In-Line Quality Control Of Extraction And Column Chromatographic Processes Of Ginkgo Biloba

Traditional Chinese medicine (TCM) is a complex system and the typical manufacturing processes include extraction, concentration, purification, etc. Each unit operation involves a set of process parameters. Variations in raw materials and process parameters may affect the quality of the final product, and quality control strategies are needed in the manufacturing process. However, as conventional methods need a long analytical time, it is dissatisfactory to use them for process monitoring and control in the manufacturing of TCM.To solve the problem, near infrared spectroscopy (NIRS) and multivariate data analysis technique were used in this work. Two key unit operations (extraction and chromatographic processes) in the manufacturing of Ginkgo biloba extract were taken as case studies. The main contents are summarized as follows:1. An in-line analysis method for the extract process was established based on NIRS. Firstly, a reference method was developed for simultaneous quantification of three flavonol glycosides, quercetin, kaempferol and isorhamnetin, using high performance liquid chromatography (HPLC). Secondly, multivariate calibration models were established for in-line quantification of the three flavonol glycosides and total flavonol glycosides using NIRS.2. Methods for the end-point detection of elution process were established. NIRS was used in conjunction with various data analysis methods such as moving block standard deviation (MBSD) and principal component analysis-moving block standard deviation (PCA-MBSD) for end-point detection of elution process. Compared with the results validated by HPLC, PCA-MBSD was chosen as the most suitable method.3. An in-line monitoring method for the elution process using visible and near-infrared spectroscopy in conjunction with multivariate statistical process control (MSPC) was established. Experiments including normal operating batches and abnormal operating batches were carried out. The MSPC model for the elution process was developed and validated. The abnormalities were detected successfully by the control charts of principal component scores, Hotelling T2 or DModX. The results suggested that the established method can be used for the in-line monitoring and batch-to-batch consistency evaluation of the elution process.