John Armstrong

Dr. John Armstrong is a Research Fellow at the Strathclyde Institute of Pharmacy and Biomedical Sciences within the University of Strathclyde's Faculty of Science. His work focuses on computational approaches to pharmaceutical manufacturing challenges, particularly in the areas of powder flow prediction and tablet dissolution performance modeling.

Armstrong's research interests span pharmaceutical powder flow prediction, deep learning applications in pharmaceuticals, tablet dissolution performance modeling, pharmaceutical crystallization, and computational modeling for pharmaceutical manufacturing. His work integrates advanced computational techniques with pharmaceutical science to improve manufacturing processes and product quality.

His recent publications demonstrate a strong focus on applying machine learning and computational modeling to solve practical pharmaceutical manufacturing challenges. The 2024 paper on flexible modeling of tablet dissolution shows how computational approaches can predict drug release profiles, while the 2023 deep learning study demonstrates innovative methods for predicting powder flow from microscopy images, bridging the gap between material characterization and process performance.

Armstrong serves as Principal Investigator for the project "From Pixels to Particles: A Computational Toolbox for Predicting Pharmaceutical Powder Characteristics" (2023-2024), which develops computational tools to predict pharmaceutical powder properties from image data. His research is closely aligned with the CMAC (Continuous Manufacturing and Crystallisation) facility at Strathclyde, contributing to advancements in continuous pharmaceutical manufacturing.