[Research Grant] Research and Training to create assets in the form of new companies to develop a new model to generate innovative therapies
Ente: UKRI Inn.Scholar
Scadenza: 2023-06-29
Importo max: 84.549 EUR
Paese: GB
Descrizione
Cancer Research UK has partnered with Deep Science Ventures to create an opportunity for early career stage researchers to build ventures that target the complexity of biology. This partnership brings together the world's largest independent funder of cancer research with the unique venture design process of Deep Science Ventures to create a programme that is exhaustive in the search for the best approach from both technical and commercial perspectives, and positioned for new venture growth from day one. Their aim is to identify and bring together entrepreneurial scientists, academic advisors and investors to design and build new companies in oncology.
In this project, the research goal is to develop therapies by leveraging the wealth of data of this new era to identify ways to kill cancer cells so that can escape from treatments.
My role will be to start as a Founder Analyst within DeepScienceVentures under their unique framework for venture creation. It's a part-time role working mainly involving research. In order to make this research successful, I will apply my skills sets of machine learning/artificial intelligence, understanding heterogeneity, developing patient-based biomarkers and hands-on experience in preclinical trials. This also provides opportunity to get trained in market analysis, and customer development together with the DSV team before incorporating our own start-up.
Cancer is an evolution machine. Decades before diagnosis, a multitude of different clones, carrying differential sets of mutations are setting the scene that makes almost any targeted therapy obsolete. The new era of personalised medicine and of immense knowledge of the genetics, epigenetics, gene expression, metabolomics, and clonal evolution of tumours, converges with the completion of flagship synthetic lethality studies, interrogating pan-cancer functional genomics. However, target discovery still focuses on finding targeted therapies against well-established cancer drivers from which cancer has already evolved out of, even years before diagnosis. This results in limited response rates in the clinic and quick evolution of resistance for targets against such drivers for example BRCA targeted PARP inhibitors.
Our Approach: We are stopping the chase for moving targets by building a highly advanced drug discovery machine, that leverages the wealth of data of this new era to identify vulnerable mechanisms that cancer cannot evolve out of and the specific context in which they are effective.
To achieve that, we identify cancer systems biology and specific mechanisms of irreversible cancer dependencies through advanced computational methods.
Our current approach sets the bar very high, to produce complete and sustained therapeutic responses. We have invented methods that have already produced potential candidates with strong independent validation.My role will be to start as a
Settori: Division of Molecular Pathology
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