Feasibility study of a high-performance data analytics pipeline for highly stratified approach to cardiovascular disease

PlaqueTec拥有一种先进的医疗导管，可以直接在冠状动脉疾病部位检测生物信号。临床应用表明，冠状动脉内生物标记物(I)因病情不同而不同，II)因患者不同而不同，III)因全身生物标记物水平(即在标准血样中检测到的生物标记物)而不同。领先的临床医生认识到了PlaqueTec平台实现个性化治疗策略的潜力。PlaqueTec现在正准备支持研究人员主导的研究(ILS)，在这种研究中，临床医生和研究人员(工业和学术)可以访问PlaqueTec的技术和数据，以帮助更好地诊断和治疗他们的患者。PlaqueTec的战略是通过一个研究人员领导的研究计划，建立世界上最全面的冠状动脉疾病生物标志物数据库。PlaqueTec将在一个独特的门户中使用机器学习和数据科学，该门户将允许上传任何患者的生物标记物，并针对最有意义的患者队列进行评估，以a)最初提供对患者风险的更多“情景”评估，以及b)最终根据真实世界的证据预测最有可能带来好处的治疗策略。PlaqueTec面临的直接挑战是高效地开发一个可扩展的、基于云的数字健康系统，该系统能够以一种向所有潜在的利益相关者(临床医生、患者、监管机构、治疗提供者)提供最大效用的方式来管理、分析和输出“真实世界”的ILS数据，政府和保险公司)。这个可行性项目的目标/问题：*什么功能**：与临床医生/利益相关者接触，定义数字健康系统的关键功能，PlaqueTec将通过这些功能将其服务商业化；*什么架构**：推荐并指定最适合满足利益相关者要求的分析解决方案架构；*最佳机器学习方法**：根据PlaqueTec数据库的组成确定最佳数据科学和机器学习策略。所附项目使PlaqueTec能够：i)接触潜在最终用户并定义需求；ii)与敏捷开发和数据科学专家合作开发门户演示程序；iii)测试门户演示程序基于当前数据集回答利益相关者问题的能力。该项目将提供一个基于云的架构，该架构可以快速扩展，为PlaqueTec计划的ILS计划提供商业服务。创新：目前冠心病的治疗缺乏精确度。抗癌已经取得了巨大的进展，因为患者得到了基于对他们的疾病更好的生物特征的高度特异性/针对性的治疗。这项创新的目的是将同样的方法转化为治疗冠心病。“

"PlaqueTec has an advanced medical catheter that can detect biological signalling directly at the site of coronary artery disease. In clinical use it has shown that intracoronary biomarkers (i) differ depending on the state of disease ii) differ from patient to patient and iii) differ to systemic biomarker levels (i.e. those detected in standard blood sample). Leading clinicians recognise the potential for PlaqueTec's platform to enable personalised treatment strategies. PlaqueTec is now preparing to support investigator led studies (ILS) where clinicians and researchers (both industrial and academic) can access PlaqueTec's technology and data to help better diagnose and treat their patients.PlaqueTec's strategy, via a programme of investigator led studies, is to build world's most comprehensive database of coronary artery disease biomarkers. PlaqueTec will use machine learning and data science within a unique portal that will allow any patient's biomarker ""profile"" to be uploaded and assessed against the most meaningful patient cohorts to a) initially provide a more ""contextualised"" assessment of patient risk and b) ultimately predict therapeutic strategies most likely to offer benefit based on real world evidence.PlaqueTec's immediate challenge is to efficiently develop a scaleable, cloud based digital health system that can curate, analyse and output ""real world"" ILS data in a manner that delivers maximum utility to all potential stakeholders (clinicians, patients, regulators, therapy providers, governments and insurance companies).This feasibility project's objectives/questions:* **What functionality**: Engage with clinicians/stakeholders to define the key functionality of digital health system through which PlaqueTec will commercialise its services;* **What architecture**: Recommend and specify the analytics solution architecture that is best suited to meeting the stakeholder requirements;* **Best machine learning approach**: Identify the best data science and machine learning strategy given the composition of the PlaqueTec database.The enclosed project enables PlaqueTec to i) engage with potential end users and define requirements ii) work with Agile development and data science experts to develop a portal demonstrator and iii) test the ability of the portal demonstrator to answer stakeholder questions based on current datasets. The project will deliver a cloud-based architecture that can be rapidly scaled to provide commercial services to PlaqueTec's planned ILS programme.Innovation: today the treatment of coronary heart disease lacks precision. Massive progress has been made against cancer because patients are given highly specific/targeted treatments based on better biological profiling of their disease. This innovation aims to translate the same approach to coronary heart disease."