The impact of polymers on 3D microstructure and controlled release of sildenafil citrate from hydrophilic matrices

In Vitro and In Vivo Evaluation of Oral Controlled Release Formulation of BCS Class I Drug Using Polymer Matrix System

Diltiazem hydrochloride is a calcium channel blocker, which belongs to the family of benzothiazepines. It is commonly used to treat hypertension and atrial fibrillation. Even though the drug has high solubility, its high permeability and rapid metabolism in the liver can limit the bioavailability and increase the dose frequencies for up to four times per day. This study focused on a polymer matrix system not only to control the drug release but also to prolong the duration of bioavailability. The polymer matrices were prepared using different ratios of poloxamer-188, hydroxypropyl methylcellulose, and stearyl alcohol. In vitro and in vivo assessments took place using 24 rabbits and the results were compared to commercially available product Tildiem® (60 mg tablet) as reference. Overall, the rate of drug release was sustained with the gradual increase of poloxamer-188 incorporated with hydroxypropyl methylcellulose and stearyl alcohol in the matrix system, achieving a maximum release period of 10 h. The oral bioavailability and pharmacokinetic parameters of diltiazem hydrochloride incorporated in polymer matrix system were similar to commercial reference Tildiem®. In conclusion, the combination of polymers can have a substantial effect on controlling and prolonging the drug release pattern. The outcomes showed that poloxamer-188 combined with hydroxypropyl methylcellulose and stearyl alcohol is a powerful matrix system for controlling release of diltiazem hydrochloride.

Quantitative Measures of Crystalline Fenofibrate in Amorphous Solid Dispersion Formulations by X-Ray Microscopy

In the pharmaceutical industry, amorphous solid dispersion can be utilized to enhance the solubility, hence bioavailability, of poorly solubility active pharmaceutical ingredients owing to the higher free energy of the amorphous state. Measuring the concentration, size and spatial distribution of crystalline API particles that may be present in amorphous solid dispersions (ASD) is critical to understanding product performance and developing improved formulations. In this study X-Ray Microscopy (XRM) was used to nondestructively measure these attributes in ASDs. Model tablets of amorphous fenofibrate in a copovidone matrix spiked with known concentrations of crystalline fenofibrate were examined by XRM to measure the concentration, size and distribution of crystalline particles in the tablets. Data collection and analysis conditions were evaluated and reported. XRM images showed contrast between the crystalline API and the amorphous matrix of the tablet. Image analysis using basic thresholding provided quantitative and distribution data of the crystallinity present. Crystals as small as 10 μm were detected and practical quantitation limits of 0.2% (w/w of total tablet) crystallinity were demonstrated. The aspects of manual data thresholding were tested for operator influence and threshold selection and found to be robust. This technique was demonstrated to provide quantitative measures of crystallinity below standard X-Ray Powder Diffraction (XRPD) techniques, provide three-dimensional information regarding size, shape and distribution of API crystals and can be performed nondestructively.

Fast, Spectroscopy-Based Prediction of In Vitro Dissolution Profile of Extended Release Tablets Using Artificial Neural Networks

The pharmaceutical industry has never seen such a vast development in process analytical methods as in the last decade. The application of near-infrared (NIR) and Raman spectroscopy in monitoring production lines has also become widespread. This work aims to utilize the large amount of information collected by these methods by building an artificial neural network (ANN) model that can predict the dissolution profile of the scanned tablets. An extended release formulation containing drotaverine (DR) as a model drug was developed and tablets were produced with 37 different settings, with the variables being the DR content, the hydroxypropyl methylcellulose (HPMC) content and compression force. NIR and Raman spectra of the tablets were recorded in both the transmission and reflection method. The spectra were used to build a partial least squares prediction model for the DR and HPMC content. The ANN model used these predicted values, along with the measured compression force, as input data. It was found that models based on both NIR and Raman spectra were capable of predicting the dissolution profile of the test tablets within the acceptance limit of the f2 difference factor. The performance of these ANN models was compared to PLS models using the same data as input, and the prediction of the ANN models was found to be more accurate. The proposed method accomplishes the prediction of the dissolution profile of extended release tablets using either NIR or Raman spectra.