Development of new drug delivery systems for drugs as relevant as praziquantel (for schistosomiasis disease), without increasing the final cost of the treatment, are current challenges of the pharmaceutical industry to contribute to global health. The use of efficient and novel methodologies or techniques based on computational chemistry able to predict the release kinetics of the drugs in low-cost natural inorganic carriers, like clay minerals, could be of great help to improve the biopharmaceutical profile of the drugs. This would mean a huge saving in the costs of the investigation, allowing a fast screening of the performance of a great number of drug-clay systems and reducing the time with respect to in vitro experimental tests. Therefore, our goal in this project was to apply the state-of-the-art methodologies (enhanced sampling methods) to establish a solid and accurate enough computational strategy for drug release simulations from clays and apply it to the systems of relevance according to the World Health Organization. With the work carried out in this project, we have developed a viable computational strategy using as a model praziquantel and montmorillonite clay as drug and excipient, respectively, that can be applied in other drug release simulations. By applying this strategy, we obtain the drug release time, rate, and diffusion coefficient, as well as the mechanism of the drug release from the excipient. These studies open a new field of research aimed at improving the design and development of new drugs in a faster and more efficient way.
