Development of Machine Learning tools for in silicon chimeric antigen receptor (CAR) design
Development of Machine Learning tools for in silicon chimeric antigen receptor (CAR) design
批准号:
10026469
负责人:
金额:
$50.83万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2022
资助国家:
英国
项目状态:
已结题
起止时间:
2022 至 --
中文摘要
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英文摘要
Adoptive cell therapy is a treatment of patients using their own, modified immune cells. It involves harvesting T cells - the immune cells that normally recognise and eliminate pathogens - from the patient's blood, reprogramming them to recognise cancer cells and re-introducing the newly modified cells back into the patient to destroy tumours. The modifying factor used to arm these T cells against cancer is called Chimeric Antigen Receptor or CAR, in short. Using the lock and key analogy, just as every lock can only be opened with the appropriate key, each type of cancer, with its unique antigens, can only be recognised by a specific engineered CAR.Currently, the National Health Service (NHS) is providing CAR-T cell therapy against malignant B cells that express antigen called CD19 to children and young adults with relapsed or difficult-to-treat leukaemia and lymphoma. The treatment is particularly effective in patients who did not respond to chemotherapy, offering real hope to those who otherwise would have no other options. However, this CAR therapy can only treat a very specific type of cancer, leaving much room for improvement. The concerted efforts into the development of specific CAR therapies against other cancers are hindered by the tedious process of target discovery and receptor optimisation.Coding.bio is streamlining the process of building better receptors, making it faster, cheaper, and more diverse. Our objective is to help bring this transformative therapy to a wider patient population.
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Understanding structural evolution of galaxies with machine learning
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批准号:
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项目类别:省市级项目
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资助金额:10.0万元
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批准年份:2022
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负责人:Nicola Rosario Napolitano
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依托单位: