Modeling the drug release from hydrogel-based matrices

In this work the behavior of hydrogel-based matrices, the most widespread systems for oral controlled release of pharmaceuticals, has been mathematically described. In addition, the calculations of the model have been validated against a rich set of experimental data obtained working with tablets made of hydroxypropyl methylcellulose (a hydrogel) and theophylline (a model drug). The model takes into account water uptake, hydrogel swelling, drug release, and polymer erosion. The model was obtained as an improvement of a previous code, describing the diffusion in concentrated systems, and obtaining the erosion front (which is a moving boundary) from the polymer mass balance (in this way, the number of fitting parameters was also reduced by one). The proposed model was found able to describe all the observed phenomena, and then it can be considered a tool with predictive capabilities, useful in design and testing of new dosage systems based on hydrogels

3D multi-agent models for protein release from PLGA spherical particles with complex inner morphologies

In order to better understand and predict the release of proteins from bioerodible micro- or nanospheres, it is important to know the influences of different initial factors on the release mechanisms. Often though it is difficult to assess what exactly is at the origin of a certain dissolution profile. We propose here a new class of fine-grained multi-agent models built to incorporate increasing complexity, permitting the exploration of the role of different parameters, especially that of the internal morphology of the spheres, in the exhibited release profile. This approach, based on Monte-Carlo (MC) and Cellular Automata (CA) techniques, has permitted the testing of various assumptions and hypotheses about several experimental systems of nanospheres encapsulating proteins. Results have confirmed that this modelling approach has increased the resolution over the complexity involved, opening promising perspectives for future developments, especially complementing in vitro experimentation

Elaborating Transition Interface Sampling Methods

We review two recently developed efficient methods for calculating rate constants of processes dominated by rare events in high-dimensional complex systems. The first is transition interface sampling (TIS), based on the measurement of effective fluxes through hypersurfaces in phase space. TIS improves efficiency with respect to standard transition path sampling (TPS) rate constant techniques, because it allows a variable path length and is less sensitive to recrossings. The second method is the partial path version of TIS. Developed for diffusive processes, it exploits the loss of long time correlation. We discuss the relation between the new techniques and the standard reactive flux methods in detail. Path sampling algorithms can suffer from ergodicity problems, and we introduce several new techniques to alleviate these problems, notably path swapping, stochastic configurational bias Monte Carlo shooting moves and order-parameter free path sampling. In addition, we give algorithms to calculate other interesting properties from path ensembles besides rate constants, such as activation energies and reaction mechanisms.Comment: 36 pages, 5 figure