Pubu Abeyasinghe (Pubuditha Abeyasinghe)
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Exploring computational modelling to predict disease progression in Huntington’s Disease using combined IMAGE-HD, PREDICT-HD and TRACK-HD datasets
RESEARCH DATE: 07/10/2019
Applications of computational modeling in Huntington’s disease is a promising avenue in research directing towards predicting the disease progression. In the past few years, researchers have shown the positive impacts of modeling the disease progression to find the most sensitive biomarkers not only in Huntington’s disease but also in other neurodegenerative disease such as Alzheimer’s’ disease. We are interested in applying computational modeling techniques to the combined data sets from IMAG-HD, PREDICT-HD and TRACK-HD studies to find a model that could explain the disease progression across studies with high accuracy. In the process of developing the model we aim explore and incorporate not only the clinical measures but also the behavioral and imaging measures and find the best combination of measures that results in the highest predictability of disease progression. These modelling techniques will be crucial to understand the level of contribution of each measure to disease progression which then can be used in the advancement of developing more effective treatment methods or therapeutical approaches targeting the most sensitive measures, to delay the neural degeneration and the subsequent onset of the Huntington’s disease.