TWINNING: Scalable technologies for creating virtual patient twin populations to accelerate in-silico enabled medical device innovation.

双胞胎：用于创建虚拟患者双胞胎群体的可扩展技术，以加速计算机模拟医疗设备创新。

• 批准号: 10103504
• 金额: $ 86.54万
• 依托单位: ADSILICO LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10103504
• 关键词: TWINNING; Scalable; technologies; creating; virtual

**ad**silico, a spin-out from the University of Leeds (UoL), is aiming to Define, Disrupt and Dominate the in-silico trials space to accelerate medical device innovations. It will become the world's first end-to-end in-silico trials service provider. adsilico's technology for creating virtual populations (VP) of anatomy and physiology builds upon 15+ years of research conducted at CISTIB, Centre for Computational Imaging and Simulation Technologies in Biomedicine from UoL.The team conducted the first in-silico trial (IST) for devices used to treat cerebral aneurysms (Sarrami-Foroushani, A, et al, 2021). The performance of flow diverters was assessed in a VP comprising cerebral vessel and aneurysm geometries and associated blood flow waveforms. The results demonstrated that ISTs can replicate and expand on the insights gained from equivalent real clinical trials, at a fraction of the cost and time, and with no real patient involvement. Impact through industrial translation of the research requires enhancement of the prototype image computing workflows for creating the vessel/aneurysm VPs, so that outputs are of suitable quality and reliability for commercial use.The team has a proven track record of conducting large-scale image analysis studies and building virtual patient populations, especially in the cardiovascular and neurovascular domains. For example, we recently analysed 40k subjects' cardiac magnetic resonance (CMR) images across 50 time points of the cardiac cycle, amounting to 2xmillion CMR image volumes (Xia, Y., et al, 2022). We are the only group in the world to have undertaken such analyses at this scale. This resulted in a curated data set of 2 million 3D full heart geometries and the associated, validated workflows used to create the same.This project aims to refine and translate a prototype for creating high-quality cerebrovascular and aneurysm virtual patient populations that are suitable for use within in-silico studies.**Key deliverables:** 1\. Securing early adopters.2\. Define QA processes for compliance with applicable regulations/standards and for audit purposes.3\. Cerebral aneurysm patient data access, curation/preparation. 4\. Strategy for automating management of primary/derived data.5\. Enhancement/validation of workflow for creating cerebrovascular and aneurysm VPs and design-controlled integration (to execution platform).6\. Create simulation ready VPs for neurovascular devices (target 5000 instances).7\. Validation of VPs with customer-driven exemplar.8\. Design/implement secure environment to access/store/manage digital assets.9\. Contractual frameworks (**ad**silico access to data and customer use of derived data).10\. Determine commercial value of cerebrovascular VPs.11\. Validation of commercial model.

**ad**silico是利兹大学（UoL）的一个分支，旨在定义、颠覆和主导计算机试验领域，以加速医疗器械创新。它将成为世界上第一个端到端的计算机模拟试验服务提供商。adsilico创建解剖学和生理学虚拟群体（VP）的技术建立在UoL生物医学计算成像和模拟技术中心CISTIB进行的15年以上研究的基础上。该团队对用于治疗脑动脉瘤的器械进行了首次计算机模拟试验（IST）（Sarrami-Foroushani，A，et al，2021）。在包括脑血管和动脉瘤几何形状以及相关血流波形的VP中评估了血流导向装置的性能。结果表明，IST可以复制和扩展从等效的真实的临床试验中获得的见解，成本和时间只有一小部分，而且没有真实的患者参与。通过研究的工业转化产生的影响需要增强用于创建血管/动脉瘤VP的原型图像计算工作流程，以便输出具有适合商业用途的质量和可靠性。该团队在进行大规模图像分析研究和构建虚拟患者人群方面拥有良好的记录，特别是在心血管和神经血管领域。例如，我们最近分析了心动周期50个时间点的40 k受试者的心脏磁共振（CMR）图像，总计2xmillion CMR图像体积（Xia，Y.，等人，2022）。我们是世界上唯一一个进行这种规模分析的组织。该项目的目标是完善和转化一个原型，用于创建高质量的脑血管和动脉瘤虚拟患者人群，这些患者人群适用于计算机模拟研究。**主要交付成果：** 1\.保护早期采用者。2\.定义质量保证过程，以符合适用的法规/标准和审计要求。脑动脉瘤患者数据访问、治疗/准备。4\.自动化管理原始/衍生数据的策略。增强/验证用于创建脑血管和动脉瘤VP的工作流程以及设计控制集成（到执行平台）。为神经血管设备创建模拟就绪VP（目标5000个实例）。用客户驱动的范例验证VP。设计/实施安全环境以访问/存储/管理数字资产。合同框架（**ad**silico访问数据和客户使用派生数据）。确定脑血管VPs.11的商业价值。商业模式的验证。