Search

Qilong capsule (QLC) is a well-known Traditional Chinese Medicine, and it has a long history for the treatment of ischemic stroke. Its major ingredients are saponins, such as paeoniflorin, amygdalin and calycosin-7-glucoside, contributing to vasodilation function. In this study, a simple, rapid and sensitive high-performance liquid chromatography-tandem mass spectrometry method was developed to determine three bioactive ingredients in rat plasma after oral administration of QLC. A simple acetonitrile precipitation method was introduced during the sample preparation. Chromatographic separation was performed on a Shiseido CAPCELL PAC MGIII-C18 column using a gradient elution with acetonitrile and water (0.1% formic acid) as a mobile phase, and the chromatographic separation was 5 min. The methodological evaluation showed that this method had a high sensitivity (the lower limit of quantification was 1 ng/mL for calycosin-7-glucoside, 5 ng/mL for paeoniflorin, 5 ng/mL for amygdalin), satisfactory accuracy (relative error ≤ ±15%) and precision (relative standard deviation ≤15%). Then, the analytical method was applied to the pharmacokinetic study in rats following oral administration of the extracts in QLC. Meanwhile, the pharmacokinetic parameters of complex system in QLC were analyzed and the potential interaction between ingredients was explored. The present quantification method and pharmacokinetic study will provide a meaningful reference for the formulas research of QLC in the treatment of ischemic stroke. Highlight

In traditional Chinese medicine, an extract intermediate is an extracted and purified intermediary of the production process, and its quality is crucial to the efficacy of the final product. Lumbrokinase (LK), which is found in earthworm extract intermediate, has good fibrinolysis, is an anticoagulant, provides hemorheological improvement and has other pharmacological effects, and it shows significant advantages in the treatment of thromboses. The traditional method for determining lumbrokinase potency is an agarose-fibrin plate assay, but it takes more than a dozen hours to perform and requires expensive culture medium. To develop a new method for rapidly and accurately determining the potency of lumbrokinase, near-infrared (NIR) spectroscopy combined with chemometrics is presented in this study. In addition, the variable selection combination method was investigated to optimize the modeling variables and improve the predictive abilities of the NIR model. After optimization, the parameter values of the correlation coefficient, R2c, R2p, RMSEC and RMSEP, of the partial least squares regression (PLSR) quantitative model were 0.9398, 0.9340, 289.618 U, and 538.313 U, respectively. This study demonstrates that NIR analysis techniques are a potential tool for rapidly determining lumbrokinase potency in earthworm extract intermediate.

Conventional liquid chromatographic fingerprint methods with a single column lack enough selectivity and separation power for analyzing complex samples with a wide range of polarities. In this work, an HPLC fingerprint method based on the serial coupling of two columns was developed to evaluate the quality of Shen–Zhi–Ling oral liquid. Twelve batches of Shen–Zhi–Ling oral liquid were used to carry out the fingerprint analysis. Compared to 22 common peaks achieved in the fingerprint with a single column, 29 common peaks were obtained when using the serial coupling of two columns under the same conditions. Five components including albiflorin, paeoniflorin, liquiritin, cinnamic acid, and glycyrrhizic acid ammonium salt were simultaneously determined with paeoniflorin as the reference standard. The established method was validated in terms of specificity, linearity, precision, accuracy, stability, and robustness. Then the five components in 12 batches of products were successfully determined. Compared with the external standard method, the determination results showed no remarkable differences. In addition, similarity analysis and hierarchical clustering analysis combined with heatmaps were also employed to perform quality assessment. The fingerprint based on directly connecting two columns in series combined with multi-component quantitation with a single reference standard could provide a feasible and attractive approach to evaluate the quality of Shen–Zhi–Ling oral liquid.

