Guiding treatment decisions in breast cancer with artificial intelligence

三阴性乳腺癌（TNBC）是乳腺癌中最具侵袭性的一种，约占所有乳腺癌患者的20%。它不成比例地影响年轻女性和少数民族，并对生活质量，生育能力和工作能力产生深远影响。有压倒性的科学证据表明，TNBC是复杂的，临床结果多种多样。与许多其他癌症不同，目前还没有测试能够使我们识别出那些有最坏结果风险的人和那些可能有良好结果的人。这意味着我们必须采取“一刀切”的方法，并为大多数患者推荐系统化疗。不幸的是，化疗会产生严重的副作用，包括手脚神经损伤和危及生命的感染。一些副作用可能是终身的，使人衰弱，导致焦虑和影响亲密关系。这种迫切需要改善生活质量和结果，促使我们开发了一种新的临床生物标志物测试，称为 **SIPA：空间免疫生态预后评估 **。SIPA是一种快速的人工智能测试，只需要常规生成的样本。它可以准确测量每个患者对肿瘤的独特免疫反应，并设想在几种组织癌症中常规使用，以加速精准医学途径。目前，SIPA主要作为TNBC的辅助测试，它可以用于预测哪些患者可能具有最佳结果并避免化疗，同时确定其他可能受益于新疗法，如免疫疗法。最终，我们打算将SIPA用于帮助癌症患者提供个性化治疗信息，通过该项目，我们的目标是开发高标准的质量管理体系，以便在专家的严格监督下在临床环境中前瞻性地测试SIPA，同时致力于在英国和欧洲推出（体外诊断）IVD CE标志监管计划。该项目使我们更接近于最大限度地利用基于人工智能的尖端技术，使英国及其他地区的癌症患者受益。通过SIPA实现的精确患者分层解决了关键的NHS优先事项，并可能彻底改变TNBC患者的治疗。我们的附加价值是为患者-防止不必要的毒性和失去在生命中最关键的时刻寻求更有效治疗的机会;为医疗保健提供者-节省潜在无效治疗的巨大成本;为临床医生-通过使他们能够提供个性化治疗来实现有效的精准肿瘤学。

Triple negative breast cancer (TNBC) is the most aggressive form of breast cancer, affecting around 20% of all people with breast cancer. It disproportionately affects younger women and ethnic minorities, and has profound effects on quality of life, fertility, and ability to work.There is overwhelming scientific evidence that TNBC is complex with diverse clinical outcomes. Unlike many other cancers, there is currently no test that enables us to identify those at risk of the worst outcomes and those likely to have excellent outcomes. This means that we must take a 'one size fits all' approach and recommend systematic chemotherapy for most patients. Unfortunately, chemotherapy produces significant side-effects, including damage to nerves in the hands and feet and life-threatening infections. Some side effects can be life-long, debilitating, cause anxiety and impact close relationships.This imminent need to improve quality of life and outcomes led us to develop a novel clinical biomarker test known as **SIPA: Spatial Immuno-Ecology Prognostic Assessment**. SIPA is a rapid, artificial intelligence-powered test that only requires routinely generated samples. It accurately measures each individual patient's unique immune response to their tumor, and it is envisaged to be routinely used across several tissue cancers to accelerate precision medicine pathways.Currently, SIPA operates primarily as a prognostication test in TNBC, it can be used to predict which patients are likely to have the best outcomes and be spared chemotherapy, whilst identifying others that may benefit from new treatments such as immunotherapy. Ultimately, we intend for SIPA to be used to help inform personalized therapies for cancer patients.Through this project, we aim to develop high-standard quality management system to prospectively test SIPA in clinical settings under careful expert supervision, whilst working towards an (In-Vitro Diagnostic) IVD CE-mark regulatory plan in preparation to launch in the UK and Europe. This project brings us a step closer to maximize the reach of cutting-edge, AI-based technologies to benefit cancer patients in the UK and beyond. Precise patient stratification enabled by SIPA addresses key NHS priorities and could revolutionize treatment for patients with TNBC.**Our added values are for patients --- prevent unnecessary toxicity and lost opportunities to pursue more effective treatments in the most crucial time of their lives; for healthcare providers --- save tremendous costs on potentially ineffective treatments; and for clinicians ---efficient precision oncology by enabling them to offer personalized treatments.**