Fast Screening and Designing Drug-Loaded Polymeric Nanoparticles via Thermodynamic Prediction

Active pharmaceutical ingredients (API) -polymer miscibility is considered to be an essential prerequisite for the successful formulation of a physically stable solid dispersion. The objective of the development of an API-polymer miscible binary system is to provide an environment in which the crystallinity of API is so altered as to manipulate its solubility and nucleation rate. In an API-polymer miscible system, it is expected that the local environment of API and the physical stability of API are altered due to molecular level mixing of API with polymers. Owing to the potential for the successful formulation of a poorly water-soluble API, the study of miscibility of API with polymers has become the important topic in both academic and industrial research. To establish a method for predicting API and polymer compatibility as a means to guide formulation development, we predict thermodynamics of binary system through free energy calculations based on Flory-Huggins interaction parameter and group contribution method (GCM). The degree of compatibility between API and polymers has been predictable by GCM which is of importance in the design of a wide range of delivery systems including block copolymer micelles.

      In experiments, ibuprofen is the model drug to validate our prediction models. Three kinds of block copolymers (BCPs) were used to encapsulate ibuprofen.  The results reveal that the prediction of interaction between API and polymers by GCM is efficiently for fast screening candidates. After validation, this method can be developed for the other common pharmaceutical polymers for their ability to yield a stable formulation system in pharmaceutical industry and as an initial tool for fast screening of immiscible combination of a polymer and API.