Hyaluronic acid (HA) is a kind of biological macromolecule with strong water binding ability. It has rich biological functions and plays an important role in the living body. It has extremely high application value in the fields of medical beauty, medicine, medical treatment and food. In the past, the thinking of studying HA was rather rigid, which is reflected in the direct study of HA itself, which is quite difficult in a complex system because there are too many influencing factors in the real biological environment. The proposal of aquaphotomics allows researchers to focus on the water molecules in complex biological systems, which leads us to shift the angle of thinking about HA-related issues to the water molecules that are closely bound to it. In previous and ongoing work, we use spectroscopy technology and aquaphotomics to study water species, focus on the widely used HA and its derivatives on the market, and apply multivariate analysis methods to analyze the interaction between HA and water molecules to further clarify the material properties of HA form the basis for monitoring its process of binding water in the body. This paper briefly reviews important knowledge concerning the relationship between HA and water, and explains our past and ongoing related research in this field. Key words: hyaluronic acid, water, aquaphotomics, spectroscopy

Precipitation is a key manufacturing unit during the immunoglobulin G (IgG) production, which guarantees the quality of the final product. Ethanol is usually used to purify IgG during the precipitation process, so it is important to monitor the ethanol concentration online. Near-infrared (NIR) spectroscopy is a powerful process analytical technology (PAT) which has been proved to be feasible to determine the ethanol concentration during the precipitation process. However, the NIR model is usually established based on the specific process, so a universal model is needed. And the clarity degree of solution will affect the quality of the spectra. Therefore, in this study an integrated NIR system was introduced to establish a universal NIR model which could predict the ethanol concentration online and determine the end-point of the whole process. First, a spectra acquisition device was designed and established in order to get high-quality NIR spectra. Then, a simple prepared ethanol NIR model was constructed to predict the actual manufacturing process. Finally, the end-point was determined to stop the peristaltic pump when the ethanol concentration reached 20%. The results showed that the spectra quality was good, model prediction was accurate, and process monitoring was accurate. In conclusion, all results indicated that the integrated NIR system could be used to monitor the biopharmaceutical process to help us understand the pharmaceutical process.

Separation power was limited when the conventional high-performance liquid chromatography (HPLC) fingerprinting method based on a single column was used to analyze very complex traditional Chinese medicine (TCM) preparations. In this research, a novel HPLC fingerprinting method based on column switching technology by using a single pump was established for evaluating the quality of Tianmeng oral liquid (TMOL). Twelve batches of TMOL samples were used for constructing HPLC fingerprints. Compared with the 16 common peaks in fingerprinting with a single column, 25 common peaks were achieved with two columns connected through a six-way valve. The similarity analysis combined with bootstrap method was applied to determine the similarity threshold, which was 0.992 to distinguish expired samples and unexpired samples. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) were also applied to classify the TMOL samples, and results revealed that expired and unexpired samples are classified into two categories. The HPLC fingerprinting based on column switching technology with better separation power and higher peak capacity could characterize chemical composition information more comprehensively, providing an effective and alternative method to control and evaluate the quality of TMOL, which would offer a valuable reference for other TCM preparations.

Extraction process is not only a critical manufacturing unit but also the initial process of various extracts and preparations. Taking the most extensive Chinese herbal medicine Danshen (Salvia miltziorrhiza Bge) as an example, salvianolic acid B (Sal B) is its main active pharmaceutical ingredient but lacks accurate characterization of the extraction process. As one of process analytical technologies, near-infrared spectroscopy (NIRS) technology has been widely applied for monitoring pharmaceutical extraction process. In most past studies, water spectral information is often eliminated due to its high absorption. However, this study proposed a method of using water spectrum to understand the whole extraction process and to quickly determine the content of Sal B. Principal component analysis (PCA) was first utilized to investigate the whole extraction process, then the reconstructed spectrum based on PCA was established and analyzed by Aquaphotomics, and finally the partial least squares regression (PLSR) quantitative model of Sal B was established. PCA and Aquaphotomics results showed the whole extraction process could be considered as a dynamic change from structure breaker to structure maker, and the dominance of highly H-bonded water structures increases with the extraction time. Also, the Sal B quantitative model with water spectrum showed higher accuracy and stability than other methods, which parameters (RMSEC, RMSECV, RMSEP, R2c, R2cv, R2p, RPD) were 0.2408 mg/mL, 0.2939 mg/mL, 0.2584 mg/mL, 0.9536, 0.9300, 0.9494, 4.6298, respectively, and the paired t-test showed that Sal B content measured by NIR and HPLC methods had no significant differences (p > 0.05). In conclusion, all result indicated that water can be used as a probe to understand the traditional Chinese medicine extraction process with NIRS.

