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

Abstract

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 optimized solid formulation containing fruits extracts of Momordica charantia and Abelmoschus esculentus

“…Since, in formulation development, the responses of interest are a function of the composition of the mixture, With D-optimal mixture design, the interactions of the mixture's composition could be modeled, graphically or mathematically, to reveal regions of desirable formulation compositions that meet the product's quality criteria. Our findings that the D-optimal mixture approach provides a model that adequately predicted the optimal design space are similar to those reported in other studies [37][38][39]58].…”

“…The D-optimal mixture design is the most popular response surface methodology used in formulation studies [37][38][39]. It investigates the main effects and interaction effects between the independent variables of the experiment on the responses.…”

“…Thus, it requires a rigorous approach to select excipients that could improve the extract's unfavorable physicochemical properties such as hygroscopicity and stickiness to meet the predetermined product's critical quality attributes (CQAs). In recent years, response surface methodology (RSM) utilizing D-optimal mixture design has emerged as the preferred statistical formulation approach for analyzing the interrelations between mixture composition and CQAs [37][38][39]. The popularity of this statistical approach could be due to its reliability in reducing the time and cost of identifying desirable formulation compositions that meet the product's quality criteria [40].…”

Real‐time detection of Angelica dahurica tablet using YOLOX_am

“…For example, Angelica dahurica tablet has shown impressive efficacy in the treatment of COVID‐19. Herbal tablets are simple, convenient, and inexpensive oral solid dosage forms with high physicochemical and microbiological stabilities (Oh et al, 2019). The dosage of herbal tablets can be flexibly adjusted according to the actual medical cases.…”