MODEL
Mathematical links between chemo-topography and biological response
In this work packages, we will apply a suite of machine learning (ML) and data curation methods (previously developed by our team in the Discovery-PG) as well as other new AI-based methods (deep learning and evolutionary algorithms - EA) to efficiently explore the vast design space of topographically patterned biomaterials. We will also employ Design of Experiments and ML models to maximize the coverage of design space for modelling with the minimum number of experiments in the MAKE and MEASURE WPs. Quantitative structure-property relationships (QSPR) that mathematically link materials topography and chemistry to their invoked biological responses will be used to identify design rules with which to propose new biomaterials.