With the implementation of quality by design (QbD), critical attributes of raw material (drug substance and excipients) are of significantly importance in pharmaceutical manufacturing process. It is desirable for the quality control of critical material attributes (CMAs) of excipients to ensure the quality of end product. This paper explored the feasibility of an at-line method for the quantitative analysis of hydroxypropoxy group in hydroxypropyl methylcellulose (HPMC) with near infrared spectroscopy (NIRS). Hydroxypropoxy group content can be seen as a CMA of HPMC for quality control. The partial least squares (PLS) model was built with 61 samples including 47 samples as calibration set, 14 samples as validation set by sample set partitioning based on joint x-y distances (SPXY) method. Multiplicative scattering correction (MSC) combined with Savitzkye-Golay (SG) smoothing with first derivative was used as the appropriate pretreatment method. Three variable selection methods including interval partial least-squares (iPLS), competitive adaptive reweighted Sampling (CARS), and the combination of the two methods (iPLS-CARS) were performed for optimizing the model. The results indicated that NIRS could predict rapidly and effectively the content of hydroxypropoxy group in HPMC. NIRS could be a potential method for the quality control of CMAs.

Nowadays, as a powerful process analytical tool, near infrared spectroscopy (NIRS) has been widely applied in process monitoring. In present work, NIRS combined with multivariate analysis was used to monitor the ethanol precipitation process of fraction I+II+III (FI+II+III) supernatant in human albumin (HA) separation to achieve qualitative and quantitative monitoring at the same time and assure the product's quality. First, a qualitative model was established by using principal component analysis (PCA) with 6 of 8 normal batches samples, and evaluated by the remaining 2 normal batches and 3 abnormal batches. The results showed that the first principal component (PC1) score chart could be successfully used for fault detection and diagnosis. Then, two quantitative models were built with 6 of 8 normal batches to determine the content of the total protein (TP) and HA separately by using partial least squares regression (PLS-R) strategy, and the models were validated by 2 remaining normal batches. The determination coefficient of validation (Rp2), root mean square error of cross validation (RMSECV), root mean square error of prediction (RMSEP) and ratio of performance deviation (RPD) were 0.975, 0.501g/L, 0.465g/L and 5.57 for TP, and 0.969, 0.530g/L, 0.341g/L and 5.47 for HA, respectively. The results showed that the established models could give a rapid and accurate measurement of the content of TP and HA. The results of this study indicated that NIRS is an effective tool and could be successfully used for qualitative and quantitative monitoring the ethanol precipitation process of FI+II+III supernatant simultaneously. This research has significant reference value for assuring the quality and improving the recovery ratio of HA in industrialization scale by using NIRS.

The usage of traditional Chinese medicines has expanded globally, but the data about authentication, efficacy, and safety is far from sufficient to meet the criteria supporting their use worldwide due to complexity in the composition. Fingerprinting describes integral characterization and reflects interactive aspects of complex components; therefore, it can offer the possibility of evaluating quality of traditional Chinese medicines following the overall principle. Chemometric techniques introduce multivariate analytical methods into fingerprinting to obtain more information that is useful, which is consistent with the holistic thought and plays an important role in research on the substantial basis. In this review, we will start with three aspects to expound the quality evaluation of traditional Chinese medicines based on fingerprints. The analytical techniques used in developing fingerprints including chromatographic methods, spectroscopic methods, and capillary electrophoresis are introduced. Strategies for fingerprints analysis usually based on chemometric methods including unsupervised and supervised pattern recognition are described. Applications of fingerprints for multi-component quantification, quality control, screening of bioactive components, and fingerprint-efficacy relationship study are also outlined. Finally, we propose challenges and future perspectives of fingerprints in quality evaluation to promote the development of modernization and internationalization of traditional Chinese medicines.

