Investigation of alternative strategies for cellular damage rescue and disease correction in Fabry disease and it’s in silico prediction using machine learning model

Due to the current limitations on cellular damage rescue and disease correction in Fabry disease, this study investigates novel strategies to address these. In addition, with the huge cost on drug trials, this study also investigates machine learning models to predict diagnosis and drug responses in Fabry disease. Together, this thesis summarises a combination of in vitro and in silico approaches in Fabry disease which may offer important insights for future interventions.