Review
Quality assessment of herbal medicines based on chemical fingerprints combined with chemometrics approach: A review

https://doi.org/10.1016/j.jpba.2020.113215Get rights and content

Highlights

  • The combination of chemical fingerprint and chemometrics is a powerful tool for quality assessment of herbal medicines.

  • Overviews of fingerprint technologies, chemometrics methods, analysis workflow and application scopes are provided.

  • Optimization selection of fingerprint technologies and chemometrics methods depend on practical purpose is highlighted.

Abstract

Herbal medicine (HM) has been playing a pivotal role in maintaining human health since ancient times, and its therapeutic theory and clinical experience are the precious traditional medical knowledge reserves. As HM occupies an important position in its own right in global healthcare systems, robust quality assessment and control over its complex chemical composition was of great significance to assure its efficacy and safety. Over the past decades, the concept of HM chemical fingerprints aiming to obtain a comprehensive characterization of complex chemical matrices has become one of the most convincing tools for the quality assessment of HM. This review summarizes the recent analytical techniques used to generate HM chemical fingerprints, including chromatography, vibrational spectroscopy, nuclear magnetic resonance spectroscopy, and mass spectrometry. The advantages, drawbacks, and the application scope of each technology have been scrutinized in an attempt to better understand the data analysis. Furthermore, HM fingerprints together with multivariate and multiway chemometrics methods used for different application domains, such as similarity, exploratory, classification, and regression analysis, have also been discussed and illustrated with a few typical studies. The article provides a general picture and workflow of fingerprinting analyses that have been used for the quality assessment of HM.

Introduction

Traditional herbal medicines have been used for the prevention and treatment of human diseases for thousands of years. Shennong Bencao Jing (Shennong’s Classic of Materia Medica), the oldest systematic monograph about the medicinal plants, formulations, effect and theory of traditional Chinese medicines, was written in ancient China from A.D. 25 to 220 [1]. Herbal medicine (HM), including herbs, herbal materials, herbal preparations, and finished herbal products, has become an increasingly important part of the global healthcare system [2,3]. Up to date, HM has attracted the interest of the global public with the trend of ‘return to nature’, and the increasing demand of HM has led to a significant expansion of its product markets [4]. However, at the present stage, HM has not been fully accepted in some western countries, due to its safety and efficacy evaluation data to be insufficient to support the criteria set by modern regulatory authorities [5,6].

Arrays of phytochemical and pharmacological investigations demonstrated that each individual herb could contain hundreds or even thousands of chemical components, which exerted the pharmacological effects through a network of multiple targets and pathways [7]. Furthermore, the quality of HM were affected by such factors, as botanical species, medicinal parts (leaf, stem, root, rhizome, flower, seed, etc.), processing methods (wash, dry, steam, etc.), storage conditions (time, temperature, humidity, etc.), cultivation years, harvest time, as well as growth conditions (terrain, soil, climate, and sunlight) [3,[8], [9], [10]]. Those variable factors caused the variations of chemical composition of HM from batch to batch, and resulted in a significant difference in pharmacological activities [5].

In the existing regulatory systems and pharmacopoeias, qualitative and quantitative quality assessment of HM was usually performed based on the sensory inspections including macroscopic and microscopic examination, as well as quantitative determination of a few intrinsic marker compounds [11]. However, sensory inspections mainly rely on personal experience and lacked adequate evidence-based validation, which could lead to subjective differences in the qualitative evaluation [12,13]. The determination of single marker compound for the quality assessment of HM neglected the importance of the synergistic effect of the multi-components, and did not represent its holistic efficacy [14,15]. Techniques for the overall quality evaluation based on the non-targeted approach have been proposed, which aimed to profile a comprehensive chemical description of HM, so-called ‘chemical fingerprint’. The World Health Organization (WHO), regulatory bodies worldwide such as the China Food and Drug Administration (CFDA), the Food and Drug Administration (FDA) of the USA, the European Medicines Agency (EMA), and the Ministry of Food and Drug Safety (MFDS) of Korea have accepted the concept of fingerprint to evaluate the quality of HM [2,[16], [17], [18]].

The analyses performed by different analytical techniques provided a huge number of variables of fingerprint data, which not only offered a good opportunity for mining useful chemical information from the original dataset, but also mean that it is difficult or even incapable to exploit the useful chemical information through general univariate analysis [19]. Nowadays, with the development of computer science, multivariate statistical analyses of chemical fingerprint information by chemometrics methods have been increasingly applied to the quality research of HM [20]. Chemometrics methods are widely used to solve various problems in different fields, such as the similarity analysis, exploratory learning, and classification algorithm can be used for qualitative analysis; multivariate calibration algorithm can be used for quantitative analysis, and explore the relationship between independent and dependent variables. The application of chemometrics to fingerprint data can extract covered information and knowledge from chemical systems by mathematical modeling, which is a potential direction for comprehensive quality assessment of HM.

Section snippets

Scope of this review

Some reviews have summarized the application of chemical fingerprint generated by different analytical techniques combined with chemometrics methods for the quality assessment of HM. However, most reviews showed a partial point of view, since they only focused on a specific analytical platform and chemometrics method for a narrowed application range. Nevertheless, the comparison between different analytical techniques, different chemometrics methods are needed to determine which one is more

Chromatography

Chromatography is a physical separation method that can separate complex chemical matrices in the herbal extract of HM into plenty of pure substances or relatively simple sub-fractions [21]. Chromatographic techniques, which include liquid chromatography (LC) [[22], [23], [24]], gas chromatography (GC) [25,26], thin layer chromatography (TLC) [[27], [28], [29]], and capillary electrophoresis (CE) [30], etc., have been used for fingerprint analysis of HM. With the characteristics of wide

Data pre-processing

The original, raw fingerprint data of HM is not suitable for direct chemometrics analysis due to the following reasons: the irreproducibility of experiment parameters from the above-mentioned instruments, such as the retention time of chromatographic technology is difficult to precisely reproduce among different samples; the multiplicative interferences caused by light scattering and particle size of infrared spectroscopy is discrepant between test samples. Multiple steps of data pre-processing

Conclusions

With the increasing attention of the public on the safety and quality of HM, the corresponding standards that efficiently assess the HM made from the raw materials to the medicinal products are becoming increasingly paramount to human health, also to the sustainability of its supply and industry. Owing to the advantages of overall quality evaluation, the chemical fingerprint used to get a comprehensive characterization of complex matrices was of promising and expected to become a powerful tool

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

The authors would like to acknowledge the financial support of National Natural Science Foundation (No. 81530095) and National Key R&D Program of China (2018YFC1707900) for the financial support.

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