Multiscale Modelling and AI-Driven Prediction of Particle Formation and Interactions Governing Inhalation Powder Performance

Description

Research scientist: Saaransh Saxena, doktorand
Principal Investigator: Professor Göran Frenning, Department of Pharmaceutical Biosciences, Uppsala University

Scientific and industrial context: The performance of dry powder inhaler formulations depends critically on the flowability and dispersibility of the powder. These properties are governed by particle morphology, surface composition, and interparticle interactions. They are strongly influenced by particle formation processes such as spray drying. Despite their importance for both manufacturing and drug delivery performance, the fundamental relationships linking particle formation mechanisms, particle characteristics, and bulk powder behaviour remain insufficiently understood. Recent advances in artificial intelligence and machine learning (AI/ML), together with mechanistic modelling approaches, provide new opportunities to uncover and quantify these complex relationships, enabling improved predictive capabilities for pharmaceutical powder systems.

Aim: To develop a mechanistic and predictive understanding of the factors governing flowability and dispersibility of inhalation powders. The research will investigate how particle-level characteristics, including interparticle interactions and particle morphology arising from particle formation processes, influence the macroscopic behaviour of powders relevant to inhalation formulations. By combining mechanistic insight with AI/ML-driven predictive approaches, and supporting these with targeted experimental investigations, the project seeks to establish quantitative relationships between particle properties and bulk powder performance, enabling more rational design and optimization of inhalation powders.

Outcome: To advance the fundamental understanding of how particle characteristics and interparticle interactions determine powder behaviour in inhalation systems. The results will contribute to the development of predictive tools and formulation strategies for inhalation powders with improved manufacturability, robustness, and aerosol performance.