Demonstrate how machine learning tools can aid development of formulation, analysis and manufacturing of pharmaceutical drug products

A first example of diglycolamide flow synthesis was developed, showcasing algorithm-accelerated reaction optimization and its potential to accelerate ligand discovery and enable autonomous, AIcontrolled manufacturing of critical materials. The increasing demand for manufacturing rare-earth elements (REEs) as critical materials has intensified research on sustainable synthesis of advanced extractants such as diglycolamides (DGAs).

Screening powder properties such as flowability, compressibility, and particle geometry is crucial for controlling ceramic processing, particularly in automated workflows that demand high reproducibility. Sacrificial templating for porous ceramics is well suited to automation because it is prone to variability arising from manual handling.

At the University of Liverpool, AI-powered robots are transforming lab work.