Statistical modeling methods to analyze the impacts of multiunit process variability on critical quality attributes of Chinese herbal medicine tablets

Abstract

The quality of Chinese herbal medicine tablets suffers from batch-to-batch variability due to a lack of manufacturing process understanding. In this paper, the Panax notoginseng saponins (PNS) immediate release tablet was taken as the research subject. By defining the dissolution of five active pharmaceutical ingredients and the tablet tensile strength as critical quality attributes (CQAs), influences of both the manipulated process parameters introduced by an orthogonal experiment design and the intermediate granules’ properties on the CQAs were fully investigated by different chemometric methods, such as the partial least squares, the orthogonal projection to latent structures, and the multiblock partial least squares (MBPLS). By analyzing the loadings plots and variable importance in the projection indexes, the granule particle sizes and the minimal punch tip separation distance in tableting were identified as critical process parameters. Additionally, the MBPLS model suggested that the lubrication time in the final blending was also important in predicting tablet quality attributes. From the calculated block importance in the projection indexes, the tableting unit was confirmed to be the critical process unit of the manufacturing line. The results demonstrated that the combinatorial use of different multivariate modeling methods could help in understanding the complex process relationships as a whole. The output of this study can then be used to define a control strategy to improve the quality of the PNS immediate release tablet.

A novel strategy for the quality control of carbonized Typhae pollen using colorimeter, liquid chromatography–mass spectrometry, and efficacy evaluation coupled with multivariate statistical analysis

“…It could be concluded that the block of chemical components ( X 2 ) possessed a greater importance than that of colors ( × 1 ) in terms of their correlation with the efficacy of CTP. Likewise, as shown in Figure 5b, the variables involved in each data block were analyzed to determine their importance for the model prediction (Sun et al, 2016). The results revealed the following variables as the ones highly correlating with the hemostatic effect of CTP—a*( x 2 ), 3,4‐dihydroxybenzoic acid ( x 4 ), 4‐hydroxybenzoic acid ( x 5 ), 3‐hydroxybenzoic acid ( x 7 ), quercetin‐3‐ O ‐glucoside ( x 15 ), azelaic acid ( x 16 ), kaempferol‐3‐ O ‐glucoside ( x 18 ), quercetin ( x 19 ), naringenin ( x 20 ), kaempferol ( x 21 ), and isorhamnetin ( x 22 ).…”

Improved Understanding of the High Shear Wet Granulation Process under the Paradigm of Quality by Design Using Salvia miltiorrhiza Granules

“…These plant extracts are very sticky and actually hinder the granulation process. Hence, to improve this unsatisfactory condition, a binder solution such as ethanol is needed to mitigate the extra viscosity [51]. Thus, in this study, ethanol of different concentrations was selected as the binder solution.…”

A Novel Framework to Aid the Development of Design Space across Multi-Unit Operation Pharmaceutical Processes—A Case Study of Panax Notoginseng Saponins Immediate Release Tablet

“…Interpretation of the parameters in the system model can help to identify correlations among the variables of different blocks. Loadings of the model indicate which process parameters and attributes affect product quality and estimate their contribution to quality [45]. The variable importance in the projection (VIP) [46] helps identify the CPPs that contribute most to the product quality.…”