Eszopiclone (E-ZOP), a strictly controlled psychoactive drug, must be accurately quantified in biological matrices. However, because of its rapid degradation and transformation into 2-amino-5-chloropyridine (ACP) during specimen preparation, the concentration of E-ZOP in biological matrices is likely underestimated. In this study, a sensitive and simple high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) method for the accurate determination of the initial concentration of E-ZOP in rat plasma was developed and validated. ACP was monitored simultaneously throughout the method validation process to ensure that it was not produced via E-ZOP hydrolysis. E-ZOP and structurally similar metabolites were stabilized in rat plasma by controlling the pH at 4.2 using a modified phosphate buffer solution (PBS) with acetic acid. Using this method, E-ZOP, ACP and the internal standard (IS), venlafaxine, were extracted from rat plasma via a simple protein precipitation and separated on a C18 column using methanol, 5 mM ammonium acetate, and 0.1 % acetic acid as the isocratic mobile phase. The validated method covered a working range from 0.1-50 ng/mL for E-ZOP, and the lower limit of detection (LLOD) for ACP was 0.2 ng/mL. In conclusion, an accurate, sensitive, and simple HPLC-MS/MS method for E-ZOP quantification was developed and successfully applied to a preclinical pharmacokinetics (PK) study in rats. The toxic product APC was effectively monitored. The HPLC-MS/MS method is a stable and sensitive quantitative method for the determination of E-ZOP in biological matrices.

Traditional Chinese medicine (TCM), especially herbal medicine compound preparation, faces great challenges in its quality control due to a myriad of components involved. How to perform quality control of TCM more effectively has been a research topic. In this study, we used Tianmeng oral liquid (TOL) as a case study and developed a comprehensive strategy based on non-targeted, targeted and bioactive analyses for quality evaluation of TOL from different batches. Firstly, a non-targeted fingerprinting analysis was performed by HPLC-DAD and UHPLC-MS/MS. Twenty-five batches of TOL were clearly discriminated by similarity analysis and hierarchical cluster analysis and components were tentatively identified. Secondly, the targeted quantitative methods based on HPLC-DAD and HPLC-MS were applied to simultaneous quantitative determination of five and eight marker compounds, especially toxic component strychnine, respectively. The quantitative data were processed with principal component analysis for differentiating different batches of samples. Finally, we explored the feasibility of establishing a total antioxidant capacity (TAC) model. How to use the peak area instead of the corresponding concentration to determine the antioxidant activity-related compounds was theoretically explained for the first time, which was of great significance for the study of the fingerprint-efficacy relationship. The orthogonal signal correction-partial least squares model was employed to predict the TAC of TOL from their chromatographic fingerprints and identify three potential antioxidant markers. These results demonstrated that the comprehensive strategy from fingerprinting, chemical composition, multiple-component quantification, and antioxidant activity could be applied to quality evaluation of TOL and discrimination of the expired and unexpired samples.

N-acetyl- d -glucosamine (GlcNAc) is a microbial fermentation product, and NIR spectroscopy is an effective process analytical technology (PAT) tool in detecting the key quality attribute: the GlcNAc content. Meanwhile, the design of NIR spectrometers is under the trend of miniaturization, portability and low-cost nowadays. The aim of this study was to explore a portable micro NIR spectrometer with the fermentation process. First, FT-NIR spectrometer and Micro-NIR 1700 spectrometer were compared with simulated fermentation process solutions. The Rc2, Rp2, RMSECV and RMSEP of the optimal FT-NIR and Micro-NIR 1700 models were 0.999, 0.999, 3.226 g/L, 1.388 g/L and 0.999, 0.999, 1.821 g/L, 0.967 g/L. Passing-Bablok regression method and paired t-test results showed there were no significant differences between the two instruments. Then the Micro-NIR 1700 was selected for the practical fermentation process, 135 samples from 10 batches were collected. Spectral pretreatment methods and variables selection methods (BiPLS, FiPLS, MWPLS and CARS-PLS) for PLS modeling were discussed. The Rc2, Rp2, RMSECV and RMSEP of the optimal GlcNAc content PLS model of the practical fermentation process were 0.994, 0.995, 2.792 g/L and 1.946 g/L. The results have a positive reference for application of the Micro-NIR spectrometer. To some extent, it could provide theoretical supports in guiding the microbial fermentation or the further assessment of bioprocess.

