ABSTRACT
Based on near infrared spectroscopy and high performance liquid chromatography, this paper established the regression relationship between near infrared spectroscopy and index component content of Huoxiang Zhengqi oral liquid, so as to realize the rapid detection of index component content based on near infrared spectroscopy. Magnolol, honokiol and hesperidin were used as the quality indexes of Huoxiang Zhengqi oral liquid. After using the first derivative and normalization pretreatment method, characteristic variables were screened by CARS, and the correction model was finally established by partial least-squares regression (PLSR) method. The method accuracy was evaluated with the external validation, and the prediction results were tested for significance. The results indicated that when the near infrared spectrum was scanned through the bottle, the model's correlation coefficients of prediction (Rp) were higher than 0.99, the root mean square errors of the prediction models (RMSEP) were all less than 0.008 4, and the relative standard errors of prediction set (RSEP) were all less than 2.83%. There was no significant difference in the predicted results between these two kinds of model. The models established in the non-destructive way have good performance and high prediction accuracy. The rapid and nondestructive way has application value in the quality control of Huoxiang Zhengqi oral liquid.
ABSTRACT
This study established a method for rapid quantification of terpene lactone, bilobalide, ginkgolide C, ginkgolide A and ginkgolide B in the chromatographic process of Ginkgo Folium based on near infrared spectroscopy(NIRS). The effects of competitive adaptive reweighting sampling(CARS), random frog(RF), and synergy interval partial least squares(siPLS) on the performance of partial least squares regression(PLSR) model were compared to the reference values measured by HPLC. Among them, the correlation coefficients of prediction(Rp) of validation sets of terpene lactone, bilobalide, and ginkgolide C were all higher than 0.98, and the relative standard errors of prediction(RSEPs) were 5.87%, 6.90% and 6.63%, respectively. Aiming at ginkgolide A and ginkgolide B with relatively low content, the genetic algorithm joint extreme learning machine(GA-ELM) was used to establish the optimized quantitative analysis model. Compared with CARS-PLSR model, the CARS-GA-ELM models of ginkgolide A and ginkgolide B exhibited a reduction in RSEP from 15.65% to 8.52% and from 21.28% to 10.84%, respectively, which met the needs of quantitative ana-lysis. It has been proved that NIRS can be used for the rapid detection of various lactone components in the chromatographic process of Ginkgo Folium.
Subject(s)
Chromatography, High Pressure Liquid , Ginkgo biloba , Lactones/analysis , Least-Squares Analysis , Spectroscopy, Near-Infrared/methodsABSTRACT
In the past few years, continuous manufacturing(CM) has been put forward by the FDA. Pharmaceutical enterprises are encouraged to promote the implementation of CM, which has become a hot research direction of pharmaceutical technology. In February 2019, the FDA issued a draft guideline for the implementation of CM, which greatly promoted the development of CM and provided reference for continuous manufacturing of traditional Chinese medicine(TCM). The production process of TCM is a complex system. With the innovation of production equipment and the promotion of automation and informatization of TCM production, the exis-ting policies, regulations and traditional production control capacity are difficult to meet the market demand for high-quality TCM pro-ducts. In this paper, we reviewed the new technologies and methods of quality control in accordance with the characteristics of TCM production by referring to modern manufacturing technology, information technology and quality control technology. Based on the "QbD" theory and "PAT" technology, process knowledge system(PKS), an advanced control strategy, was proposed to provide a reference for the implementation of CM in TCM production.