Investigating the role of post-remission therapies in the eradication of founder mutations in Acute Leukaemia

This thesis explores the use of prognostic models with machine learning to determine groups who may or may not benefit from post remission therapy with stem cell (or bone marrow) transplantation, identifying populations who currently do not benefit from this intervention. Following this it explores the use of specialised techniques to monitor in blood for the evidence of recurrence of leukaemia following transplant.