Determination of modification degree in BDDE-modified hyaluronic acid (HA) hydrogel is of particular interest. In this paper, three crosslinking parameters (degree of total modification, t-MOD; degree of cross-link modification, c-MOD; degree of pendent modification, p-MOD) are defined and determined by quantification of the modified fragments in hydrogel digestion by size exclusion chromatography combined with mass spectrometry (SEC-MS). The digestion products of a novel hyaluronidase HAase-B produced by Bacillus sp. A50 are studied and only a few modified fragments are identified by (1)H NMR and MS. As a result, Three HA hydrogels prepared in lab have different t-MOD, c-MOD and p-MOD, but the ratio of c-MOD to p-MOD result in the almost same value of 75%. Hydrogel products from Q-Med have nearly same t-MOD about 0.8% and c-MOD about 0.1%, the ratio of c-MOD to p-MOD is about 13%. Hydrogels from ANTEIS S.A all have much higher t-MOD values, the ratio of c-MOD and p-MOD is about 8%.

Salvia miltiorrhiza Bge. var. alba C.Y. Wu and H.W. Li has wide prospects in clinical practice. A useful comprehensive method was developed for the quality evaluation of S. miltiorrhiza var. alba by three quantitative parameters: high-performance liquid chromatography fingerprint, ten-component contents, and antioxidant activity. The established method was validated for linearity, precision, repeatability, stability, and recovery. Principal components analysis and hierarchical clustering analysis were both used to evaluate the quality of the samples from different origins. The results showed that there were category discrepancies in quality of S. miltiorrhiza var. alba samples according to the three quantitative parameters. Multivariate linear regression was adopted to explore the relationship between components and antioxidant activity. Three constituents, namely, danshensu, rosmarinic acid, and salvianolic acid B, significantly correlated with antioxidant activity, and were successfully elucidated by the optimized multivariate linear regression model. The combined use of high-performance liquid chromatography fingerprint analysis, simultaneous multicomponent quantitative analysis, and antioxidant activity for the quality evaluation of S. miltiorrhiza var. alba is a reliable, comprehensive, and promising approach, which might provide a valuable reference for other herbal products in general to improve their quality control.

Near-infrared (NIR) spectroscopy has been developed into an indispensable tool for both academic research and industrial quality control in a wide field of applications. The feasibility of NIR spectroscopy to monitor the concentration of puerarin, daidzin, daidzein and total isoflavonoid (TIF) during the extraction process of kudzu (Pueraria lobata) was verified in this work. NIR spectra were collected in transmission mode and pretreated with smoothing and derivative. Partial least square regression (PLSR) was used to establish calibration models. Three different variable selection methods, including correlation coefficient method, interval partial least squares (iPLS), and successive projections algorithm (SPA) were performed and compared with models based on all of the variables. The results showed that the approach was very efficient and environmentally friendly for rapid determination of the four quality indices (QIs) in the kudzu extraction process. This method established may have the potential to be used as a process analytical technological (PAT) tool in the future.

At present, Tradition Chinese Medicine (TCM) industry in China is in the stage from the empirical development to industrial production. Near infrared (NIR) spectroscopy has been widely used in the quality control of TCM’s modernization with its characteristics including rapidness, nondestruction, simplicity, economy, and so on. In this study, as one type of a portable micro NIR spectrometer, Micro NIR 1700 was used to establish the qualitative models for identification of geographical region and authenticity of Radix codonopsis based on discriminant analysis (DA) method. Both of the DA models had better predictive ability with 100% accuracy. In addition, a method for rapid quantitative analysis of polysaccharide in Radix codonopsis was also developed based on Micro NIR 1700 spectrometer with partial least-squares (PLS) algorithm. In the PLS calibration model, the NIR spectra of samples were pretreated with different preprocessing methods and the spectral region was selected with different variable selection methods as well. The performance of the final PLS model was evaluated according to correlation coefficient of calibration ([Formula: see text]), correlation coefficient of prediction ([Formula: see text]), root mean squared error of cross validation (RMSECV), and root mean squared of prediction (RMSEP). The values of [Formula: see text], [Formula: see text], RMSECV, and RMSEP were 0.9775, 0.9602, 2.496, and 2.734[Formula: see text]g/mL, respectively. This work demonstrated that micro infrared spectrometer could be more convenient and rapid for quality control of Radix codonopsis, and the presented models would be a useful reference for quality control of other similar raw materials of TCM.

