Foreword

Since crude drugs are derived from natural resource, the characteristics of their chemical profiles, appearance and more alter according to the genetic background, growing condition, processing method and so on. In order to achieve the reproducibility of therapeutic effects of natural medicines, minimization of quality variance of crude drugs is one of the important subjects in pharmacognosy. In addition, an expected role of a crude drug in formulation of the product is not always the same since multicomponent crude drugs have multiple pharmaceutical activities with multiple molecular targets. Therefore, the preferable characteristics (chemical profile) of a crude drug may be different for each crude drug product including Kampo formulation. For example, Japanese Pharmacopoeia specifies total content of ephedrine and pseudoephedrine in Ephedra Herb as not less than 0.7%, and the ratio of these alkaloids having distinct activity in the drug is variable. Understanding the chemical diversity of crude drug in more detail is desired for future tailored medicine.

Until recently, the chemical evaluation of crude drugs has been performed by analyzing a limited number of components. In this decade, chemometrics has frequently been used for this purpose along with the rapid advance of PC performance. There are mainly two advantages when utilizing the chemometrics for quality evaluation: 1) Visualization of diversity range and 2) Clarifying the responsible component(s) for the diversity. In early days, the chemometrics was mainly used for mapping of quality diversity of crude drugs, and now, it is widely utilized in combination with other information such as genetic information, cultivation condition, processing method, habitat etc. Paring analytical methodologies are also varied and not only the separating analyses such as GC(-MS) and LC(-MS) but also the mixture analyses by using NMR and NIR are introduced as the methods to obtain the chemical information.

This Current Topics consists of four regular articles relevant to the quality (diversity) evaluation of crude drugs by multivariate analyses of the data obtained from the above-mentioned four instruments. In the first regular article, I and my colleagues report the study entitled “Genetic and Chemical Diversity of Commercial Japanese Valerian.” We investigated chemical composition of volatile compounds in commercial Japanese Valerian by GC-MS metabolomics, and revealed the good correlation between the chemical diversity and psbA-trnH genotype of the drug. Main components in Japanese and Chinese cultivars have different pharmaceutical activities, suggesting the selection of an appropriate cultivar depending on the symptoms will lead to more effective medication.

The second article entitled “Effect of Cultivation Conditions on Components of Ephedra sp. Using Liquid Chromatography-Mass Spectrometry and Multivariate Analysis” is reported by Dr. Hiroyuki Fuchino and Dr. Naoko Anjiki (Research Center for Medicinal Plant Resources, National Institutes of Biomedical Innovation, Health and Nutrition) et al. They analyzed Ephedra sinica and Ephedra sp. (EP-13) cultivated in various conditions using LC-MS metabolomics, and clarified major factors influencing contents of ephedrine and pseudophedrine.

The third regular article, entitled “¹H-NMR-Based Metabolomics for the Classification of the Roots of Paeonia lactiflora, a Constituent of Kampo Medicines” is reported by Dr. Ryuichiro Suzuki (Josai University) and his colleagues. They compared the chemical difference between the Japanese and Chinese Peony Roots using ¹H-NMR metabolomics, and identified oxypaeoniflorine and (+)-catechin as the specific compounds to the Japanese one. Although ¹H-NMR metabolomics has less resolution and sensitivity than GC and LC-MS, its target molecules are extremely comprehensive since all molecules with hydrogen atom is theoretically detectable. NMR metabolomics is free from risk of carry-over unlike GC and LC-MS because the spectra are measured using each NMR tube by each sample. Furthermore, NMR has more wide quantitative capability than those of GC and LC-MS.

The final article, entitled “Near-Infrared Metabolic Profiling for Discrimination of Apricot and Peach Kernels” is reported by Dr. Tatsuya Shirahata (Kitasato University) et al. Discrimination of related crude drugs, Apricot and Peach Kernels was accomplished by using multivariate analysis of NIR spectra. It is rapid and non-destructive method suitable for screening examination. Since the same technology have already been put into practical use in the measurement of sugar content of fruits and vegetables, the use of NIR metabolomics to quality assurance of crude drug is expected in near future.

Finally, I thank all authors for their contribution of this topics.