Engineering T cell receptors in TCR-T cell therapy using Machine Learning

Adoptive cell transfer (ACT) is a promising approach in cancer immunotherapy. It consists in providing a cancer patient with a large number of immune cells that were previously grown and multiplied in a lab. One of the techniques in ACT is T cell receptor–engineered T (TCR-T) cell therapy. TCR-T cells are genetically engineered cells that express a receptor directed against a specific neoantigen. This antigen is a protein expressed in cancer cells as a result of tumor-specific mutations in their DNA. Though the use of TCR-T cells holds great promise in improving the sensitivity and efficacy of cancer immunotherapy, the process of engineering cell therapies that target neoantigens in cancer is complex and time-consuming. To address these challenges, our customer asked us to apply machine learning to this process.