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Pharmaceutics. 2019 Feb 13;11(2). pii: E79. doi: 10.3390/pharmaceutics11020079.

Multivariate Statistical Optimization of Tablet Formulations Incorporating High Doses of a Dry Herbal Extract.

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College of Pharmacy, The Catholic University of Korea, Bucheon 14662, Korea.
College of Pharmacy, The Catholic University of Korea, Bucheon 14662, Korea.
College of Pharmacy, Ajou University, Suwon 16499, Korea.
College of Pharmacy and Research Institute of Life and Pharmaceutical Sciences, Sunchon National University, Suncheon 57922, Korea.


The development of oral tablet formulation for herbal medicines has been restricted by large drug loadings and the poor physicochemical and mechanical properties of dry herbal extracts (DHEs). Herein, statistical experimental designs were applied to herbal tablet formulation development and optimization using Wuzi Yanzong dry extract (WYE). The tablet disintegration time and hardness were identified as the critical quality attributes (CQAs) of the product. The tablet formulation was designed to achieve a high drug loading (50% or higher of WYE), shorter tablet disintegration time (less than 30 minutes), and suitable hardness (6.0 to 7.5 kp). A D-optimal mixture design was used to evaluate the effects of excipients on CQAs to minimize the risk compression failure and improve the tabletability in formulations containing WYE at 50% and 65% by weight. A partial least squares model was used to elucidate the multivariate relationships between a large number of formulation variables and product CQAs, and determine the maximum possible WYE loading. From overlaid plots of the effects of formulation variables on CQAs, it was found that a maximum WYE loading of 67% in tablet formulation satisfied the acceptance criteria of CQAs. In conclusion, this study shows that multivariate statistical tools are useful for developing tablet formulations containing high doses of herbal extracts and establishing control strategies that ensure product quality.


D-optimal mixture design; herbal dry extract; herbal tablet formulation; multivariate statistical design; partial least square

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