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

使用人工智能和大数据来确定一组经过生物学验证的药物靶点，用于治疗难以治疗的癌症

• 批准号: 2886797
• 金额: --
• 依托单位: University of Sussex
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2886797
• 关键词: Using; AI; big; data; identify

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.

癌症治疗的最终目标是识别患者肿瘤的治疗脆弱性，并利用这一点来设计个性化的药物制度。最近基因组技术的成本降低，使得对临床样本进行广泛的基因组分析成为可能，但对于大多数肿瘤类型，我们缺乏将这些数据转化为成功的治疗策略的能力。因此，珍珠生物信息学实验室开发了一套人工智能(AI)算法，利用癌症基因组和其他大数据集来预测癌细胞中的可药物脆弱性。在这个博士学位中，学生们将使用人工智能技术，使用多平台、基因组癌症数据和蛋白质-蛋白质相互作用数据，来识别一套针对难以治疗的癌症的新型药物靶点。目标验证将在肯特郡的加勒特实验室和癌症研究地平线进行。培训学生将在珀尔生物信息学实验室接受编程、生物信息学、大数据和数据科学、癌症生物学和治疗学方面的培训。加勒特实验室将提供癌细胞培养、细胞增殖分析和靶标验证的RNA干扰技术方面的培训。CASE合作伙伴癌症研究地平线将提供CRISPR技术方面的培训，并提供对其广泛和独特的小分子药物和工具化合物目录的访问，以进行更详细的靶标验证。