Adsilico
Adsilico provides a computational modeling and generative AI platform that creates fully synthetic virtual patient populations for in silico trials of implantable medical devices. The platform enables device makers to assess safety and efficacy across diverse anatomies—spanning sex, age, ethnicity, and disease severity—without exposing real patients to risk. Its Virtual Chimera™ technology builds high-fidelity models from anonymised clinical imaging, with credibility assessments aligned to ASME V&V 40 and FDA guidance.
- Artificial Intelligence
- Healthcare Technology
- Software Only
- Data & Analytics
- Biotechnology
Funding
Raised to date
£13.5MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Est. $17.1Macross 2 rounds
P£10M · Series A
Announced Oct 2026 · from article date
Disclosed cumulative: $17.1M
Founders
Product
Problem
Traditional medical device testing relies on human trials, which are costly, time-consuming, and may expose patients to unnecessary risks. Identifying design flaws early in the development process is challenging, leading to increased R&D expenses and potential clinical failures. Furthermore, access to diverse patient populations for testing can be limited, hindering the comprehensive evaluation of device safety and efficacy.
Solution
Adsilico offers a computational modeling and generative AI platform that creates customizable virtual patient populations for in silico trials, enabling medical device manufacturers to assess device safety and efficacy without human testing. The platform simulates diverse anatomical, physiological, and pathological conditions at scale, allowing for early identification of design flaws and optimization of clinical trial protocols. By using virtual patients, Adsilico reduces the need for extensive human trials, accelerates R&D timelines, and minimizes the risk of patient harm. The technology facilitates the exploration of device performance across a wide range of patient characteristics, including under-represented and ethically challenging populations. Virtual populations are validated against real patient data under clinical oversight, and each study documents its data provenance, assumptions, validation, and uncertainty. Model credibility is assessed with the risk-informed principles of ASME V&V 40, on which FDA’s 2023 guidance builds, supporting regulatory conversations.
Target Audience
The primary target audience includes medical device manufacturers, research institutions, and regulatory agencies involved in the development, testing, and approval of medical devices, with a particular focus on structural heart and neurovascular device makers approaching feasibility and pivotal decisions.
Features
- Generative AI technology (Virtual Chimera™) for creating high-fidelity, fully synthetic virtual patient models built from anonymised clinical imaging
- Customizable virtual models of human anatomy, physiology, and pathology, spanning sex, age, ethnicity, anatomy, and disease severity
- Scalable generation of virtual patient populations, from dozens to thousands, including rare anatomies and edge cases
- Physics-based simulation to assess device behavior across the population, with documented and traceable stages
- Clinical review of study results to ensure they make clinical sense, with findings framed for leadership, clinical, and regulatory decisions
- Credibility assessment aligned with ASME V&V 40 and FDA’s 2023 guidance, supporting regulatory conversations