VHT
Patient dataset + computer model
A virtual human twin (VHT) is a digital representation of a human health or disease state. They refer to different levels of human anatomy (e.g. cells, tissues, organs or organ systems).
VHTs are built using software models and data and are designed to mimic and predict behaviour of their physical counterparts, including interaction with additional diseases a person may have.
European Commission’s Virtual Human Twins initiative for health and care
The technology
1
from patient data to personalized VHTs
2
HPC simulations of organ function and treatment response.
3
Insights generation, scale predictions
4
web-based platform tailorable to different use cases.
Our simulation engine
Co-developed with the Barcelona Supercomputing Center, Alya powers our ability to model cardiac function based on real patient data and geometries by simulating the complex multi-physics underlying our models, including electrophysiology, biomechanics, and hemodynamics.
Multiphysics
MultiScale
High Performance Computing
Full-organ model
Key aspects
Our technology is built on real clinical data, including high-resolution imaging and diagnostics, under strict data governance protocols.
Our models rely on centuries of mathematical and physical models of nature, ensuring that predictions are interpretable, reproducible and consistent with real-world science.
Our technology is developed by a team of senior engineers and domain scientists with experience in modeling and simulation, medical informatics and AI.
We compare simulated outputs to actual clinical outcomes to ensure alignment between predictions and biological evidence.
For precision medicine
Our approach starts with creating 3D models of individual patients. These models integrate patient-specific data into a multiphysics and multiscale simulation environment powered by high-performance computing and physics-based solvers.
This enables quantitative predictions of clinical outcomes, such as cardiac risk, therapeutic efficacy, and patient-specific biomarkers and indicators. Our patient-specific models capture the unique physiological, anatomical, and functional characteristics of each individual.
Patient data - Echography
Patient data - Segmentation
ELEM whole heart Multiphysics model
Outputs — Quantitative predictions of clinical outcomes
For in silico clinical trials
Beyond individual models, we build statistically diverse Virtual Populations starting from real patient data.
Using ELEM's proprietary technology, powered by advanced AI tools, these cohorts are scaled up to thousands of virtual patients with different risk profiles, anatomies, and responses.
This enables bigger and better trials that account for variability, safety and efficacy, across a broad patient landscape. Our Virtual Populations mirror the diversity of real populations, from healthy to pathological conditions.
More info on how ELEM Virtual Humans can help you?
Contact usR&D and Future Vision
Driven by clinical needs and scientific opportunities, we are expanding beyond cardiovascular applications to address broader and more complex challenges in human biology. Current R&D lines include:
World wide collaborations
Oxford University
(UK)
Universidad Politécnica de Valencia
(Spain)
Universitat Pompeu Fabra
(Spain)
University College London
(UK)
Washington University of Saint Louis
(US)
Hôpital Européen Georges-Pompidou
(France)
Hospital de la Santa Creu i Sant Pau
(Spain)
Barcelona Supercomputing Center
(Spain)
Media Coverage, Publications and Conferences
ELEM actively participates in research collaborations and contributes to peer-reviewed journals, leading conferences and clinical studies.
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