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Traditional Chinese medicine (TCM) is the treasure of China, and the quality control of TCM is of crucial importance. In recent years, with the quick rise of artificial intelligence (AI) and the rapid development of hyperspectral imaging (HSI) technology, the combination of the two has been widely used in the quality evaluation of TCM. Machine learning (ML) is the core wisdom of AI, and its progress in rapid analysis and higher accuracy improves the potential of applying HSI to the field of TCM. This article reviewed five aspects of ML applied to hyperspectral data analysis of TCM: partition of data set, data preprocessing, data dimension reduction, qualitative or quantitative models, and model performance measurement. The different algorithms proposed by researchers for quality assessment of TCM were also compared. Finally, the challenges in the analysis of hyperspectral images for TCM were summarized, and the future works were prospected. [ABSTRACT FROM AUTHOR]

The Analytical Quality by Design (AQbD) concept was adopted to establish a quantitative analysis of multi-components with a single marker (QAMS) method for industrial lanolin alcohol, targeting cholesterol, lanosterol, and 24,25-dihydrolanosterol. The potential critical method parameters (CMPs) were identified as column temperature, flow rate, and gradient. Definitive screening design and statistical modeling were employed to optimize the gradient conditions of the mobile phase, column temperature, and flow rate. The Method Operable Design Region (MODR) was determined using a risk-based quantification approach. The robustness was assessed using a Plackett–Burman experimental design, followed by methodological validation. Optimal analytical conditions were as follows: acetonitrile (B)—water (A) mobile phase system; flow rate of 1.58 mL/min; detection wavelength of 205 nm; injection volume of 10 µL; and column temperature of 37 °C. A gradient elution program was implemented as follows: 0–19.0 min, 90.5% B; 19.0–25.0 min, 90.5–100% B; and 25.0–55.0 min, 100% B. Cholesterol served as an internal standard for quantifying lanosterol and 24,25-dihydrolanosterol, with relative correction factors of 0.4227 and 0.8228, respectively. This analytical method utilized only the cholesterol reference substance as an internal standard to quantify the content of cholesterol, lanosterol, and 24,25-dihydrolanosterol in industrial lanolin alcohol. It reduced the testing costs and enhanced efficiency, making it potentially suitable for widespread adoption in lanolin alcohol processing industries. [ABSTRACT FROM AUTHOR]

Risk management should run through the entire process of method development, utilization, and maintenance. Based on the analytical quality by design (AQbD) concept, various integrated risk management techniques were used in this study to develop an analysis method for the percolation solution of Xiaochaihu capsules. During the development of the analysis method, risk assessment was conducted using an Ishikawa diagram and failure mode effects analysis, followed by method optimization using experimental design. The probability of nonconformance calculated via an exhaustive Monte Carlo method quantitatively characterized the risk magnitude of method parameter failures, leading to the establishment of a operable design region method based on risk magnitude. Validation experiments and robustness tests of the data were utilized for model refinement and initial risk review. Methodological validation of the developed method was performed, and control strategies for the analysis method were presented through a decision tree. Stability experiments demonstrated that the samples remained stable at 4 °C for 24 h. The average recovery rate fell between 98.8% and 105%, with relative standard deviations ranging from 2.73% to 4.48%. The results showed that the established analysis method exhibited robustness. This analysis method can simultaneously determine the contents of uridine, adenine, 5-hydroxymethylfurfural, and guanosine. This method can also be employed for process control during percolation. This study integrated various risk management techniques to develop and maintain the analysis method, and this approach can potentially be extended to other analytical methods. [ABSTRACT FROM AUTHOR]

Introduction: Despite numerous successful cases, there are still some challenges in using analytical quality by design (AQbD) for the development of analytical methods. Knowledge organization helps to enhance the objectivity of risk assessment, reduce the number of preliminary exploratory experiments, identify potential critical method parameters (CMPs) and their scope. Objective: In the present study, we aimed to develop a simple, rapid, and robust analytical method for detecting phenolic compounds in Xiaochaihu capsule intermediates utilizing knowledge organization. Methods: Knowledge organization and AQbD were combined to obtain the initial analytical conditions through knowledge collection, extraction, reorganization, and analysis. The quantitative relationship between critical method attributes (CMAs) and CMPs was then established by a definitive screening design. The method operable design region was calculated using an exhaustive Monte Carlo approach based on the probability of reaching the standard. Robustness investigation and methodological validation were finally performed. Results: Analytical target profiles, CMAs, potential CMPs, and initial analytical conditions were initially identified, and the optimized ranges of operating parameters were obtained. A UHPLC method was successfully established for the analysis of phenolic compounds in ginger–ginger pinellia percolate, and the method validation outcomes were also satisfactory. Conclusion: The developed method can be a reliable means to detect the phenolic compounds of Xiaochaihu capsule intermediates. Knowledge organization provides a new approach for making better use of prior knowledge, significantly enhancing the efficiency of analytical method development. The approach is versatile and can be similarly applied to the development of other methods. This study employed an AQbD process based on knowledge organization to develop an analytical method for detecting phenolic compounds in Xiaochaihu capsule intermediate, improving the efficiency of conducting single‐factor experiments and identifying potential CMPs in the early stage of method development. Simultaneously, it offers a new approach for utilizing prior knowledge effectively. This analytical method can be used for quality control of intermediate in Xiaochaihu capsule. [ABSTRACT FROM AUTHOR]

