Combining two unique AI platforms for the discovery of novel genetic therapeutic targets & preclinical validation of synthetic biomolecules to treat Acute myeloid leukaemia (AML).

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This project is focused on the discovery of first-in-class drug candidates for the treatment of Acute Myeloid Leukaemia (AML) based on a novel approach to identifying novel genetic targets.AML is a high-risk hematologic malignancy with a high unmet need. Limited treatment options exist, particularly for patients who are ineligible for intensive chemotherapy or experience relapse. AML is rare, making up around 1% of all cancers. In the UK around 3,100 patients will be diagnosed with AML in 2023 (CRUK). Incidence rates are typically higher for those over 45\. Mortality in older patients is high, around 2,700 patients in the UK will die annually from AML. The 5-year relative survival rate for people over twenty with AML is 28%. Poor outcomes due to drug resistance and relapse is common in patients with AML.This project will combine the unique AI-based bioinformatics platforms and expertise of two SMEs, based in the UK and Switzerland, to tackle the problem of AML using AI, machine learning and synthetic biology to advance new disease understanding, novel target identification, and novel drug discovery.