method parameters. A stepwise regression method was used to build quantitative models. The method operable design region was calculated using the experimental error simulation method. Plackett–Burman designed experiments were carried out to test robustness. Results: The contents of four components were simultaneously determined. There were seven common peaks in the fingerprint. The common peak area accounted for 91.72%. Both fingerprint and quantitative analysis methods were validated as applicable in the methodology study. The quantitative fingerprint analysis method for sugar components can fill the gap in the detection of strong polar components in the existing methods. It provides a new technology for the comprehensive overall evaluation of Xiaochaihu capsule.

Abstract Ethanol precipitation is a purification process widely used in the purification of Chinese medicine concentrates. This article reviews the research progress on the process mechanism of ethanol precipitation, ethanol precipitation process application for bioactive component purification, ethanol precipitation and traditional Chinese medicine quality, ethanol precipitation equipment, critical parameters, parameter research methods, process modeling and calculation methods, and process monitoring technology. This review proposes that ethanol precipitation technology should be further developed in terms of five aspects, namely, an in-depth study of the mechanism, further study of the effects on traditional Chinese medicine quality, improvement of the quality control of concentrates, development of new process detection methods, and development of a complete intelligent set of equipment.

An in-line monitoring method for the elution process of Ginkgo biloba L. leaves using visible and near-infrared spectroscopy in conjunction with multivariate statistical process control (MSPC) was established. Experiments, including normal operating batches and abnormal ones, were designed and carried out. The MSPC model for the elution process was developed and validated. The abnormalities were detected successfully by the control charts of principal component scores, Hotelling T2, or DModX (distance to the model). The results suggested that the established method can be used for the in-line monitoring and batch-to-batch consistency evaluation of the elution process.

The objective of this study was to develop and validate a near-infrared (NIR) spectroscopy based method for in-line quantification during the second alcohol precipitation process of Astragali radix. In total, 22 calibration experiments were carefully arranged using a Box–Behnken design. Variations in the raw materials, critical process parameters, and environmental temperature were all included in the experimental design. Two independent validation sets were built for method evaluation. Validation set 1 was used for optimization. Different spectral pretreatments were compared using a “trial-and-error” approach. To reduce the calculation times, the full-factorial design was applied to determine the potential optimal combinations. Then, the best parameters for the pretreatment algorithms were compared and selected. Partial least squares (PLS) regression models were obtained with low complexity and good predictive performance. Validation set 2 was used for a thorough validation of the NIR spectroscopy method. Based on the same validation set, traditional chemometric validation and validation using accuracy profiles were conducted and compared. Conventional chemometric parameters were used to obtain the overall predictive capability of the established models; however, these parameters were insufficient for pharmaceutical regulatory requirements. Then, the method was fully validated according to the ICH Q2(R1) guideline and using the accuracy profile approach, which enabled visual and reliable representation of the future performances of the analytical method. The developed method was able to determine content ranges of 8.44–39.8% at 0.541–2.26 mg/mL, 0.118–0.502 mg/mL, 0.220–0.940 mg/mL, 0.106–0.167 mg/mL, 0.484–0.879 mg/mL, and 0.137–0.320 mg/mL for total solid, calycosin glucoside, formononetin glucoside, 9, 10-dimethoxypterocarpan glucopyranoside, 2′-dihydroxy -3′, 4′-dimethoxyisoflavan glucopyranoside, astragloside II, and astragloside IV, respectively. These ranges were specific to the early and middle stages of the second alcohol precipitation process. The method was confirmed to be capable of achieving an in-line prediction with a very acceptable accuracy. The present study demonstrates that accuracy profiles offer a potential approach for the standardization of NIR spectroscopy method validation for traditional Chinese medicines (TCMs).

Chemical imaging (CI) possesses a strong ability of pharmaceutical analysis. Its great strength relies on the integration of traditional spectroscopy (one dimension) and imaging technique (two dimensions) to generate three-dimensional data hypercubes. Data pre-processing or processing methods are proposed to analyze vast data matrixes and thereby realizing different research objectives. In this review paper, various pharmaceutical applications of quality control over the past few years are summed up in two groups of final product test and industrial utilization. The scope of “quality control” here includes traditional analytical use, process understanding and manufactural control. Finally, two major challenges about undesirable sample geometry and lengthy acquisition time are discussed for prospective commercial or industrial application.

