Wenlong Li

Rapid quantification of phenolic acids in Radix Salvia Miltrorrhiza extract solutions by FT-NIR spectroscopy in transflective mode

A rapid method for simultaneous determination of main phenolic acids in Radix Salvia Miltrorrhiza extract solutions was developed using Fourier transform near infrared spectroscopy in transflective mode and multivariate calibration and HPLC-UV as the reference method. Partial least squares (PLS) algorithm was conducted on the calibration of regression models. The multiplicative scatter correction, Norris derivative and second derivative were adopted for the spectral pre-processing, and the number of PLS factors were optimized by leave-one-out cross-validation. The performance of the final model was evaluated according to root mean square error of prediction (RMSEP) and correlation coefficient (R). The R values achieved in the prediction set were above 0.93. The developed models were used for analysis of unknown samples and routine monitoring with satisfactory results. This work demonstrated that NIR spectroscopy combined with PLS algorithm could be used for the rapid determination of the main phenolic acids of Salvia Miltrorrhiza extract solutions.

Application of near infrared spectroscopy for rapid analysis of intermediates of Tanreqing injection

A method for rapid quantitative analysis of four kinds of Tanreqing injection intermediates was developed based on Fourier transform near infrared (FT-NIR) spectroscopy and partial least squares (PLS) algorithm. The NIR spectra of 120 samples were collected in transflective mode. The concentrations of chlorogenic acid, caffeic acid, luteoloside, baicalin, ursodesoxycholic acid (UDCA), and chenodeoxycholic acid (CDCA) were determined with the HPLC-DAD/ELSD as reference method. In the PLS calibration, the NIR spectra were pretreated with different methods and the number of PLS factors used in the model calibration was optimized by leave-one-out cross-validation. The performance of the final PLS models was evaluated according to the root mean square error of calibration (RMSEC), root mean square error of cross-validation (RMSECV), root mean square error of prediction (RMSEP), BIAS, standard error of prediction (SEP), and correlation coefficients (R). The R values in the prediction sets were all higher than 0.93, and the SEPs for the 6 compounds are 1.18, 6.02, 2.71, 155, 126, 30.0mg/l, respectively. The established models were used for the liquid preparation process analysis of Tanreqing injection in three batches, and a model updating method was proposed for the long-term usage of the established models. This work demonstrated that NIR spectroscopy is more rapid and convenient than the conventional methods to analyze the intermediates of Tanreqing injection, and the presented method is helpful to the implementation of process analytical technology (PAT) in pharmaceutical industry of Chinese Medicines Injections.

Quality control of Lonicerae Japonicae Flos using near infrared spectroscopy and chemometrics.

A set of qualitative and quantitative methods based on near infrared (NIR) spectroscopy was established for the geographical origin identification, quantitative determination of active compounds, and fingerprint analysis of Lonicerae Japonicae Flos. The spectra of 140 samples from different origins were collected with two NIR instruments from different manufacturers (Thermo Scientific and Buchi). A Soft Independent Modeling of Class Analogy model was established for the identification of Lonicerae Japonicae Flos from the genuine producing area. Using the established discriminant analysis model, 22 samples from Henan province were predicted with 100% rate of accuracy, while the 68 samples from other producing areas were predicted with 9 samples incorrectly judged. Futhermore, partial least square regression method was used for developing the quantitative calibration models with the reference values determined with a validated HPLC-UV method. The RMSEP values of external validation are 0.169%, 0.048%, 0.172%, 0.007%, 0.203%, and 0.066% for NCA, CA, CfA, 3,4-DCA, 3,5-DCA, and 4,5-DCA, respectively, which indicated that the established models possess satisfactory predictive abilities. In addition, the models established on the primary instrument can also be transferred to the secondary instrument using direct standardization algorithm, which enlarged the application scope of the established models. Since the NIR spectra can reflect the comprehensive quality information of Lonicerae Japonicae Flos, a fingerprint analysis method was finally proposed for the quality consistency check of raw materials. The proposed methods are rapid and effective, and possess good portability, which is helpful to the quality control of Lonicerae Japonicae Flos.