Charged aerosol detection, increasingly recognized for quantifying pharmaceutical compounds with weak ultraviolet absorption, is a universal detection technique for high‐performance liquid chromatography (HPLC). Charged aerosol detection shows a non‐linear response with increasing analyte concentration over a wide range, limiting its versatility in various analytical applications. In this work, a co‐optimization strategy for power function value (PFV) and power laws was proposed and applied to broaden the linear range of the standard curve of saccharides in Qishen Yiqi dripping pills using the HPLC‐charged aerosol detection (HPLC‐CAD) method. Power function values for all analytes were optimized based on empirical models. Subsequently, the optimum power laws were investigated based on a preferred PFV. Additionally, various regression equations were evaluated to ensure the accuracy and precision of the results. With the optimized PFV and power law, the ordinary least squares model demonstrated a satisfactory fit. The optimal PFVs and power laws expanded the standard curve's linear range by 2.7 times compared to default settings, reducing model uncertainty. This paper presents a vital method for developing a multi‐component quantitative HPLC‐CAD approach without external data transformation outside the provided software, especially suitable for analytical applications of traditional Chinese medicine with significant quality differences. [ABSTRACT FROM AUTHOR]

Ginkgo biloba leaf extract (EGBL) is a valuable herbal extract. The main active ingredients are flavonoids, terpene lactones, organic acids and proanthocyanidins. In recent years, there have been many reports on the detection of the above active ingredients. In this paper, the analysis methods of chemical components in EGBL were reviewed, such as ultraviolet spectrophotometry, high-performance liquid chromatography, and quantitative nuclear magnetic resonance. The analysis methods of ginkgolic acids are also reviewed. Based on the current research progress, three suggestions are provided. Firstly, the quality marker research of EGBL needs to be strengthened. Secondly, more bioassay methods for EGBL quality control should be developed. Thirdly, it is necessary to strengthen the detection of proanthocyanidins in EGBL. [ABSTRACT FROM AUTHOR]

Quantity and measure value transfer is widely used to examine the correlation between the quality of Chinese herbs, Chinese herbal intermediates, and Chinese patent medicines. This study performed a quantity and measure value transfer analysis to assess the total solids yield, phenolic component yield, and phenolic component purity in the Salvia miltiorrhiza purified extract (SMPE) preparation process. The amount of extracted total solids was between 45–250 mg/g following the processes of reflux extraction, vacuum concentration, lime–sulfuric acid refining, first ethanol precipitation, second ethanol precipitation, first acidification, alkalization, thermal hydrolysis, and second acidification. Regarding yield and purity, Danshensu ranked first among all phenolic components. Additionally, a quantitative index defined as the total variation (TV) value was proposed to describe the consistency of the SMPE preparation process. The batch-to-batch variation in the SMPE came from the variable in herb quality and the preparation process, and the latter contributed more. The contribution of individual processes to the total variation (TVP) was proposed as an index to measure the impact of processes on batch-to-batch consistency. According to the TVP value, the lime–sulfuric acid refining process, the first ethanol precipitation process, and the second acidification process were all deemed crucial. When the similarity algorithms for the composition of the intermediates and SMPE were examined, the Euclidean distance outperformed the Pearson correlation coefficient, Spearman correlation coefficient, and cosine of the pinch angles. Based on the variation in the average Euclidean distance ( Δ D j ¯ ) during the process, the second ethanol precipitation, alkalization, and thermal hydrolysis processes were determined to be critical. This study clarified the primary causes of extract quality fluctuation, identified the critical processes, and examined the pharmaceutical process of traditional Chinese medicine (TCM) from the standpoint of quantity and measure value transfer. The method can be used as a reference for the analysis of other TCM pharmaceutical processes. [ABSTRACT FROM AUTHOR]