As a powerful process analytical technology (PAT) tool, near infrared (NIR) spectroscopy has been widely used in real-time monitoring. In this study, NIR spectroscopy was applied to monitor multi-parameters of traditional Chinese medicine (TCM) Shenzhiling oral liquid during the concentration process to guarantee the quality of products. Five lab scale batches were employed to construct quantitative models to determine five chemical ingredients and physical change (samples density) during concentration process. The paeoniflorin, albiflorin, liquiritin and samples density were modeled by partial least square regression (PLSR), while the content of the glycyrrhizic acid and cinnamic acid were modeled by support vector machine regression (SVMR). Standard normal variate (SNV) and/or Savitzkye-Golay (SG) smoothing with derivative methods were adopted for spectra pretreatment. Variable selection methods including correlation coefficient (CC), competitive adaptive reweighted sampling (CARS) and interval partial least squares regression (iPLS) were performed for optimizing the models. The results indicated that NIR spectroscopy was an effective tool to successfully monitoring the concentration process of Shenzhiling oral liquid.

A simple, sensitive and accurate method based on high performance liquid chromatography (HPLC) with diode array detector (DAD) was developed and validated for systematic quality evaluation of one type of traditional Chinese medicine preparations named Xinkeshu (XKS) tablet. In this study, the chromatographic fingerprints of XKS tablet were developed first, 23 peaks were selected as the common peaks to evaluate the similarities among different batches of XKS samples, which were manufactured in a long time span of three years. Additionally, simultaneous quantification of six markers in XKS tablet, including Danshensu, Protocatechuic aldehyde, Puerarin, Daidzin, Salvianolic acid B and Daidzein, was performed. The validation results showed that the developed method was specific, accurate, precise and robust. The preliminary explanation on why a close similarity between fingerprints did not exactly mean similar contents of chemical components in samples was given. The contribution of each chromatographic peak to similarity was also evaluated. The developed method offers an efficient, reliable and practical approach for systematic quality evaluation of XKS tablet. Keywords: Fingerprint analysis, Quality evaluation, Multi-ingredient quantitative analysis, Xinkeshu tablet, High-performance liquid chromatography

To develop a method for the rapid monitoring of five components during the alcohol precipitation process of Shenzhiling oral solution using near infrared spectroscopy(NIRS).The contents of five components detemined by high performance liquid chromatography(HPLC) were used as the reference values, and the NIRS based partial least square regression(PLSR) models were used to monitor the concentrations of paeoniflorin, albiflorin, liquiritin, cinnamic acid and glycyrrhizic acid during the alcohol precipitation process of Shenzhiling oral solution, which were optimized and verified through comparing of different spectral pre-processing and variables selection methods. Determination coefficients(Rcal2 and Rpred2), root mean squares error of prediction (RMSEP), root mean squares error of calibration(RMSEC) and ratiao of performance to deviation(RPD) were applied to evaluate the performance of the models, and the corresponding values were 0.993 3 and 0.997 6, 0.084 9 g•L⁻¹, 0.073 3 g•L⁻¹ and 14.7 for paeoniforin; 0.991 4, 0.992 7, 0.028 1 g•L⁻¹, 0.030 5 g•L⁻¹ and 10.2 for albiforin; 0.955 3, 0.976 1, 0.012 0 g•L⁻¹, 0.012 3 g•L⁻¹ and 5.1 for liquiritin; 0.958 8, 0.990 3, 0.003 89 g•L⁻¹, 0.002 89 g•L⁻¹ and 7.1 for cinnamic acid; 0.982 0, 0.986 3, 0.053 8 g•L⁻¹, 0.059 0 g•L⁻¹, 7.2 for glycyrrhizic acid, respectively. The results indicated that the presented approach was effectively for the quantitative monitoring of the alcohol precipitation process of Shenzhiling oral solution.

A simple and accurate capillary electrophoresis (CE) method was developed to simultaneously separate and quantify heparin, chondroitin sulfate and hyaluronic acid. The relative standard deviations (intra-day) of migration time, peak height and peak area for heparin, chondroitin sulfate and hyaluronic acid were lower than 1.11, 5.45 and 2.82%, respectively. The limits of detection of heparin, chondroitin sulfate and hyaluronic acid were 0.91, 0.12 and 9.04 × 10(-3) mg/mL, respectively. The developed electrophoretic method was successfully applied to the analysis of commercial drug products and biological samples containing chondroitin sulfate and/or hyaluronic acid. The recoveries for chondroitin sulfate and hyaluronic acid were in the range of 95.9 ~107.0%. This was the first time the content of hyaluronic acid in the synovial fluids from osteoarthritic rabbits was investigated by CE. The results suggested that hyaluronic acid in the synovial fluids from osteoarthritic rabbits may be further metabolized and the administration of chondroitin sulfate or hyaluronic acid could affect the content and metabolism of hyaluronic acid in the synovial fluids. The developed CE method was simple to implement without sample pretreatment such as depolymerisation, very repeatable and easily transferred from lab to lab.