As a health-care food and traditional Chinese medicine, E'jiao, from the skin of Equus animus L, has been used to nourish blood in China for more than 2000 years. In modern medicine, there are also evidences indicate it has a beneficial effect on chemotherapy-caused blood deficiency. However, its mechanism of action for blood invigoration remains unclear. In the present study, we investigated the hematopoietic effect of E'jiao in 5-Fluorouracil-treated mice. In addition to the counting of bone marrow nucleated cells (BMNCs), flow cytometry was used to detect the population of hematopoietic stem cells (HSCs), and colony-forming unit (CFU) was used to assay the differentiation ability of hematopoietic progenitor cells (HPCs). Gene expression profiles of bone marrow cells were obtained from RNA sequencing (RNA-seq) and differentially expressed genes (DEGs) were analyzed with an emphasis on hematopoiesis-related pathways. The results show that E'jiao promotes the proliferation of both BMNCs and HSCs, as well as the differentiation of HPCs. By providing a hematopoiesis-related molecular regulatory network of E'jiao, we point out that the mechanism of E'jiao is associated with pathways including ECM-receptor interaction, Wnt signaling pathway, PI3K-Akt signaling pathway, TGF-beta signaling pathway, Hematopoietic cell lineage and Osteoclast differentiation, in which Ibsp, Col1a1, Col1a2, Notum, Sost, Dkk1, Irx5, Irx3 and Dcn are the key regulatory molecules. These findings provide valuable molecular basis for the mechanism of action of E'jiao.

(1) Background: Ethanol precipitation is widely used in the manufacturing traditional Chinese medicines (TCMs). Insufficient mixing of ethanol solution and concentrate usually results in the coating loss of active ingredients. However, there is no index for quantitative evaluation of the mixing in ethanol precipitation. Therefore, this study aimed to define an index for quantitative evaluation of the mixing effect in ethanol precipitation of TCMs. (2) Methods: The concept and requirements of a mixing indicator were proposed. The mass percentage of concentrate fully mixed with ethanol solution (well-mixing ratio, WMR) was used as an index to evaluate the mixing effect. The formula for calculation of WMR was derived. The utility of the WMR was evaluated on stirring devices and a micromesh mixer. (3) Results: Increasing stirring speed, decreasing total solid content of the concentrate, and decreasing the diameter of the ethanol solution droplets all resulted in higher retention rates for lobetyolin and higher WMR. The WMR increased with the increasing flow rate of the concentrate and ethanol solution in the micromesh mixer. The mixing of ethanol solution and concentrate was better when using a micromesh mixer with a smaller internal mixing zone. The results revealed that WMR could be used to quantitatively characterize the mixing of concentrate and ethanol solution, although it has some limitations. (4) Conclusions: The proposed index WMR could guide quality control of the TCM ethanol precipitation process. This study represents a new contribution to improving ethanol precipitation equipment, optimizing process parameters, and enhanced properties of concentrate for TCM enterprises.

The optimization of process parameters in the pharmaceutical industry is often carried out according to the Quality by Design (QbD) concept. QbD also emphasizes that continuous improvement should be performed in life cycle management. Process parameters that are difficult to control in actual production can be regarded as noise parameters. In this study, based on the QbD concept, the ethanol precipitation process of Carthami Flos extract was optimized, considering a noise parameter. The density of the concentrated extract, ethanol concentration, the volume ratio of ethanol to concentrated extract, stirring time after ethanol addition, and refrigeration temperature were selected as critical process parameters (CPPs), using a definitive screening design. The mathematical models among CPPs and evaluation indicators were established. Considering that the refrigeration temperature of industrial ethanol precipitation is often difficult to control with seasonal changes, refrigeration temperature was treated as a noise parameter. A calculation method for the design space in the presence of the noise parameter was proposed. The design space was calculated according to the probability of reaching the standards of evaluation indicators. Controlling parameters within the design space was expected to reduce the influence of noise parameter fluctuations on the quality of the ethanol precipitation supernatant. With more data obtained, the design space was updated. In industry, it is also recommended to adopt a similar idea: that is, continuing to collect industrial data and regularly updating mathematical models, which can further update the design space and make it more stable and reliable.

As unsafe components in herbal medicine (HM), saccharides can affect not only the drug appearance and stabilization, but also the drug efficacy and safety. The present study focuses on the in-line monitoring of batch alcohol precipitation processes for saccharide removal using near-infrared (NIR) spectroscopy. NIR spectra in the 4000–10,000-cm−1 wavelength range are acquired in situ using a transflectance probe. These directly acquired spectra allow characterization of the dynamic variation tendency of saccharides during alcohol precipitation. Calibration models based on partial least squares (PLS) regression have been developed for the three saccharide impurities, namely glucose, fructose, and sucrose. Model errors are estimated as the root-mean-square errors of cross-validation (RMSECVs) of internal validation and root-mean-square errors of prediction (RMSEPs) of external validation. The RMSECV values of glucose, fructose, and sucrose were 1.150, 1.535, and 3.067mg⋅mL−1, and the RMSEP values were 0.711, 1.547, and 3.740mg⋅mL−1, respectively. The correlation coefficients (r) between the NIR predictive and the reference measurement values were all above 0.94. Furthermore, NIR predictions based on the constructed models improved our understanding of sugar removal and helped develop a control strategy for alcohol precipitation. The results demonstrate that, as an alternative process analytical technology (PAT) tool for monitoring batch alcohol precipitation processes, NIR spectroscopy is advantageous for both efficient determination of quality characteristics (fast, in situ, and requiring no toxic reagents) and process stability, and evaluating the repeatability.

