Elucidating molecular properties of kappa-carrageenan as critical material attributes contributing to drug dissolution from pellets with a multivariate approach.

Multivariate data analysis (MVDA) and artificial neural networks (ANN) are supporting statistical methodologies required for successful development and manufacturing of drug products. To address this purpose, a complex dataset from 49 industrially produced capsules filled with pellets was first analyzed through the development of a multiple linear regression model focused on determining raw material attributes or process parameters with a significant impact on drug dissolution. Based on the model, the following molecular and micrometrics properties of κ-carrageenan have been identified as critical material attributes with the highest contribution to drug dissolution: molecular weight and polydispersity index, viscosity, content of potassium ions, wettability, particle size, and density.

Theory for the three-dimensional Mercedes-Benz model of water.

The two-dimensional Mercedes-Benz (MB) model of water has been widely studied, both by Monte Carlo simulations and by integral equation methods. Here, we study the three-dimensional (3D) MB model. We treat water as spheres that interact through Lennard-Jones potentials and through a tetrahedral Gaussian hydrogen bonding function.

Ion pairing in molecular simulations of aqueous alkali halide solutions.

Using classical molecular dynamics simulations, we study ion-ion interactions in water. We study the potentials of mean force (PMF) for the full set of alkali halide ion pairs, and in each case, we test different parameter sets for modeling both the water and the ions. Altogether, we compared 300 different PMFs.