Preclinical validation of synthetic biomolecules to treat Breast Cancer from AI-enabled discovery of novel lncRNA therapeutic targets.

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This project is focused on the discovery and preclinical validation of first-in-class drug candidates for the treatment of Triple Negative Breast Cancer (TNBC) based on a novel approach to identifying novel genetic targets.TNBC is a high-risk malignancy with a high unmet need. TNBC grows and spreads faster than other invasive breast cancer subtypes, has fewer treatment options and a poorer prognosis. TNBC is traditionally considered the most difficult type of breast cancer to treat and patient outcomes are extremely poor relative to other subtypes.TNBC makes up around 15% of all breast cancers. In the UK around thousands of patients will be diagnosed with TNBC in 2023\. Incidence rates are high in women under 40\. The 5-year relative survival rate for patients where TNBC has spread to distant parts of the body (such as the lungs, liver, or bones) is 12%. Poor outcomes due to drug resistance and relapse are also common in patients with TNBC.This project will validate the results of a unique new AI-based bioinformatics platform being used to tackle the problem of highly genetically mediated cancers. The platform uses AI, machine learning and synthetic biology to advance new disease understanding, identify novel targets, and discover novel biologic drugs.