Digital Twins
High-Fidelity Predictive Modeling for Precision Medicine and R&D
Our Digital Twin framework represents the next evolution in evidence-based medicine, transforming static data into dynamic, predictive models. Leveraging over a decade of longitudinal follow-up, we provide highly granular virtual twins across critical therapeutic areas: Reproductive Health (IVF), HPV-associated Oropharyngeal Cancer, Arrhythmogenic Cardiomyopathy, and Type 2 Diabetes. These models integrate multi-modal data layers, from clinical phenotypes to deep genomic and transcriptomic signatures, allowing researchers to simulate disease progression and therapeutic responses with unprecedented accuracy.
Each digital twin is built upon a foundation of real-world evidence, ensuring that simulations reflect biological reality. For our IVF cohort (400+ cases), this includes integrated parental genetics, blastocyst secretome data, and long-term child health follow-ups. Our twins in oncology and cardiology are designed to accelerate drug discovery and optimize clinical trial designs by providing high-resolution virtual control arms. All models are developed in strict adherence to the EU AI Act and SOP 00.2, providing a secure, compliant environment for advanced computational research.
Key Capabilities:
Multimodal Integration: Seamless synthesis of genomic, molecular, and longitudinal clinical data.
IVF Specialized Dataset: 400+ comprehensive digital twins tracking the journey from parental genetics to 3-year post-birth outcomes.
Complex Pathologies: Dedicated models for HPV-associated oncology, arrhythmogenic cardiomyopathy, and metabolic disorders (T2D).
Regulatory Gold Standard: Built to meet the stringent requirements of the EU AI Act and GDPR for secondary data use.
Custom Feasibility: We offer tailored modeling and feasibility studies to align our digital twins with your specific therapeutic targets.