Developing analytical data-informed statistical models for predicting the physical stability of drug-polymer solid dispersions using high-throughput 2D printed arrays - Ghazi, Noha (2024)
Introduction: Amorphous solid dispersions (ASDs) offer a promising strategy to address the poor solubility challenges in over 40% of newly discovered active pharmaceutical ingredients (APIs). Despite the potential advantages of solid dispersions, some challenges would hinder the development of ASDs such as scaling up and physical instability that lead to phase segregation and possible further recrystallization of the API, particularly during the storage period. Traditional preparation methods of ASDs as well as analytical techniques to assess formulation stability may require samples on a milligram-to-gram scale. However, whilst a number of drugs and polymers have been studied in the literature, the number of researched APIs and their loading with different polymers is still very limited, and model development is often done for each system in isolation, making it difficult to draw any general conclusions regarding the physicochemical properties of APIs that would be highly correlated to the stability of those ASDs. Therefore, this thesis aims to combine the use of a novel high-throughput miniaturised screening approach for printing nano-arrays of a relatively larger number of samples than previously reported using a minimal amount of materials in picoliter with statistical modelling of the outcome stability data. That model could correlate the stability of solid dispersion formulations with the physicochemical properties of the utilized APIs. Then to test the predictive power of 2D inkjet printing through 3D inkjet printing, highlighting its utility in anticipating the physical stability of scaled-up drug-polymer dispersions.