Human albumin (HA) is a very important blood product which requires strict quality control strategy. Acid precipitation is a key step which has a great effect on the quality of final product. Therefore, a new method based on quality by design (QbD) was proposed to investigate the feasibility of realizing online quality control with the help of near infrared spectroscopy (NIRS) and chemometrics. The pH value is the critical process parameter (CPP) in acid precipitation process, which is used as the end-point indicator. Six batches, a total of 74 samples of acid precipitation process, were simulated in our lab. Four batches were selected randomly as calibration set and remaining two batches as validation set. Then, the analysis based on material information and three different variable selection methods, including interval partial least squares regression (iPLS), competitive adaptive reweighted sampling (CARS) and correlation coefficient (CC) were compared for eliminating irrelevant variables. Finally, iPLS was used for variables selection. The quantitative model was built up by partial least squares regression (PLSR). The values of determination coefficients ([Formula: see text] and [Formula: see text]), root mean squares error of prediction (RMSEP), root mean squares error of calibration (RMSEC) and root mean squared error of cross validation (RMSECV) were 0.969, 0.953, 0.0496, 0.0695 and 0.0826, respectively. The paired [Formula: see text] test and repeatability test showed that the model had good prediction ability and stability. The results indicated that PLSR model could give accurate measurement of the pH value.

Potency is an important parameter for evaluation of quality of heparin active pharmaceutical ingredient (API). In this paper the feasibility to determine potency of heparin API with near infrared reflectance spectroscopy (NIRS) coupled with partial least squares (PLS) algorithm is attempted. PLS factors, correlation coefficient of calibration set (R(c)), the root mean square of cross-validation (RMSECV), correlation coefficient of prediction set (R(p)) and the root mean square of prediction (RMSEP) were used to evaluate the performance of the models. The optimal calibration model was obtained with R(p)=0.9721 and RMSEP=0.55 in the 1700-1898nm spectral region when using SG-1st derivative spectral transform method and division of calibration/prediction samples was 1/1. Three other additional samples demonstrated good prediction capability of the final model and three validation samples gave good repeatability result. NIRS has the potential to be a final lot release test to be performed in a QC laboratory.

Evaluation of the batch consistency of traditional Chinese medicines (TCMs) is essential for the promotion of the development and quality control of TCMs. The aim of the present work was to develop a useful strategy via liquid chromatography and chemometrics to evaluate the batch consistency of TCM preparations. Xin-Ke-Shu (XKS) tablet was chosen as a model for this method development. Four types of chromatographic fingerprint approaches were compared by using similarity analysis based on cosine of angel or correlation coefficient. Differences in the fingerprints of 71 batches of XKS tablet were illustrated by hierarchical cluster analysis. Then, Mahalanobis distance was employed for estimating the probability level (P<0.05) of the differences mentioned above. Additionally,t-test was applied to find out the chromatographic peaks which had significant differences. For XKS tablet, the maximum wavelength fingerprint had the largest range and dispersion degree of similarity as compared with the other three ones. There were two clear clusters in all the batches of samples. And we clearly arrived at the conclusion that higher similarity does not exactly indicate small Mahalanobis distance, while lower similarity indicated larger Mahalanobis distance. Finally, a useful strategy was proposed for evaluation of the batch consistency of XKS tablet.

