10103504TWINNING: Scalable technologies for creating virtual patient twin populations to accelerate in-silico enabled medical device innovation.ActiveCollaborative R&DInnovate UK**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.