The success rate for cancer drug development is ~5%. Imagen has pioneered an automated, sophisticated algorithmic technique - to date modelling >150,000 patient treatment data points, which is now being used to accelerate the drug development process and reduce failure. Historically ~£3m raised.
We aim to benefit patients by revolutionising cancer research for pharma.
Our unique innovative platform aims to identify the most effective cancer treatments, helping to deliver personalised, life-changing medicines.
Every cancer is genetically unique, making it difficult for oncologists to predict which treatments to select & which to avoid. Imagen can test 1000's of individual tumours across a wide range of cancer drugs in-vitro, aiming to predict which are most likely to be effective.
Imagen has fully developed its proprietary predictRx assay, enabling oncologists to refer patients to Imagen. This is creating a source of tumour samples to which industry does not have access, allowing Imagen to expand into the pharma sector by satisfying its unmet demand for patient-derived cancer models.
In early-stage drug development, companies must use pre-clinical 'models' that closely resemble real patients, but few such models with patient-relevant data are available. This scarcity contributes to the high drug development failure rate (~95%), which Imagen is addressing by developing 1000's of patient-derived cancer models using its global access to patients.
We require capital to scale our infrastructure with the aim of creating the world's leading Biobank of clinically relevant patient-derived cancer models whilst building the most comprehensive big data set available in cancer research.