A study on the use of near-infrared spectroscopy for the rapid quantification of major compounds in Tanreqing injection

In this paper we describe the strategy used in the development and validation of a near infrared spectroscopy method for the rapid determination of baicalin, chlorogenic acid, ursodeoxycholic acid (UDCA), chenodeoxycholic acid (CDCA), and the total solid contents (TSCs) in the Tanreqing injection. To increase the representativeness of calibration sample set, a concentrating-diluting method was adopted to artificially prepare samples. Partial least square regression (PLSR) was used to establish calibration models, with which the five quality indicators can be determined with satisfied accuracy and repeatability. In addition, the slope/bias (S/B) method was used for the models transfer between two different types of NIR instruments from the same manufacturer, which is contributing to enlarge the application range of the established models. With the presented method, a great deal of time, effort and money can be saved when large amounts of Tanreqing injection samples need to be analyzed in a relatively short period of time, which is of great significance to the traditional Chinese medicine (TCM) industries.

Rapid analysis of the in-process extract solutions of compound E Jiao oral liquid using near infrared spectroscopy and partial least-squares regression

A rapid and simultaneous quantification of the main active compounds of the in-process extract solutions is beneficial to the process monitoring as well as ensuring quality consistency of the end products during the production of traditional Chinese medicine. Here we present a near infrared (NIR) spectroscopy-based method for rapid analysis of extract solutions in the production of compound E Jiao oral liquid. The partial least-squares regression (PLSR) models for four quality indicators (viz. total flavonoids, total saponins, total saccharides and soluble solid contents) were established and validated. The results showed that all of the four models exhibited satisfactory fitting and predictive capacity. The root mean squares error of prediction (RMSEP) was 0.0384 mg mL−1, 0.0154 mg mL−1, 3.80 mg mL−1 and 0.199% for total flavonoids, total saponins, total saccharides and soluble solid contents, respectively. This work here demonstrated that NIR spectroscopy coupled with PLSR calibration can offer a reliable and non-destructive alternative in the routine monitoring of the extraction process in the production of compound E Jiao oral liquid. The presented approach is expected to be equally applicable to the mixed decoction of other herbal medicines.

Feasibility Research on Non-Invasive Analysis of Tanreqing Injection with near Infrared Spectroscopy

A non-invasive analysis method for bottled Tanreqing injection was developed based on near infrared (NIR) spectroscopy. The NIR trans-mission spectra were collected using a home-made accessory. The quality indicators of Tanreqing injection, which include baicalin, ursodesoxycholic acid (UDCA), chenodeoxycholic acid (CDCA), chlorogenic acid (CA), forsythin, total amino acids (TAA) and soluble solid content (SSC), were determined with standard methods. Several outlier samples were eliminated using the Dixon test, leverage and studentised residual test and analogous samples were amalgamated. Partial least squares regression (PLSR) was used for establishing the calibration models with the pre-treated spectra and the reference values. The root mean square errors of prediction (RMSEP) values of external validation samples were 0.098 g L−1, 0.059 g L−1, 0.140 g L−1, 0.038g L−1, 0.007 g L−1, 0.053 g L−1 and 0.538 gL−1 for baicalin, CA, UDCA, CDCA, forsythin, TAA and SSC, respectively, which indicated that the established models possessed satisfactory predictive abilities. The presented method can reduce the workload of product inspection to a large extent. This will allow the sampling proportion to be increased and enable improved quality control during Tanreqing injection production.

