Metodi Predittivi per la Formazione di Addotti Supramolecolari di Antinfiammatori Non Steroidei

The master project is focused on the field of supramolecular and pharmaceutical chemistry. It consists in the prediction, synthesis and characterization of new multicomponent crystal forms of 2-phenilpropionic acid. This molecule was selected because it is the basis of several Non-Steroidal Anti-Inflammatory Drugs (NSAIDs). A very challenging step in co-crystal design is the selection of a coformer that is likely to form weak interactions with the API, as well as to improve its properties. The most commonly used method for coformer selection is also the most time consuming and is based on the trial-and-error approach, in which coformers are chosen from a list of pharmaceutically acceptable molecules, accordingly to affinity in terms of probability of forming supramolecular synthons. A tools for predicting the possibility of co-crystallization is desirable to minimize the waste of reagents, time and costs. In this project a predictive model was built on three different computational methods based on physical properties of molecules: Hydrogen Bond Energy (HBE), which considers the possibility of establishing hydrogen bonds as supramolecular synthons; Molecular Complementarity (MC) which is based on structural similarity and Hansen Solubility Parameters (HSP) which evaluates the mutual miscibility between coformers and API. The supramolecular adducts were synthetised thanks to different solvent-free and solvent-based synthesis techniques like grinding, kneading, slurry and slow evaporation. Finally, the obtained adducts were characterised with solid-state NMR, powder X-Ray diffraction and single-crystal X-Ray diffraction for experimental evidence of the predicted outcomes.