Predicting Complexation Performance between Cyclodextrins and Guest Molecules by Integrated Machine learning and Molecular Modeling Techniques

In conclusion, the developed predictive models were able to quickly and accurately predict the solubilizing capacity of CD systems. Current research has taken an important step toward the application of machine learning in pharmaceutical formulation design.Graphical abstractCurrent research presented an alternative to traditionally trial-and-error experimentation for drug–CD formulation development. It revealed that the integration of experimental determinations, molecular modeling calculation and data-driven machine learning techniques could provide a new solution for highly efficient and accurate formulation development in the future.
Source: Acta Pharmaceutica Sinica B - Category: Cancer & Oncology Source Type: research