Application of Near-Infrared Spectroscopy (NIRS) as a Tool for Quality Control in Traditional Chinese Medicine (TCM)

Rapid quantification of active pharmaceutical ingredient for sugar-free Yangwei granules in commercial production using FT-NIR spectroscopy based on machine learning techniques

Rapid quantification methods for sugar-free Yangwei granules were developed based on near-infrared (NIR) spectroscopy combined with machine learning approaches as a quality control strategy for Chinese medicine granules (CMGs). Different machine learning approaches-i.e., interval partial least squares optimized by the genetic algorithm (GA-iPLS), the backpropagation artificial neural network (BP-ANN), and the particle swarm optimization-support vector machine (PSO-SVM)-were used to develop prediction models for three active pharmaceutical ingredients (APIs), namely, albiflorin, paeoniflorin, and benzoylpaeoniflorin. The partial least squares (PLS) algorithm was used for linear model calibration and comparison of the prediction performance of these developed models. The performance of the final models was assessed by the correlation coefficient (R), root mean square error of calibration set (RMSEC), and root mean square error of prediction set (RMSEP). All models performed well in model fitting and provided satisfactory prediction accuracy. The results indicate that the machine learning approaches are more stable, predictable, and suitable for CMGs when a high-accuracy analysis is required. In summary, NIR spectroscopy coupled with machine learning techniques is a suitable tool for the straightforward quantification of CMGs.

NIR spectroscopy of natural medicines supported by novel instrumentation and methods for data analysis and interpretation

Near-infrared (NIR) spectroscopy is a powerful tool for qualitative and quantitative phytoanalysis. It is a rapid and high-throughput analytical method, with on-site capability, high chemical specificity, and no/minimal sample preparation. NIR spectroscopy is a powerful non-invasive and low-cost alternative with significant practical advantages compared to the conventional methods of analysis. These advantages are particularly exposed in the field of phytoanalysis. In contrast to synthetic medicines, natural products feature chemical diversity that can vary depending on the medicinal plant cultivation conditions, geographical origin or harvest time. The content of bioactive compounds and their derivatives, and thus, the quality parameters of the natural medicine need to be controlled with respect to a number of conditions. NIR spectroscopy has been proved to be particularly competitive in such difficult scenarios. In recent years, remarkable advances in the field of spectroscopic instrumentation and methods of analysis have appeared. Noteworthy was the appearance and dynamic continuing development of miniaturized, on-site capable NIR spectrometers. This was accompanied by application of new tools increasing the potential and reliability of NIR spectroscopy in phytoanalytical applications. The present review discussed the major principles of this technique and critically assesses its future application potential in phytoanalytical strategies. Major attention is given to the current development trends based on the most recent literature published in the field.

Quantifying several adulterants of notoginseng powder by near-infrared spectroscopy and multivariate calibration

The authentication of traditional Chinese medicine (TCM) is critically important for public-health and economic terms. Notoginseng, a classical TCM of high economic and medical value, could be easily adulterated with Sophora flavescens powder (SFP), corn flour (CF) or other analogues of low-grade (ALG) because of their similar tastes, appearances and much lower cost. The main objective of this study was to evaluate the feasibility of applying of near-infrared (NIR) spectroscopy and multivariate calibration for identifying and quantifying several common adulterants in notoginseng powder. Two datasets were prepared for experiment. The competitive adaptive reweighted sampling (CARS) was used to select informative variables. Two different schemes were used for sample set partition. Model population analysis (MPA) was made. The results showed that, the constructed partial least squares (PLS) model using a reduced set of variables from CARS can provide superior performance to the full-spectrum PLS model. Also, the sample set partition is very of great importance. It seems that the combination of NIR spectroscopy, CARS and PLS is feasible to quantify common adulterants in notoginseng powder.

Rapid and simultaneous analysis of five alkaloids in four parts of Coptidis Rhizoma by near-infrared spectroscopy

Near-Infrared Spectroscopy (NIRS) was first used to develop a method for rapid and simultaneous determination of 5 active alkaloids (berberine, coptisine, palmatine, epiberberine and jatrorrhizine) in 4 parts (rhizome, fibrous root, stem and leaf) of Coptidis Rhizoma. A total of 100 samples from 4 main places of origin were collected and studied. With HPLC analysis values as calibration reference, the quantitative analysis of 5 marker components was performed by two different modeling methods, partial least-squares (PLS) regression as linear regression and artificial neural networks (ANN) as non-linear regression. The results indicated that the 2 types of models established were robust, accurate and repeatable for five active alkaloids, and the ANN models was more suitable for the determination of berberine, coptisine and palmatine while the PLS model was more suitable for the analysis of epiberberine and jatrorrhizine. The performance of the optimal models was achieved as follows: the correlation coefficient (R) for berberine, coptisine, palmatine, epiberberine and jatrorrhizine was 0.9958, 0.9956, 0.9959, 0.9963 and 0.9923, respectively; the root mean square error of validation (RMSEP) was 0.5093, 0.0578, 0.0443, 0.0563 and 0.0090, respectively. Furthermore, for the comprehensive exploitation and utilization of plant resource of Coptidis Rhizoma, the established NIR models were used to analysis the content of 5 active alkaloids in 4 parts of Coptidis Rhizoma and 4 main origin of places. This work demonstrated that NIRS may be a promising method as routine screening for off-line fast analysis or on-line quality assessment of traditional Chinese medicine (TCM).