Manufacturer identification and storage time determination of “Dong’e Ejiao” using near infrared spectroscopy and chemometrics

We have developed a set of chemometric methods to address two critical issues in quality control of a precious traditional Chinese medicine (TCM), Dong’e Ejiao (DEEJ). Based on near infrared (NIR) spectra of multiple samples, the genuine manufacturer of DEEJ, e.g. Dong’e Ejiao Co., Ltd., was accurately identified among 21 suppliers by the fingerprint method using Hotelling T2, distance to Model X (DModX), and similarity match value (SMV) as discriminate criteria. Soft independent modeling of the class analogy algorithm led to a misjudgment ratio of 6.2%, suggesting that the fingerprint method is more suitable for manufacturer identification. For another important feature related to clinical efficacy of DEEJ, storage time, the partial least squares-discriminant analysis (PLS-DA) method was applied with a satisfactory misjudgment ratio (15.6%) and individual prediction error around 1 year. Our results demonstrate that NIR spectra comprehensively reflect the essential quality information of DEEJ, and with the aid of proper chemometric algorithms, it is able to identify genuine manufacturer and determine accurate storage time. The overall results indicate the promising potential of NIR spectroscopy as an effective quality control tool for DEEJ and other precious TCM products.中文概要目的对东阿阿胶的生产厂家和存放时间进行鉴定,为 东阿阿胶的品牌保护和质量控制提供技术手段。创新点首次报道采用近红外光谱指纹图谱技术和相关的 化学计量学方法对东阿阿胶进行质量控制。方法收集有代表性的阿胶样品,其中包括来自不同厂 家的阿胶、黄明胶、龟甲胶、鹿角胶样品188 份 和来自东阿阿胶股份有限公司2005∼2012 年间生 产的阿胶,每年30 批,共计240 份东阿阿胶样品。 采集样品光谱,采用Hotelling T2、DModX 和相 似度匹配值等统计量作为判断标准,进行东阿阿 胶品牌的鉴定; 采用偏最小二乘判别分析 (PLS-DA)方法进行东阿阿胶存放年限的判别 分析。结论所建立的方法可有效区分东阿阿胶与黄明胶、龟 甲胶、鹿角胶、以及其他品牌的阿胶,可用于东 阿阿胶的品牌保护;利用PLS-DA 可对不同存放 年限的东阿阿胶进行判别分析,结果令人满意。

Wavelet-based classification and influence matrix analysis method for the fast discrimination of Chinese herbal medicines according to the geographical origins with near infrared spectroscopy

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.

Rapid quantification of multi-components in alcohol precipitation liquid of Codonopsis Radix using near infrared spectroscopy (NIRS)

A near infrared spectroscopy (NIRS) approach was established for quality control of the alcohol precipitation liquid in the manufacture of Codonopsis Radix. By applying NIRS with multivariate analysis, it was possible to build variation into the calibration sample set, and the Plackett-Burman design, Box-Behnken design, and a concentrating-diluting method were used to obtain the sample set covered with sufficient fluctuation of process parameters and extended concentration information. NIR data were calibrated to predict the four quality indicators using partial least squares regression (PLSR). In the four calibration models, the root mean squares errors of prediction (RMSEPs) were 1.22 μg/ml, 10.5 μg/ml, 1.43 μg/ml, and 0.433% for lobetyolin, total flavonoids, pigments, and total solid contents, respectively. The results indicated that multi-components quantification of the alcohol precipitation liquid of Codonopsis Radix could be achieved with an NIRS-based method, which offers a useful tool for real-time release testing (RTRT) of intermediates in the manufacture of Codonopsis Radix.摘 要目 的建立党参醇沉上清液中多指标的快速近红外光谱分 析法, 帮助实现党参醇沉中间体的实时放行检测。创新点采用近红外光谱技术建立党参醇沉过程中间体的 质控方法, 实现醇沉上清液中4 种关键质量属性 的同时定量。方 法将近红外光谱技术与多变量数据处理相结合, 在 建模样本制备中, 通过实验设计的方法引入过程 参数的波动(表1 和表2), 先浓缩后稀释的方 法进一步扩大样品浓度范围, 以模型预测能力为 指标选择了最优的预处理方法、建模波段和回归 算法, 得到4 个指标的最佳回归模型。结 论实现了党参醇沉上清液中4 类指标的近红外光谱 快速分析法, 所建党参炔苷、总黄酮、色素和固 含量模型的预测均方根误差(RMSEP)值分别为 1.22 μg/ml、10.50 μg/ml、1.43 μg/ml 和0.433%。