The modeling of the minimum fluidization velocity (U0mf) and the incipient fluidization pressure drop (ΔPmf) is a valuable research topic in the fluidization field. In this paper, first, a series of experiments are carried out by changing the particle size and material mass to explore their effects on U0mf and ΔPmf. Then, an Ergun equation modifying method and the dimensional analysis method are used to obtain the modeling correlations of U0mf and ΔPmf by fitting the experimental data, and the advantages and disadvantages of the two methods are discussed. The experimental results show that U0mf increases significantly with increasing particle size but has little relationship with the material mass; ΔPmf increases significantly with increasing material mass but has little relationship with the particle size. Experiments with small particles show a significant increase at large superficial gas velocity; we propose a conjecture that the particles’ collision with the fluidization chamber’s top surface causes this phenomenon. The fitting accuracy of the modified Ergun equation is lower than that of the dimensionless model. When using the Ergun equation modifying method, it is deduced that the gas drag force is approximately 0.8995 times the material total weight at the incipient fluidized state.

Although multiple bioactive components have been identified in Fufang E’jiao Jiang (FEJ), their hematopoietic effects and molecular mode of action in vivo are still not fully understood. In the current study, we analyzed the effects of martynoside, R-notoginsenoside R2 (R2), and 20S-ginsenoside Rg2 (Rg2) in a 5-fluorouracil-induced myelosuppression mouse model. Bone marrow nucleated cells (BMNCs) counts, hematopoietic progenitor cell colony-forming unit (CFU) assay, as well as flow cytometry analysis of Lin-/c-kit+/Sca-1+ hematopoietic stem cell (HSC) population were conducted, and bone marrow cells were subjected to RNA sequencing. The transcriptome data were processed based on the differentially expressed genes. The results of the analysis show that each of the three compounds stimulates BMNCs and HSC growth, as well as burst-forming unit-erythroid and colony-forming unit granulocyte-monocyte colony expansion. The most relevant transcriptional changes appeared to be involved in regulation of hematopoietic cell lineage, NF-κB and TNF-α signaling, inhibition of inflammation, and acceleration of hematopoietic cell recovery. Notably, the individual compounds shared similar but specified transcriptome profiles. Taken together, the hematopoietic effects for the three tested compounds of FEJ are confirmed in this myelosuppression mouse model. The transcriptome maps of these effects provide valuable information concerning their underlying mechanisms and provide a framework for the continued study of the complex mode of action of FEJ.

The aim of this study was to present a novel analytical quality by design (AQbD) approach for developing an HPLC method to analyze herbal extracts. In this approach, critical method attributes (CMAs) and critical method parameters (CMPs) of the analytical method were determined using the same data collected from screening experiments. The HPLC-ELSD method for separation and quantification of sugars in Codonopsis Radix extract (CRE) samples and Astragali Radix extract (ARE) samples was developed as an example method with a novel AQbD approach. Potential CMAs and potential CMPs were found with Analytical Target Profile. After the screening experiments, the retention time of the D-glucose peak of CRE samples, the signal-to-noise ratio of the D-glucose peak of CRE samples, and retention time of the sucrose peak in ARE samples were considered CMAs. The initial and final composition of the mobile phase, flow rate, and column temperature were found to be CMPs using a standard partial regression coefficient method. The probability-based design space was calculated using a Monte-Carlo simulation method and verified by experiments. The optimized method was validated to be accurate and precise, and then it was applied in the analysis of CRE and ARE samples. The present AQbD approach is efficient and suitable for analysis objects with complex compositions.

The alkaline ethanol precipitation process is investigated as an example of a technique for the removal of tannins extracted from Salviae miltiorrhizae Radix et Rhizoma for the manufacture of Danshen injection. More than 90% of the tannins can be removed. However, the recoveries of danshensu, rosmarinic acid, and salvianolic acid B were less than 60%. Total tannin removal increased as the refrigeration temperature decreased or the amount of NaOH solution added increased. Phenolic compound recoveries increased as refrigeration temperature increased or the amount of NaOH solution added decreased. When operated at a low refrigeration temperature, a relative high separation selectivity can be realized. Phenolic compound losses and tannin removal were mainly caused by precipitation. The formation of phenol salts, whose solubility is small in the mixture of ethanol and water used, is probably the reason for the precipitation. A model considering dissociation equilibrium and dissolution equilibrium was established. Satisfactory correlation results were obtained for phenolic compound recoveries and total tannin removal. Two important parameters in the model, which are the water content and pH value of alkaline supernatant, are suggested to be monitored and controlled to obtain high batch-to-batch consistency.

