Artificial Intelligence algorithms to predict aggregation and gel phenomena in peptide synthesis and isolation

Peptides hold significant potential as therapeutic agents in the pharmaceutical industry, yet their application is often challenged by formulation issues, including the formation of crystal structures and metastable states. This research project seeks to address these challenges by employing advanced computational modelling techniques, such as coarse-grained molecular dynamics simulations, in conjunction with AI and machine learning methodologies. The aim is to elucidate how the production and molecular composition of peptide materials can be precisely controlled through chemical modifications. Insights gained from these computational simulations will be validated through collaboration with an experimental partner, thereby bridging theoretical predictions with practical outcomes.