TCRID - Accelerating T-Cell receptor research and target identification through AI

**TCRID -通过人工智能加速t细胞受体研究和靶点识别**传统的癌症治疗方法（如化疗、放疗、手术）往往不能治愈，不能防止癌症复发，需要持续干预。基于t细胞受体（TCR）的细胞疗法是一种新的、有希望治愈的治疗方法，用于治疗无法治疗的晚期实体癌，如骨癌、肺癌和胃肠道癌。它们由来自患者的免疫细胞（t细胞）组成，这些细胞被基因重新编程为靶向癌症的TCR，繁殖并重新引入患者体内以摧毁癌细胞。靶向癌症的tcr很少见，但可以在癌症患者中发现，并且是开发基于tcr的细胞疗法的重要组成部分。然而，识别这种靶向癌症的tcr是一个极具挑战性、耗时和资本密集型的实验室过程，而且缺乏自动化和简化这一过程的计算方法。Exogene利用人工智能（AI）来显著加速发现新的靶向癌症的tcr，同时大大减少发现过程所需的时间和成本。与目前可用的显示分析不同，Exogene正在构建人工智能模型，通过结合内部湿实验室TCR筛选、10亿数据点训练数据集、结构建模和尖端深度学习，大规模预测TCR与靶点的相互作用。这项极具前景的技术将加速开发新的挽救生命的癌症治疗方法，为英国超过18万晚期实体癌患者（全球超过900万）提供治疗，否则这些患者的治疗选择和预期寿命将受到限制。该项目的结果将发表在同行评议的期刊上，并将加强英国在推进基于tcr的细胞疗法以应对全球癌症方面的世界领先地位。

**TCRID - Speeding up T-Cell receptor research and target identification through AI**Traditional cancer therapies (e.g. chemotherapy, radiotherapy, surgery) are often not curative, do not prevent cancer from re-emerging and require continuous intervention.T-cell-receptor(TCR)-based cell therapies are new, promising curative treatments for otherwise untreatable advanced solid cancers, such as bone, lung and gastrointestinal cancers. They consist of immune cells (T-cells), derived from patients, that are genetically reprogrammed with a cancer-targeting TCR, multiplied, and re-introduced into patients to destroy cancer cells.Cancer-targeting TCRs are rare but can be found in cancer patients, and are an essential component to developing TCR-based cell therapies. However, identifying such cancer-targeting TCRs is an incredibly challenging, time-consuming and capital-intensive laboratory process, and there is a lack of computational methods to automate and streamline the process. Exogene leverages artificial intelligence (AI) to significantly accelerate the discovery of new cancer-targeting TCRs, while drastically reducing the time and cost required for the discovery process.Unlike currently available display assays, which focus on the analysis of 1 TCR at the time, Exogene is building AI models to predict TCR-target interactions at massive scale by combining in-house wet lab TCR screening, a 1 billion data-point training dataset, structural modelling and cutting-edge deep learning.This highly-promising technology will accelerate the development of novel life-saving cancer treatments for more than 180,000 patients with advanced solid cancers in the UK (more than 9 million worldwide) that would otherwise have limited treatment options and life expectancy. The results of the project will be published in a peer-reviewed journal and will strengthen the UK's world-leading position in advancing TCR-based cell therapies to tackle cancer worldwide.