ABSTRACT
The spatial distribution uniformity of valuable medicines is the critical quality attribute in the process control of Tongren Niuhuang Qingxin Pills. With the real world sample of the mixed end-point powder of Tongren Niuhuang Qingxin Pills as the research object, hyperspectral imaging technology was used to collect a total of 32 400 data points with a size of 180 pix×180 pix. Spectral angle matching(SAM), classical least squares and mixed tuned matched filtering(MTMF) were used to identify the spatial distribution of rare medicines. MTMF model showed higher identification accuracy, therefore the spatial distribution of the blended intermediates was identified based on the MTMF model. The histogram method was also used to evaluate the spatial distribution uniformity of rare medicines. The results showed that the standard deviation was 4.78, 6.5, 3.48, 1.96, and 3.00 respectively for artificial bezoar, artificial musk, Borneol, Antelope horn and Buffalo horn; the variance was 22.8, 42.3, 12.1, 3.82, and 9.00, and the skewness was 1.26, 1.71, 0.06,-0.86, and 1.04, respectively. The final results showed that the most even blending was achieved in concentrated powder of Borneol, Antelope horn and Buffalo horn, followed by artificial bezoar, and last artificial musk. A visualization method was established for quality attributes of distribution uniformity in blending process of Tongren Niuhuang Qingxin Pills. It could provide evidences of quality control methods in the mixing process of big brand traditional Chinese medicine.
Subject(s)
Drugs, Chinese Herbal , Medicine, Chinese Traditional , Powders , Quality ControlABSTRACT
Objective: Using Qingrun Pill as model drug, the raw material powder of Qingrun Pill with uniform mixture was prepared. The rapid analysis method was used to evaluate the mixing uniformity of Qingrun Pill raw materials. Methods: Based on the particle design technology, the raw material powder of Qingrun Pill was prepared, the core-shell particles were established with the particle size as the index, and the mixing uniformity of the raw material powder of Qingrun Pill was analyzed with the standard deviation of moving block as the index by near infrared spectroscopy. Finally, it was verified by HPLC. Results: According to the particle design technology, the raw material powder of Qingrun Pill was designed. Shell particles: Rheum officinale and other materials; Nuclear particles: Scutellaria baicalensis and other materials; The particle size (d0.9) of shell particles at ultrafine grinding for 12 min was about 5 μm, and that of nuclear particles at ultrafine grinding for 6 min was about 130 μm. The ratio of nuclear particles to shell particles was more than 10:1, which met the requirements of particle design. Near-infrared spectroscopy showed that shell particles were ultrafine comminuted for 12 min, and then the nuclear particles were mixed evenly for 6 min. Conclusion: In this study, Qingrun Pill powder was prepared based on particle design technology, and the mixing uniformity of powder was evaluated by near infrared spectroscopy. This method is simple and feasible, real-time, and without destroying the sample.
ABSTRACT
OBJECTIVE: To establish a nondestructive and rapid analysis method to measure the critical parameter, mixing uniformity, in the production of Ginkgo leaf dispersible tablets in order to control the quality of products. METHODS: The near-infrared diffuse reflectance spectroscopy (NIRDRS) spectra of the pre-mix and the total mixed Ginkgo leaf dispersible tablets (Wuhan Jianmin Suizhou Pharmaceutical Co., Ltd.) were obtained. The mixing uniformity of samples was monitored by quantitative analysis model and standard deviation method combined with the Mahalanobis distance method, respectively. Meanwhile, lab-made mixing samples and dynamic simulation mixing process were used to validate the feasibility of Mahalanobis distance method. RESULTS: The results obtained from quantitative analysis model and standard deviation method were consistent with each other, and the Mahalanobis distance method was feasible for monitoring the mixing process. CONCLUSION: The method is rapid, simple, and can be used for online and sideline analysis in drug production process.