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

从利兹大学（UoL）分拆出来的ad silicon旨在定义、颠覆和主导芯片试验领域，以加速医疗设备的创新。它将成为世界上第一家端到端硅试验服务提供商。adsilico创建解剖学和生理学虚拟种群（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年以上的研究基础上。该团队对用于治疗脑动脉瘤的设备进行了首次计算机试验（IST） （sarrami - foroushai， 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中评估分流器的性能。结果表明，ist可以复制和扩展从等效的真实临床试验中获得的见解，成本和时间都很低，而且不需要真正的患者参与。通过工业转化的研究需要增强原型图像计算工作流程，以创建血管/动脉瘤副总裁，从而使输出具有合适的质量和可靠性，可用于商业用途。该团队在进行大规模图像分析研究和构建虚拟患者群体方面有着良好的记录，特别是在心血管和神经血管领域。例如，我们最近分析了40k名受试者在心脏周期的50个时间点的心脏磁共振（CMR）图像，共计200万CMR图像体积（Xia， Y., et al ., 2022）。我们是世界上唯一一个在这种规模上进行这种分析的团队。这就产生了一个包含200万个3D全心脏几何形状的数据集，以及用于创建相同几何形状的相关验证工作流程。该项目旨在完善和翻译一个原型，以创建适合在计算机研究中使用的高质量脑血管和动脉瘤虚拟患者群体。**关键成果：** 1\。确保早期采用者的安全。为符合适用的法规/标准和审核目的，定义QA过程。脑动脉瘤患者资料获取、整理/准备。4 \。主/派生数据的自动化管理策略[j]。脑血管和动脉瘤副总裁创建工作流程的增强/验证以及设计控制集成（到执行平台）。为神经血管设备创建仿真就绪的副总裁（目标5000个实例）。用客户驱动的范例验证副总裁。设计/实现安全的环境来访问/存储/管理数字资产。合同框架（数据访问和客户对衍生数据的使用）。确定脑血管vps的商业价值。商业模型的验证。

**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.