Impact of Process Parameters and Formulation Properties on Dissolution Performance of an Extended Release Tablet: a Multivariate Analysis

Dissolution profile prediction of sinomenine hydrochloride sustained release tablets, part II: a multisource data fusion approach

“…PLS regression identifies the underlying latent variables (LVs) that explain the covariance between the spectral dataset (X) and responses (Y variable) by constructing a set of new variables. 1 These LVs are linear combinations of the original predictors and explain as much variance as possible in the predictors while being highly correlated with the responses. To characterize the goodness of models, the coefficient of determinations ( R 2 ) and the root mean square errors (RMSE) were also calculated individually for the calibration, cross-validation and prediction (external validation) of samples.…”

“…The dissolution of solid oral dosage formulations is an important quality attribute that characterizes the in vivo behavior and bioavailability of drugs. 1 Particularly, the in vitro dissolution profile is significant as it is linked to the in vivo therapeutic efficacy. 2 Currently, in vitro dissolution testing is widely used during drug development and implemented for controlling product quality.…”

Prediction of dissolution profiles of sinomenine hydrochloride sustained-release tablets part I: using near-infrared spectra as predictors

“…In other words, the process of dissolution testing is still cumbersome. 8 Moreover, several studies have suggested that conical sedimentation can occur beneath the paddle after tablet disintegration, resulting in significant unpredictability and variability in dissolution tests using apparatus II. 9,10 Despite the fact that a new method has been proposed to estimate the quantitative impact of formulation and drug sedimentation or ''coning'' on dissolution in a recent study, 11 there is no doubt that the development can be time-consuming.…”