Near infrared (NIR) spectroscopy has been developed into one of the most important process analytical techniques (PAT) in a wide field of applications. The feasibility of NIR spectroscopy with partial least square regression (PLSR) to monitor the concentration of paeoniflorin, albiflorin, gallic acid, and benzoyl paeoniflorin during the water extraction process of Radix Paeoniae Alba was demonstrated and verified in this work. NIR spectra were collected in transmission mode and pretreated with smoothing and/or derivative, and then quantitative models were built up using PLSR. Interval partial least squares (iPLS) method was used for the selection of spectral variables. Determination coefficients ([Formula: see text] and [Formula: see text]), root mean squares error of prediction (RMSEP), root mean squares error of calibration (RMSEC), and residual predictive deviation (RPD) were applied to verify the performance of the models, and the corresponding values were 0.9873 and 0.9855, 0.0487[Formula: see text]mg/mL, 0.0545[Formula: see text]mg/mL and 8.4 for paeoniflorin; 0.9879, 0.9888, 0.0303[Formula: see text]mg/mL, 0.0321[Formula: see text]mg/mL and 9.1 for albiflorin; 0.9696, 0.9644, 0.0140[Formula: see text]mg/mL, 0.0145[Formula: see text]mg/mL and 5.1 for gallic acid; 0.9794, 0.9781, 0.00169[Formula: see text]mg/mL, 0.00171[Formula: see text]mg/mL and 6.9 for benzoyl paeoniflorin, respectively. The results turned out that this approach was very efficient and environmentally friendly for the quantitative monitoring of the water extraction process of Radix Paeoniae Alba.

Radix Salvia miltiorrhiza Bge. var. alba C.Y. Wu and H.W. Li and Radix S. miltrorrhiza belong to the same genus. S. miltiorrhiza var. alba has a unique effectiveness for thromboangiitis besides therapeutical efficay of S. miltrorrhiza. It exhibits antioxidant activity (AA), while its quality and efficacy also vary with geographic locations. Therefore, a rapid and nondestructive method based on Fourier transform near infrared spectroscopy (FT-NIRS) was developed for discrimination of geographical origin and evaluation of AA of S. miltiorrhiza var. alba. The discrimination of geographical origin was achieved by using discriminant analysis and the accuracy was 100%. Partial least squares (PLS) regression was employed to establish the model for evaluation of AA by NIRS. The spectral regions were selected by interval PLS (i-PLS) method. Different pre-treated methods were compared for the spectral pre-processing. The final optimal results of PLS model showed that correlation coefficients in the calibration set (Rc) and the prediction set (Rp), root mean square error of prediction (RMSEP) and residual prediction deviation (RPD) were 0.974, 0.950, 0.163 mg mL(-1) and 2.66, respectively. The results demonstrated that NIRs combined with chemometric methods could be a rapid and nondestructive tool to discriminate geographical origin and evaluate AA of S. miltiorrhiza var. alba. The developed NIRS method might have a potential application to high-throughput screening of a great number of raw S. miltiorrhiza var. alba samples for AA.

Near-infrared spectroscopy (NIRS) is known to be a powerful analytical tool in process monitoring. The feasibility of NIRS was investigated for determination of immunoglobulin G (IgG) in raw plasma cold ethanol precipitation process. Partial least squares (PLS) was used to develop regression model for 63 samples between spectra and reference data measured with a UV spectrophotometer. Three different variable selection methods, including correlation coefficient method, interval partial least squares (iPLS) and successive projection algorithm (SPA), were performed and compared with models based on all the variables. The values of Rc and root mean square error of cross validation (RMSECV) produced by the best model for the calibration set were 0.9599 and 0.6135 g/L, respectively. While for the validation set, the values of Rp and root mean square error of prediction (RMSEP) were 0.9577 and 0.4913 g/L, respectively. The results of this paper demonstrated that NIRS could be a feasible alternative approach for rapid determination of IgG in the cold ethanol precipitation process and can be used as a PAT tool in the future.

Ion-exchange chromatography is a widely used purification technology in the heparin manufacturing process. To improve the efficiency and understand the process directly, a rapid and equally precise method needs to be developed to measure heparin concentration in chromatography process. Here, two robust partial least squares regression (PLS-R) models were established for quantification of heparin based on the near-infrared (NIR) spectroscopy with 80 samples of adsorption process and 76 samples of elution process. Several variables selection algorithms, including correlation coefficient method, successive projection algorithm (SPA) and interval partial least squares (iPLSs), were performed to remove non-informative variables. The results showed that the correlation coefficient of validation (Rp) and the residual predictive deviation (RPD) corresponded to 0.957 and 3.4472 for adsorption process, 0.968 and 3.9849 for elution process, respectively. The approach was found considerable potential for real-time monitoring the heparin concentration of chromatography process.