A preparation process of salvianolic acid B (SAB) disodium salt from Salvia miltiorrhiza Bunge (Danshen) is provided in this work. A water extract quality standard was also developed to estimate the influences of Danshen quality on SAB disodium salt quality at an early stage of the preparation process. Crude SAB solution was obtained after water extraction, concentration, acidification, 1-butanol extraction, water washing, basification, and water back extraction. Extraction temperature, extraction pH, and back-extraction pH were identified to be key parameters for the preparation of crude SAB solution. These parameters were optimized with Box–Behnken designed experiments. Crude SAB solution was further purified with a chromatography process. AMBERCHROW CG161M resin was selected as the best adsorbent. SAB disodium salt could be obtained by drying the eluate. Considering the quality of Danshen may affect the purity and yield of SAB disodium salt, different batches of Danshen were used to prepare SAB disodium salt with the optimized parameters. Water extract indices of phenolic compound purity and phenolic compound yield were measured. By developing models between SAB disodium salt purity and yield with water extract indices, the quality standard of Danshen water extract was obtained. The application of water extract quality standards can improve the quality consistency of SAB disodium salt. The effects of different batches of Danshen raw materials on the final product could be evaluated at the beginning of production stages. The present method could prepare about five grams of high-purity SAB disodium salt (>95%) in one preparation cycle. The method reported in this work can also be used to develop process intermediate quality standards for other natural products.

A novel quantitative 1H NMR (Q-NMR) combined with HPLC-MS method has been proposed for investigating the degradation process of traditional Chinese medicine (TCM) components. Through this method, in-situ monitoring of dynamics degradation process of lithospermic acid (LA), one of the popular polyphenolic acids in TCM, was realized under low oxygen condition. Additionally, this methodology was proved to be simple, rapid and specific. Degradation kinetic runs have been carried out to systematically investigate the effects of two key environmental factors, initial pH values and temperatures. Eight main degradation products of LA were detected, seven of which were tentatively structural elucidated with the help of both NMR and LC-MS in this work and salvianolic acid A (Sal A) was the primary degradation product of LA. A possible degradation pathway of LA was proposed, subsequently. The results showed that the degradation of LA followed pseudo-first-order kinetics. The apparent degradation kinetic constants increased as the initial pH value of the phosphate buffer increased. Under the given conditions, the rate constants of overall degradation as a function of temperature obeyed the Arrhenius equation. Our results proved that the Q-NMR combined with HPLC-MS method can be one of the most promising techniques for investigating degradation process of active components in TCM.

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 10,000 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.

Homogeneity of powder blend is essential to obtain uniform contents for the tablets and capsules. Near-infrared (NIR) spectroscopy with fiber-optic probe was used as an on-line technique for monitoring the homogeneity of pharmaceutical blend during the blending process instead of the traditional techniques, such as high performance liquid chromatograph (HPLC) method. In this paper NIRS with a SabIR diffuse reflectance fiber-optic probe was used to monitor the blending process of coptis powder and lactose (excipient) with different contents, and further qualitative methods, like similarity, moving block of standard deviation and mean square were used for calculation purposes with the collected spectra after the pretreatment of multiplicative signal correction (MSC) and second derivative. Correlation spectrum was used for the wavelength selection. Four different coptis were blended with lactose separately to validate the proposed method, and the blending process of "liu wei di huang" pill was also simulated in bottles to verify this method on multiple herbal blends. The overall results suggest that NIRS is a simple, effective and noninvasive technique can be successfully applied to the determination of homogeneity in the herbal blend.

A discriminant analysis technique using wavelet transformation (WT) and influence matrix analysis (CAIMAN) method is proposed for the near infrared (NIR) spectroscopy classification. In the proposed methodology, NIR spectra are decomposed by WT for data compression and a forward feature selection is further employed to extract the relevant information from the wavelet coefficients, reducing both classification errors and model complexity. A discriminant-CAIMAN (D-CAIMAN) method is utilized to build the classification model in wavelet domain on the basis of reduced wavelet coefficients of spectral variables. NIR spectra data set of 265 salviae miltiorrhizae radix samples from 9 different geographical origins is used as an example to test the classification performance of the algorithm. For a comparison, k-nearest neighbor (KNN), linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) methods are also employed. D-CAIMAN with wavelet-based feature selection (WD-CAIMAN) method shows the best performance, achieving the total classification rate of 100% in both cross-validation set and prediction set. It is worth noting that the WD-CAIMAN classifier also shows improved sensitivity, selectivity and model interpretability in the classifications.

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.

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.