ELEM Biosimulation technology combines clinical data, mechanistic modeling, physics-based simulation and AI-driven analytics to support model-informed drug development (MIDD).
VHT
ELEM virtual human methodology enables researchers to explore treatment responses and disease progression without exposing patients to unnecessary risk.
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
Quantitative predictions supporting model-informed drug development across discovery, safety assessment and clinical development.
1
From patient data to personalised Virtual Human Twins
2
HPC simulations of organ function and treatment response
3
Accelerated insights generation and predictions at scale
4
Web-based platform customisable to different use cases
Our biosimulation engine
Co-developed with the Barcelona Supercomputing Center, Alya is the physics-based simulation engine at the core of ELEM biosimulation platforms. It models organ function from real patient data and geometries, solving the coupled multi-physics of electrophysiology, biomechanics and hemodynamics at full-organ scale.
Multiphysics
MultiScale
High Performance Computing
Full-organ model
Key aspects
ELEM Biosimulation technology is backed by validated data, transparent versioning and rigorous scientific methodology.
ELEM Biosimulation Technology is built on real clinical data, including high-resolution imaging and diagnostics, under strict data governance protocols.
ELEM physics-based modeling approach relies on established mathematical and physiological principles, ensuring that biosimulation outputs are interpretable, reproducible and consistent with real-world science.
ELEM Technology is developed by senior engineers and domain scientists with expertise in computational modeling, QSP/PBPK methodologies, medical informatics and AI, for Model Informed Drug Development.
We compare simulated outputs to actual clinical outcomes to ensure alignment between predictions and biological evidence.
For precision medicine
ELEM 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 MIDD
For in silico clinical trials
Beyond individual virtual human twins, we build statistically diverse Virtual Populations for in silico clinical trials, starting from real patient data and scaled using AI.
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.
Discover our platform!
V.HEART TrialsR&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:
Driving Clinical and Scientific Progress
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.
Replicating clinical placebo effects in computational trials: Bridging the gap between in silico and clinical studies
Publications
18/10/2025
Read nowDigital twins and Big AI: the future of truly individualised healthcare
Publications
01/08/2025
Read nowExpanding Digital Twins Use from Biopharma to Virtual Human Development
Media coverage
01/10/2024
Read nowGet started
One of our experts will get in touch with you
