The use of scanning electron microscopy provides useful information to further understand drug release mechanisms from matrix tablets.

An artificial neural network was used to optimize the release of salbutamol sulfate from hydrophilic matrix formulations. Model formulations to be used for training, testing and validating the neural network were manufactured with the aid of a central composite design with varying the levels of Methocel® K100M, xanthan gum, Carbopol® 974P and Surelease® as the input factors. In vitro dissolution time profiles at six different sampling times were used as target data in training the neural network for formulation optimization. A multi layer perceptron with one hidden layer was constructed using Matlab®, and the number of nodes in the hidden layer was optimized by trial and error to develop a model with the best predictive ability. The results revealed that a neural network with nine nodes was optimal for developing and optimizing formulations. Simulations undertaken with the training data revealed that the constructed model was useable. The optimized neural network was used for optimization of formulation with desirable release characteristics and the results indicated that there was agreement between the predicted formulation and the manufactured formulation. This work illustrates the possible utility of artificial neural networks for the optimization of pharmaceutical formulations with desirable performance characteristics.

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The objective of these studies was to develop a discriminatory in vitro release test for assessing formulation factors that may affect oxytocin (OT) release during formulation development studies of a Pluronic® F127 OT in situ gel-forming parenteral dosage form. An appropriate release assessment method should be able to discriminate between the performance of different formulation compositions (1, 2), and this was the primary criterion used for selection of an appropriate test procedure during the test method development process. ANOVA and the difference (f 1 ) and similarity (f 2 ) factors were used to evaluate the discriminatory behavior of different test methods that were investigated in these studies. The in vitro release tests that were investigated included the use of USP Apparatus 1, 2, and 3; a dialysis bag in USP Apparatus 2; and a membrane-less diffusion method. It was concluded that the use of USP Apparatus 3 was best able to discriminate between OT release for the different formulations tested. USP Apparatus 3 was thus considered the most suitable in vitro release test apparatus for studying formulation factors affecting OT release during the development of a parenteral dosage form prepared using Pluronic® F127.

The objective of this study was to develop a hydrophilic matrix formulation with in vitro release characteristics similar to Asthalin(®) tablets and that would sustain the release of salbutamol sulfate over a 12-h period. A central composite design was used as the framework for manufacturing formulations that may be used to understand the relationships between polymer levels and in vitro release characteristics. Tablets were manufactured using wet granulation with Surelease(®) as the granulating fluid and different levels of Methocel(®) K100M, xanthan gum, and Carbopol(®) 974P as matrix-forming materials. In vitro dissolution testing was conducted using USP Apparatus 3 and samples were analyzed using a validated reversed-phase HPLC method. The results revealed that the levels and types of polymers had a significant impact on the rate of drug release from these formulations and that it was possible to optimize the levels of matrix-forming polymers to achieve the desired release characteristics. Statistical design and response surface methodology have been successfully used to understand and optimize formulation factors and interactions that impact the in vitro release characteristics of salbutamol sulfate from a potential multisource sustained release dosage form.