Evidence map›Paper›PMID 33150773›Full record

ArticleJournal of Zhejiang University. Science. B

A near-infrared spectroscopy-based end-point determination method for the blending process of Dahuang soda tablets.

Si-Jun Wu, Ping Qiu, Pian Li, Zheng Li, Wen-Long Li

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Article in Journal of Zhejiang University. Science. B. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

5 authors.

Si-Jun WuCollege of Pharmaceutical Engineering of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China.
Ping QiuHunan Zhengqing Pharmaceutical Group Co., Ltd., Huaihua 418005, China.
Pian LiLangtian Pharmaceutical (Hubei) Co., Ltd., Huangshi 435000, China.
Zheng LiCollege of Pharmaceutical Engineering of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China.
Wen-Long LiCollege of Pharmaceutical Engineering of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study is aimed to explore the blending process of Dahuang soda tablets. These are composed of two active pharmaceutical ingredients (APIs, emodin and emodin methyl ether) and four kinds of excipients (sodium bicarbonate, starch, sucrose, and magnesium stearate). Also, the objective is to develop a more robust model to determine the blending end-point.

methodsQualitative and quantitative methods based on near-infrared (NIR) spectroscopy were established to monitor the homogeneity of the powder during the blending process. A calibration set consisting of samples from 15 batches was used to develop two types of calibration models with the partial least squares regression (PLSR) method to explore the influence of density on the model robustness. The principal component analysis-moving block standard deviation (PCA-MBSD) method was used for the end-point determination of the blending with the process spectra.

resultsThe model with different densities showed better prediction performance and robustness than the model with fixed powder density. In addition, the blending end-points of APIs and excipients were inconsistent because of the differences in the physical properties and chemical contents among the materials of the design batches. For the complex systems of multi-components, using the PCA-MBSD method to determine the blending end-point of each component is difficult. In these conditions, a quantitative method is a more suitable alternative.

conclusionsOur results demonstrated that the effect of density plays an important role in improving the performance of the model, and a robust modeling method has been developed.

Indexed as

TabletsCalibrationEmodinEtherHumansLeast-Squares AnalysisModels, StatisticalPowdersPrincipal Component AnalysisRegression AnalysisSodium BicarbonateSpectroscopy, Near-InfraredStarchStearic AcidsSucroseEmodinEtherPowdersSodium BicarbonateStarchstearic acidStearic AcidsSucroseTabletsProcess analytical technology; Blending process; Near-infrared spectroscopy; End-point determination

Identifiers

PMID33150773
PMCPMC7691685

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.