Application of NIR and MIR spectroscopy for rapid determination of antioxidant activity of Radix Scutellariae from different geographical regions

INTRODUCTION

The beneficial health effects of traditional Chinese medicines are often attributed to their potent antioxidant activities, usually established in vitro. However, these wet chemical methods for determining antioxidant activities are time-consuming, laborious, and expensive.

OBJECTIVES

This study was conducted to establish a rapid determination of antioxidant activity of Radix Scutellariae using near-infrared (NIR) and mid-infrared (MIR) spectroscopy.

MATERIAL AND METHODS

Antioxidant capabilities were evaluated using 2,2-diphenyl-1-picrylhydrazyl hydrazyl (DPPH) and oxygen radical absorbance capacity (ORAC) assays. The total flavonoid contents (TFCs) of Radix Scutellariae were measured by the aluminium chloride colorimetric method. The same sample was then scanned using NIR and MIR spectroscopy. Chemometrics analysis using partial least-squares (PLS) regression was performed to establish the models for predicting the antioxidant activities of Radix Scutellariae.

RESULTS

A better predictive performance was achieved using PLS models based on NIR data. The determination coefficient (R(2)) and the residual predictive deviation (RPD) for the validation set were 0.9298 and 2.84 for DPPH, and 0.9436 and 2.66 for TFCs, respectively. MIR-PLS algorithms gave a slightly lower reliability (R(2) = 0.9090 and 0.9374, RPD = 2.01 and 2.42, for DPPH and TFC, respectively). Very comparable results for ORAC were obtained with the two methods.

CONCLUSION

The developed spectroscopic method can be successfully applied in high-throughput screening of the antioxidant capability of Radix Scutellariae samples. It can also be a viable and advantageous alternative to laborious chemical procedures.

The relevance of pharmacognosy in pharmacological research on herbal medicinal products

As all medicines, herbal medicinal products are expected to be safe, effective, and of appropriate quality. However, regulations on herbal medicinal products vary from country to country, and herbal preparations do occur not only in the form of medicinal products but also as less strictly regulated product groups like dietary supplements. Therefore, it is not always easy for the consumers to discriminate high-quality products from low-quality products. On the other hand, herbal medicines have many special features that distinguish them from conventional medicinal products. Plants are complex multicomponent mixtures; in addition, their phytochemical composition is not constant because of inherent variability and a plethora of external influences. Therefore, the production process of an herbal medicinal product needs to be strictly monitored. First of all, the starting materials need to be correctly authenticated and free of adulterants and contaminants. During plant growth, many factors like harvest season and time, developmental stage, temperature, and humidity have a strong impact on plant metabolite production. Also, postharvest processing steps like drying and storage can significantly alter the phytochemical composition of herbal material. As the production of many phytopharmaceuticals includes an extraction step, the extraction solvent and conditions need to be optimized in order to enrich the bioactive constituents in the extract. The quality of finished preparations needs to be determined either on the basis of marker constituents or on the basis of analytical fingerprints. Thus, all production stages should be accompanied by appropriate quality assessment measures. Depending on the particular task, different methods need to be applied, ranging from macroscopic, microscopic, and DNA-based authentication methods to spectroscopic methods like vibrational spectroscopy and chromatographic and hyphenated methods like HPLC, GC-MS and LC-MS. Also, when performing pharmacological and toxicological studies, many features inherent in herbal medicinal products need to be considered in order to guarantee valid results: concerning in vitro studies, difficulties are often related to lacking knowledge of ADME characteristics of the bioactive constituents, nuisance compounds producing false positive and false negative results, and solubility problems. In in vivo animal studies, the route of administration is a very important issue. Clinical trials on herbal medicinal products in humans very often suffer from a poor reporting quality. This often hampers or precludes the pooling of clinical data for systematic reviews. In order to overcome this problem, appropriate documentation standards for clinical trials on herbal medicinal products have been defined in an extension of the CONSORT checklist. This article is part of a Special Issue entitled "Botanicals for Epilepsy".