Using AI and big data to identify a set of biologically validated drug targets for hard-to-treat cancers

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The ultimate goal in cancer treatment is to identify the therapeutic vulnerabilities of a patient's tumour and use this to design a personalised medicine regime. The recent cost reduction in genomic technologies, has allowed extensive genomic analysis of clinical samples but for most tumour types, we lack the ability to translate these data into a successful therapeutic strategy. The Pearl bioinformatics laboratory have therefore developed a suite of artificial intelligence (AI) algorithms that use cancer genomic and other 'big' data sets to predict druggable vulnerabilities in cancer cells.In this PhD, students will use AI-techniques using multi-platform, genomic cancer data and protein-protein interaction data, to identify a set of set of novel, drug targets for hard-to-treat cancers. Target validation will be carried out at the Garrett laboratory at Kent, and at Cancer Research Horizons.TrainingThe student will be trained in programming, bioinformatics, big data and data science, cancer biology and therapeutics, in the Pearl bioinformatics laboratory. Training in cancer cell culture, cell proliferation analysis, and RNA interference technology for target validation, will be provided in the Garrett Lab. The CASE Partner, Cancer Research Horizons, will provide training in CRISPR technology and provide access to their extensive and unique catalogue of small molecule drugs and tool compounds for more detailed target validation.